4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

PubMed Central

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-01-01

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp–Davis–Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations. PMID:26758496

Model and parametric uncertainty in source-based kinematic models of earthquake ground motion

USGS Publications Warehouse

Hartzell, Stephen; Frankel, Arthur; Liu, Pengcheng; Zeng, Yuehua; Rahman, Shariftur

2011-01-01

Four independent ground-motion simulation codes are used to model the strong ground motion for three earthquakes: 1994 Mw 6.7 Northridge, 1989 Mw 6.9 Loma Prieta, and 1999 Mw 7.5 Izmit. These 12 sets of synthetics are used to make estimates of the variability in ground-motion predictions. In addition, ground-motion predictions over a grid of sites are used to estimate parametric uncertainty for changes in rupture velocity. We find that the combined model uncertainty and random variability of the simulations is in the same range as the variability of regional empirical ground-motion data sets. The majority of the standard deviations lie between 0.5 and 0.7 natural-log units for response spectra and 0.5 and 0.8 for Fourier spectra. The estimate of model epistemic uncertainty, based on the different model predictions, lies between 0.2 and 0.4, which is about one-half of the estimates for the standard deviation of the combined model uncertainty and random variability. Parametric uncertainty, based on variation of just the average rupture velocity, is shown to be consistent in amplitude with previous estimates, showing percentage changes in ground motion from 50% to 300% when rupture velocity changes from 2.5 to 2.9 km/s. In addition, there is some evidence that mean biases can be reduced by averaging ground-motion estimates from different methods.

The application of mean field theory to image motion estimation.

PubMed

Zhang, J; Hanauer, G G

1995-01-01

Previously, Markov random field (MRF) model-based techniques have been proposed for image motion estimation. Since motion estimation is usually an ill-posed problem, various constraints are needed to obtain a unique and stable solution. The main advantage of the MRF approach is its capacity to incorporate such constraints, for instance, motion continuity within an object and motion discontinuity at the boundaries between objects. In the MRF approach, motion estimation is often formulated as an optimization problem, and two frequently used optimization methods are simulated annealing (SA) and iterative-conditional mode (ICM). Although the SA is theoretically optimal in the sense of finding the global optimum, it usually takes many iterations to converge. The ICM, on the other hand, converges quickly, but its results are often unsatisfactory due to its "hard decision" nature. Previously, the authors have applied the mean field theory to image segmentation and image restoration problems. It provides results nearly as good as SA but with much faster convergence. The present paper shows how the mean field theory can be applied to MRF model-based motion estimation. This approach is demonstrated on both synthetic and real-world images, where it produced good motion estimates.

Learning Motion Features for Example-Based Finger Motion Estimation for Virtual Characters

NASA Astrophysics Data System (ADS)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-09-01

This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.

Motion compensation for cone-beam CT using Fourier consistency conditions

NASA Astrophysics Data System (ADS)

Berger, M.; Xia, Y.; Aichinger, W.; Mentl, K.; Unberath, M.; Aichert, A.; Riess, C.; Hornegger, J.; Fahrig, R.; Maier, A.

2017-09-01

In cone-beam CT, involuntary patient motion and inaccurate or irreproducible scanner motion substantially degrades image quality. To avoid artifacts this motion needs to be estimated and compensated during image reconstruction. In previous work we showed that Fourier consistency conditions (FCC) can be used in fan-beam CT to estimate motion in the sinogram domain. This work extends the FCC to 3\\text{D} cone-beam CT. We derive an efficient cost function to compensate for 3\\text{D} motion using 2\\text{D} detector translations. The extended FCC method have been tested with five translational motion patterns, using a challenging numerical phantom. We evaluated the root-mean-square-error and the structural-similarity-index between motion corrected and motion-free reconstructions. Additionally, we computed the mean-absolute-difference (MAD) between the estimated and the ground-truth motion. The practical applicability of the method is demonstrated by application to respiratory motion estimation in rotational angiography, but also to motion correction for weight-bearing imaging of knees. Where the latter makes use of a specifically modified FCC version which is robust to axial truncation. The results show a great reduction of motion artifacts. Accurate estimation results were achieved with a maximum MAD value of 708 μm and 1184 μm for motion along the vertical and horizontal detector direction, respectively. The image quality of reconstructions obtained with the proposed method is close to that of motion corrected reconstructions based on the ground-truth motion. Simulations using noise-free and noisy data demonstrate that FCC are robust to noise. Even high-frequency motion was accurately estimated leading to a considerable reduction of streaking artifacts. The method is purely image-based and therefore independent of any auxiliary data.

Improved frame-based estimation of head motion in PET brain imaging.

PubMed

Mukherjee, J M; Lindsay, C; Mukherjee, A; Olivier, P; Shao, L; King, M A; Licho, R

2016-05-01

Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type.

Simulation of range imaging-based estimation of respiratory lung motion. Influence of noise, signal dimensionality and sampling patterns.

PubMed

Wilms, M; Werner, R; Blendowski, M; Ortmüller, J; Handels, H

2014-01-01

A major problem associated with the irradiation of thoracic and abdominal tumors is respiratory motion. In clinical practice, motion compensation approaches are frequently steered by low-dimensional breathing signals (e.g., spirometry) and patient-specific correspondence models, which are used to estimate the sought internal motion given a signal measurement. Recently, the use of multidimensional signals derived from range images of the moving skin surface has been proposed to better account for complex motion patterns. In this work, a simulation study is carried out to investigate the motion estimation accuracy of such multidimensional signals and the influence of noise, the signal dimensionality, and different sampling patterns (points, lines, regions). A diffeomorphic correspondence modeling framework is employed to relate multidimensional breathing signals derived from simulated range images to internal motion patterns represented by diffeomorphic non-linear transformations. Furthermore, an automatic approach for the selection of optimal signal combinations/patterns within this framework is presented. This simulation study focuses on lung motion estimation and is based on 28 4D CT data sets. The results show that the use of multidimensional signals instead of one-dimensional signals significantly improves the motion estimation accuracy, which is, however, highly affected by noise. Only small differences exist between different multidimensional sampling patterns (lines and regions). Automatically determined optimal combinations of points and lines do not lead to accuracy improvements compared to results obtained by using all points or lines. Our results show the potential of multidimensional breathing signals derived from range images for the model-based estimation of respiratory motion in radiation therapy.

Estimation of slipping organ motion by registration with direction-dependent regularization.

PubMed

Schmidt-Richberg, Alexander; Werner, René; Handels, Heinz; Ehrhardt, Jan

2012-01-01

Accurate estimation of respiratory motion is essential for many applications in medical 4D imaging, for example for radiotherapy of thoracic and abdominal tumors. It is usually done by non-linear registration of image scans at different states of the breathing cycle but without further modeling of specific physiological motion properties. In this context, the accurate computation of respiration-driven lung motion is especially challenging because this organ is sliding along the surrounding tissue during the breathing cycle, leading to discontinuities in the motion field. Without considering this property in the registration model, common intensity-based algorithms cause incorrect estimation along the object boundaries. In this paper, we present a model for incorporating slipping motion in image registration. Extending the common diffusion registration by distinguishing between normal- and tangential-directed motion, we are able to estimate slipping motion at the organ boundaries while preventing gaps and ensuring smooth motion fields inside and outside. We further present an algorithm for a fully automatic detection of discontinuities in the motion field, which does not rely on a prior segmentation of the organ. We evaluate the approach for the estimation of lung motion based on 23 inspiration/expiration pairs of thoracic CT images. The results show a visually more plausible motion estimation. Moreover, the target registration error is quantified using manually defined landmarks and a significant improvement over the standard diffusion regularization is shown. Copyright © 2011 Elsevier B.V. All rights reserved.

Respiratory motion estimation in x-ray angiography for improved guidance during coronary interventions

NASA Astrophysics Data System (ADS)

Baka, N.; Lelieveldt, B. P. F.; Schultz, C.; Niessen, W.; van Walsum, T.

2015-05-01

During percutaneous coronary interventions (PCI) catheters and arteries are visualized by x-ray angiography (XA) sequences, using brief contrast injections to show the coronary arteries. If we could continue visualizing the coronary arteries after the contrast agent passed (thus in non-contrast XA frames), we could potentially lower contrast use, which is advantageous due to the toxicity of the contrast agent. This paper explores the possibility of such visualization in mono-plane XA acquisitions with a special focus on respiratory based coronary artery motion estimation. We use the patient specific coronary artery centerlines from pre-interventional 3D CTA images to project on the XA sequence for artery visualization. To achieve this, a framework for registering the 3D centerlines with the mono-plane 2D + time XA sequences is presented. During the registration the patient specific cardiac and respiratory motion is learned. We investigate several respiratory motion estimation strategies with respect to accuracy, plausibility and ease of use for motion prediction in XA frames with and without contrast. The investigated strategies include diaphragm motion based prediction, and respiratory motion extraction from the guiding catheter tip motion. We furthermore compare translational and rigid respiratory based heart motion. We validated the accuracy of the 2D/3D registration and the respiratory and cardiac motion estimations on XA sequences of 12 interventions. The diaphragm based motion model and the catheter tip derived motion achieved 1.58 mm and 1.83 mm median 2D accuracy, respectively. On a subset of four interventions we evaluated the artery visualization accuracy for non-contrast cases. Both diaphragm, and catheter tip based prediction performed similarly, with about half of the cases providing satisfactory accuracy (median error < 2 mm).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myronakis, M; Cai, W; Dhou, S

Purpose: To determine if 4DCT-based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery. Methods: This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external-surrogate based motion modeling. The accuracy of these estimated residual tumormore » motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days. Results: All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three out of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset. Conclusion: Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result. I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.« less

Inertial sensor-based smoother for gait analysis.

PubMed

Suh, Young Soo

2014-12-17

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother).

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation.

PubMed

Feghali, Rosario; Mitiche, Amar

2004-11-01

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.

An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging

PubMed Central

Mukherjee, Joyeeta Mitra; Hutton, Brian F; Johnson, Karen L; Pretorius, P Hendrik; King, Michael A

2014-01-01

Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference (MSD), mutual information (MI), normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation (NCC) and entropy of the difference (EDI). Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in 1 of the 5 patient studies, and with external-surrogate based correction in 3 out of 5 patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality. PMID:24107647

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Mode extraction on wind turbine blades via phase-based video motion estimation

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

2017-04-01

In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl

2013-03-15

Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phasemore » (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum improvement of the NCC value by 100% and of the RMSD value by 81%. The corresponding maximum improvements for the registration-based approach were 20% and 40%. In phases with very rapid motion the registration-based algorithm obtained better image quality, while the image quality of the MAM algorithm was superior in phases with less motion. The image quality improvement of the MAM optimization was visually confirmed for the different clinical cases. Conclusions: The proposed method allows a software-based best-phase image quality improvement in coronary CT angiography. A short scan data interval at the target heart phase is sufficient, no additional scan data in other cardiac phases are required. The algorithm is therefore directly applicable to any standard cardiac CT acquisition protocol.« less

Improved frame-based estimation of head motion in PET brain imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukherjee, J. M., E-mail: joyeeta.mitra@umassmed.edu; Lindsay, C.; King, M. A.

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition ismore » uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. Conclusions: The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type.« less

Improved frame-based estimation of head motion in PET brain imaging

PubMed Central

Mukherjee, J. M.; Lindsay, C.; Mukherjee, A.; Olivier, P.; Shao, L.; King, M. A.; Licho, R.

2016-01-01

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. Conclusions: The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type. PMID:27147355

3D pose estimation and motion analysis of the articulated human hand-forearm limb in an industrial production environment

NASA Astrophysics Data System (ADS)

Hahn, Markus; Barrois, Björn; Krüger, Lars; Wöhler, Christian; Sagerer, Gerhard; Kummert, Franz

2010-09-01

This study introduces an approach to model-based 3D pose estimation and instantaneous motion analysis of the human hand-forearm limb in the application context of safe human-robot interaction. 3D pose estimation is performed using two approaches: The Multiocular Contracting Curve Density (MOCCD) algorithm is a top-down technique based on pixel statistics around a contour model projected into the images from several cameras. The Iterative Closest Point (ICP) algorithm is a bottom-up approach which uses a motion-attributed 3D point cloud to estimate the object pose. Due to their orthogonal properties, a fusion of these algorithms is shown to be favorable. The fusion is performed by a weighted combination of the extracted pose parameters in an iterative manner. The analysis of object motion is based on the pose estimation result and the motion-attributed 3D points belonging to the hand-forearm limb using an extended constraint-line approach which does not rely on any temporal filtering. A further refinement is obtained using the Shape Flow algorithm, a temporal extension of the MOCCD approach, which estimates the temporal pose derivative based on the current and the two preceding images, corresponding to temporal filtering with a short response time of two or at most three frames. Combining the results of the two motion estimation stages provides information about the instantaneous motion properties of the object. Experimental investigations are performed on real-world image sequences displaying several test persons performing different working actions typically occurring in an industrial production scenario. In all example scenes, the background is cluttered, and the test persons wear various kinds of clothes. For evaluation, independently obtained ground truth data are used. [Figure not available: see fulltext.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

PubMed

Power, Jonathan D; Plitt, Mark; Kundu, Prantik; Bandettini, Peter A; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection

PubMed Central

Plitt, Mark; Kundu, Prantik; Bandettini, Peter A.; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). PMID:28880888

Human Pose Estimation from Monocular Images: A Comprehensive Survey

PubMed Central

Gong, Wenjuan; Zhang, Xuena; Gonzàlez, Jordi; Sobral, Andrews; Bouwmans, Thierry; Tu, Changhe; Zahzah, El-hadi

2016-01-01

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. PMID:27898003

A vision-based system for measuring the displacements of large structures: Simultaneous adaptive calibration and full motion estimation

NASA Astrophysics Data System (ADS)

Santos, C. Almeida; Costa, C. Oliveira; Batista, J.

2016-05-01

The paper describes a kinematic model-based solution to estimate simultaneously the calibration parameters of the vision system and the full-motion (6-DOF) of large civil engineering structures, namely of long deck suspension bridges, from a sequence of stereo images captured by digital cameras. Using an arbitrary number of images and assuming a smooth structure motion, an Iterated Extended Kalman Filter is used to recursively estimate the projection matrices of the cameras and the structure full-motion (displacement and rotation) over time, helping to meet the structure health monitoring fulfilment. Results related to the performance evaluation, obtained by numerical simulation and with real experiments, are reported. The real experiments were carried out in indoor and outdoor environment using a reduced structure model to impose controlled motions. In both cases, the results obtained with a minimum setup comprising only two cameras and four non-coplanar tracking points, showed a high accuracy results for on-line camera calibration and structure full motion estimation.

Identification of Piecewise Linear Uniform Motion Blur

NASA Astrophysics Data System (ADS)

Patanukhom, Karn; Nishihara, Akinori

A motion blur identification scheme is proposed for nonlinear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.

Human motion analysis with detection of subpart deformations

NASA Astrophysics Data System (ADS)

Wang, Juhui; Lorette, Guy; Bouthemy, Patrick

1992-06-01

One essential constraint used in 3-D motion estimation from optical projections is the rigidity assumption. Because of muscle deformations in human motion, this rigidity requirement is often violated for some regions on the human body. Global methods usually fail to bring stable solutions. This paper presents a model-based approach to combating the effect of muscle deformations in human motion analysis. The approach developed is based on two main stages. In the first stage, the human body is partitioned into different areas, where each area is consistent with a general motion model (not necessarily corresponding to a physical existing motion pattern). In the second stage, the regions are eliminated under the hypothesis that they are not induced by a specific human motion pattern. Each hypothesis is generated by making use of specific knowledge about human motion. A global method is used to estimate the 3-D motion parameters in basis of valid segments. Experiments based on a cycling motion sequence are presented.

Fast instantaneous center of rotation estimation algorithm for a skied-steered robot

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2015-05-01

Skid-steered robots are widely used as mobile platforms for machine vision systems. However it is hard to achieve a stable motion of such robots along desired trajectory due to an unpredictable wheel slip. It is possible to compensate the unpredictable wheel slip and stabilize the motion of the robot using visual odometry. This paper presents a fast optical flow based algorithm for estimation of instantaneous center of rotation, angular and longitudinal speed of the robot. The proposed algorithm is based on Horn-Schunck variational optical flow estimation method. The instantaneous center of rotation and motion of the robot is estimated by back projection of optical flow field to the ground surface. The developed algorithm was tested using skid-steered mobile robot. The robot is based on a mobile platform that includes two pairs of differential driven motors and a motor controller. Monocular visual odometry system consisting of a singleboard computer and a low cost webcam is mounted on the mobile platform. A state-space model of the robot was derived using standard black-box system identification. The input (commands) and the output (motion) were recorded using a dedicated external motion capture system. The obtained model was used to control the robot without visual odometry data. The paper is concluded with the algorithm quality estimation by comparison of the trajectories estimated by the algorithm with the data from motion capture system.

Relationships between scalp, brain, and skull motion estimated using magnetic resonance elastography.

PubMed

Badachhape, Andrew A; Okamoto, Ruth J; Johnson, Curtis L; Bayly, Philip V

2018-05-17

The objective of this study was to characterize the relationships between motion in the scalp, skull, and brain. In vivo estimates of motion transmission from the skull to the brain may illuminate the mechanics of traumatic brain injury. Because of challenges in directly sensing skull motion, it is useful to know how well motion of soft tissue of the head, i.e., the scalp, can approximate skull motion or predict brain tissue deformation. In this study, motion of the scalp and brain were measured using magnetic resonance elastography (MRE) and separated into components due to rigid-body displacement and dynamic deformation. Displacement estimates in the scalp were calculated using low motion-encoding gradient strength in order to reduce "phase wrapping" (an ambiguity in displacement estimates caused by the 2 π-periodicity of MRE phase contrast). MRE estimates of scalp and brain motion were compared to skull motion estimated from three tri-axial accelerometers. Comparison of the relative amplitudes and phases of harmonic motion in the scalp, skull, and brain of six human subjects indicate that data from scalp-based sensors should be used with caution to estimate skull kinematics, but that fairly consistent relationships exist between scalp, skull, and brain motion. In addition, the measured amplitude and phase relationships of scalp, skull, and brain can be used to evaluate and improve mathematical models of head biomechanics. Copyright © 2018 Elsevier Ltd. All rights reserved.

MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner.

PubMed

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B; Michel, Christian J; El Fakhri, Georges; Schmand, Matthias; Sorensen, A Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed, and motion estimates were obtained using 2 high-temporal-resolution MRI-based motion-tracking techniques. After accounting for the misalignment between the 2 scanners, perfectly coregistered MRI and PET volumes were reproducibly obtained. The MRI output gates inserted into the PET list-mode allow the temporal correlation of the 2 datasets within 0.2 ms. The Hoffman phantom volume reconstructed by processing the PET data in the LOR space was similar to the one obtained by processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the procedure. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 s and 20 ms, respectively. Motion-deblurred PET images, with excellent delineation of specific brain structures, were obtained using these 2 MRI-based estimates. An MRI-based MC algorithm was implemented for an integrated MR-PET scanner. High-temporal-resolution MRI-derived motion estimates (obtained while simultaneously acquiring anatomic or functional MRI data) can be used for PET MC. An MRI-based MC method has the potential to improve PET image quality, increasing its reliability, reproducibility, and quantitative accuracy, and to benefit many neurologic applications.

Advanced Respiratory Motion Compensation for Coronary MR Angiography

PubMed Central

Henningsson, Markus; Botnar, Rene M.

2013-01-01

Despite technical advances, respiratory motion remains a major impediment in a substantial amount of patients undergoing coronary magnetic resonance angiography (CMRA). Traditionally, respiratory motion compensation has been performed with a one-dimensional respiratory navigator positioned on the right hemi-diaphragm, using a motion model to estimate and correct for the bulk respiratory motion of the heart. Recent technical advancements has allowed for direct respiratory motion estimation of the heart, with improved motion compensation performance. Some of these new methods, particularly using image-based navigators or respiratory binning, allow for more advanced motion correction which enables CMRA data acquisition throughout most or all of the respiratory cycle, thereby significantly reducing scan time. This review describes the three components typically involved in most motion compensation strategies for CMRA, including respiratory motion estimation, gating and correction, and how these processes can be utilized to perform advanced respiratory motion compensation. PMID:23708271

Losses to single-family housing from ground motions in the 1994 Northridge, California, earthquake

USGS Publications Warehouse

Wesson, R.L.; Perkins, D.M.; Leyendecker, E.V.; Roth, R.J.; Petersen, M.D.

2004-01-01

The distributions of insured losses to single-family housing following the 1994 Northridge, California, earthquake for 234 ZIP codes can be satisfactorily modeled with gamma distributions. Regressions of the parameters in the gamma distribution on estimates of ground motion, derived from ShakeMap estimates or from interpolated observations, provide a basis for developing curves of conditional probability of loss given a ground motion. Comparison of the resulting estimates of aggregate loss with the actual aggregate loss gives satisfactory agreement for several different ground-motion parameters. Estimates of loss based on a deterministic spatial model of the earthquake ground motion, using standard attenuation relationships and NEHRP soil factors, give satisfactory results for some ground-motion parameters if the input ground motions are increased about one and one-half standard deviations above the median, reflecting the fact that the ground motions for the Northridge earthquake tended to be higher than the median ground motion for other earthquakes with similar magnitude. The results give promise for making estimates of insured losses to a similar building stock under future earthquake loading. ?? 2004, Earthquake Engineering Research Institute.

Direction-dependent regularization for improved estimation of liver and lung motion in 4D image data

NASA Astrophysics Data System (ADS)

Schmidt-Richberg, Alexander; Ehrhardt, Jan; Werner, René; Handels, Heinz

2010-03-01

The estimation of respiratory motion is a fundamental requisite for many applications in the field of 4D medical imaging, for example for radiotherapy of thoracic and abdominal tumors. It is usually done using non-linear registration of time frames of the sequence without further modelling of physiological motion properties. In this context, the accurate calculation of liver und lung motion is especially challenging because the organs are slipping along the surrounding tissue (i.e. the rib cage) during the respiratory cycle, which leads to discontinuities in the motion field. Without incorporating this specific physiological characteristic, common smoothing mechanisms cause an incorrect estimation along the object borders. In this paper, we present an extended diffusion-based model for incorporating physiological knowledge in image registration. By decoupling normal- and tangential-directed smoothing, we are able to estimate slipping motion at the organ borders while preventing gaps and ensuring smooth motion fields inside. We evaluate our model for the estimation of lung and liver motion on the basis of publicly accessible 4D CT and 4D MRI data. The results show a considerable increase of registration accuracy with respect to the target registration error and a more plausible motion estimation.

FPGA-based architecture for motion recovering in real-time

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Maya-Rueda, Selene E.; Torres-Huitzil, Cesar

2002-03-01

A key problem in the computer vision field is the measurement of object motion in a scene. The main goal is to compute an approximation of the 3D motion from the analysis of an image sequence. Once computed, this information can be used as a basis to reach higher level goals in different applications. Motion estimation algorithms pose a significant computational load for the sequential processors limiting its use in practical applications. In this work we propose a hardware architecture for motion estimation in real time based on FPGA technology. The technique used for motion estimation is Optical Flow due to its accuracy, and the density of velocity estimation, however other techniques are being explored. The architecture is composed of parallel modules working in a pipeline scheme to reach high throughput rates near gigaflops. The modules are organized in a regular structure to provide a high degree of flexibility to cover different applications. Some results will be presented and the real-time performance will be discussed and analyzed. The architecture is prototyped in an FPGA board with a Virtex device interfaced to a digital imager.

3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

PubMed Central

Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Cai, Weixing; Rottmann, Joerg; Li, Ruijiang; Williams, Christopher; Wagar, Matthew; Berbeco, Ross; Ionascu, Dan; Lewis, John H.

2015-01-01

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722

Markerless motion estimation for motion-compensated clinical brain imaging

NASA Astrophysics Data System (ADS)

Kyme, Andre Z.; Se, Stephen; Meikle, Steven R.; Fulton, Roger R.

2018-05-01

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (<2 mm discrepancy against a benchmarking system) on an ethnically diverse range of subjects and, moreover, exhibits lower jitter and estimation of motion over a greater range than some marker-based methods. Our optimization tests indicate that the basic pose estimation algorithm is very robust but generally benefits from rudimentary background masking. Further marginal gains in accuracy can be achieved by accounting for non-rigid motion of features. Efficiency gains can be achieved by capping the number of features used for pose estimation provided that these features adequately sample the range of head motion encountered in the study. These proof-of-principle data suggest that markerless motion tracking is amenable to motion-compensated brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.

Doppler ultrasound-based measurement of tendon velocity and displacement for application toward detecting user-intended motion.

PubMed

Stegman, Kelly J; Park, Edward J; Dechev, Nikolai

2012-07-01

The motivation of this research is to non-invasively monitor the wrist tendon's displacement and velocity, for purposes of controlling a prosthetic device. This feasibility study aims to determine if the proposed technique using Doppler ultrasound is able to accurately estimate the tendon's instantaneous velocity and displacement. This study is conducted with a tendon mimicking experiment consisting of two different materials: a commercial ultrasound scanner, and a reference linear motion stage set-up. Audio-based output signals are acquired from the ultrasound scanner, and are processed with our proposed Fourier technique to obtain the tendon's velocity and displacement estimates. We then compare our estimates to an external reference system, and also to the ultrasound scanner's own estimates based on its proprietary software. The proposed tendon motion estimation method has been shown to be repeatable, effective and accurate in comparison to the external reference system, and is generally more accurate than the scanner's own estimates. After establishing this feasibility study, future testing will include cadaver-based studies to test the technique on the human arm tendon anatomy, and later on live human test subjects in order to further refine the proposed method for the novel purpose of detecting user-intended tendon motion for controlling wearable prosthetic devices.

Interaction force and motion estimators facilitating impedance control of the upper limb rehabilitation robot.

PubMed

Mancisidor, Aitziber; Zubizarreta, Asier; Cabanes, Itziar; Bengoa, Pablo; Jung, Je Hyung

2017-07-01

In order to enhance the performance of rehabilitation robots, it is imperative to know both force and motion caused by the interaction between user and robot. However, common direct measurement of both signals through force and motion sensors not only increases the complexity of the system but also impedes affordability of the system. As an alternative of the direct measurement, in this work, we present new force and motion estimators for the proper control of the upper-limb rehabilitation Universal Haptic Pantograph (UHP) robot. The estimators are based on the kinematic and dynamic model of the UHP and the use of signals measured by means of common low-cost sensors. In order to demonstrate the effectiveness of the estimators, several experimental tests were carried out. The force and impedance control of the UHP was implemented first by directly measuring the interaction force using accurate extra sensors and the robot performance was compared to the case where the proposed estimators replace the direct measured values. The experimental results reveal that the controller based on the estimators has similar performance to that using direct measurement (less than 1 N difference in root mean square error between two cases), indicating that the proposed force and motion estimators can facilitate implementation of interactive controller for the UHP in robotmediated rehabilitation trainings.

Assessing the effects of subject motion on T2 relaxation under spin tagging (TRUST) cerebral oxygenation measurements using volume navigators.

PubMed

Stout, Jeffrey N; Tisdall, M Dylan; McDaniel, Patrick; Gagoski, Borjan; Bolar, Divya S; Grant, Patricia Ellen; Adalsteinsson, Elfar

2017-12-01

Subject motion may cause errors in estimates of blood T 2 when using the T 2 -relaxation under spin tagging (TRUST) technique on noncompliant subjects like neonates. By incorporating 3D volume navigators (vNavs) into the TRUST pulse sequence, independent measurements of motion during scanning permit evaluation of these errors. The effects of integrated vNavs on TRUST-based T 2 estimates were evaluated using simulations and in vivo subject data. Two subjects were scanned with the TRUST+vNav sequence during prescribed movements. Mean motion scores were derived from vNavs and TRUST images, along with a metric of exponential fit quality. Regression analysis was performed between T 2 estimates and mean motion scores. Also, motion scores were determined from independent neonatal scans. vNavs negligibly affected venous blood T 2 estimates and better detected subject motion than fit quality metrics. Regression analysis showed that T 2 is biased upward by 4.1 ms per 1 mm of mean motion score. During neonatal scans, mean motion scores of 0.6 to 2.0 mm were detected. Motion during TRUST causes an overestimate of T 2 , which suggests a cautious approach when comparing TRUST-based cerebral oxygenation measurements of noncompliant subjects. Magn Reson Med 78:2283-2289, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

The algorithm of motion blur image restoration based on PSF half-blind estimation

NASA Astrophysics Data System (ADS)

Chen, Da-Ke; Lin, Zhe

2011-08-01

A novel algorithm of motion blur image restoration based on PSF half-blind estimation with Hough transform was introduced on the basis of full analysis of the principle of TDICCD camera, with the problem that vertical uniform linear motion estimation used by IBD algorithm as the original value of PSF led to image restoration distortion. Firstly, the mathematical model of image degradation was established with the transcendental information of multi-frame images, and then two parameters (movement blur length and angle) that have crucial influence on PSF estimation was set accordingly. Finally, the ultimate restored image can be acquired through multiple iterative of the initial value of PSF estimation in Fourier domain, which the initial value was gained by the above method. Experimental results show that the proposal algorithm can not only effectively solve the image distortion problem caused by relative motion between TDICCD camera and movement objects, but also the details characteristics of original image are clearly restored.

An error-based micro-sensor capture system for real-time motion estimation

NASA Astrophysics Data System (ADS)

Yang, Lin; Ye, Shiwei; Wang, Zhibo; Huang, Zhipei; Wu, Jiankang; Kong, Yongmei; Zhang, Li

2017-10-01

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ± 0.06 m for normal walking and 0.13 ± 0.11 m for jumping motions. Research supported by the National Natural Science Foundation of China (Nos. 61431017, 81272166).

PROMO – Real-time Prospective Motion Correction in MRI using Image-based Tracking

PubMed Central

White, Nathan; Roddey, Cooper; Shankaranarayanan, Ajit; Han, Eric; Rettmann, Dan; Santos, Juan; Kuperman, Josh; Dale, Anders

2010-01-01

Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image-based approach for prospective motion correction is described, which utilizes three orthogonal 2D spiral navigator acquisitions (SP-Navs) along with a flexible image-based tracking method based on the Extended Kalman Filter (EKF) algorithm for online motion measurement. The SP-Nav/EKF framework offers the advantages of image-domain tracking within patient-specific regions-of-interest and reduced sensitivity to off-resonance-induced corruption of rigid-body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady-state error of the SP-Nav/EKF motion estimates of less than 10 % of the motion magnitude, even for large compound motions that included rotations over 15 degrees. A preliminary in vivo application in 3D inversion recovery spoiled gradient echo (IR-SPGR) and 3D fast spin echo (FSE) sequences demonstrates the effectiveness of the SP-Nav/EKF framework for correcting 3D rigid-body head motion artifacts prospectively in high-resolution 3D MRI scans. PMID:20027635

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

NASA Astrophysics Data System (ADS)

Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

2012-03-01

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

A hybrid spatiotemporal and Hough-based motion estimation approach applied to magnetic resonance cardiac images

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Sroubek, F.; Ledesma-Carbayo, M. J.; Santos, A.

2006-08-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation to the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach, more specifically on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The later is a well-known line and shape detection method very robust against incomplete data and noise. The rationale of using the HT in this context is because it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results with synthetic sequences are compared against an implementation of the variational technique for local and global motion estimation, where it is shown that the results obtained here are accurate and robust to noise degradations. Real cardiac magnetic resonance images have been tested and evaluated with the current method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, X; Sisniega, A; Zbijewski, W

Purpose: Visualization and quantification of coronary artery calcification and atherosclerotic plaque benefits from coronary artery motion (CAM) artifact elimination. This work applies a rigid linear motion model to a Volume of Interest (VoI) for estimating motion estimation and compensation of image degradation in Coronary Computed Tomography Angiography (CCTA). Methods: In both simulation and testbench experiments, translational CAM was generated by displacement of the imaging object (i.e. simulated coronary artery and explanted human heart) by ∼8 mm, approximating the motion of a main coronary branch. Rotation was assumed to be negligible. A motion degraded region containing a calcification was selected asmore » the VoI. Local residual motion was assumed to be rigid and linear over the acquisition window, simulating motion observed during diastasis. The (negative) magnitude of the image gradient of the reconstructed VoI was chosen as the motion estimation objective and was minimized with Covariance Matrix Adaptation Evolution Strategy (CMAES). Results: Reconstruction incorporated the estimated CAM yielded signification recovery of fine calcification structures as well as reduced motion artifacts within the selected local region. The compensated reconstruction was further evaluated using two image similarity metrics, the structural similarity index (SSIM) and Root Mean Square Error (RMSE). At the calcification site, the compensated data achieved a 3% increase in SSIM and a 91.2% decrease in RMSE in comparison with the uncompensated reconstruction. Conclusion: Results demonstrate the feasibility of our image-based motion estimation method exploiting a local rigid linear model for CAM compensation. The method shows promising preliminary results for the application of such estimation in CCTA. Further work will involve motion estimation of complex motion corrupted patient data acquired from clinical CT scanner.« less

Human Age Estimation Method Robust to Camera Sensor and/or Face Movement

PubMed Central

Nguyen, Dat Tien; Cho, So Ra; Pham, Tuyen Danh; Park, Kang Ryoung

2015-01-01

Human age can be employed in many useful real-life applications, such as customer service systems, automatic vending machines, entertainment, etc. In order to obtain age information, image-based age estimation systems have been developed using information from the human face. However, limitations exist for current age estimation systems because of the various factors of camera motion and optical blurring, facial expressions, gender, etc. Motion blurring can usually be presented on face images by the movement of the camera sensor and/or the movement of the face during image acquisition. Therefore, the facial feature in captured images can be transformed according to the amount of motion, which causes performance degradation of age estimation systems. In this paper, the problem caused by motion blurring is addressed and its solution is proposed in order to make age estimation systems robust to the effects of motion blurring. Experiment results show that our method is more efficient for enhancing age estimation performance compared with systems that do not employ our method. PMID:26334282

High-resolution estimates of Nubia-Somalia plate motion since 20 Ma from reconstructions of the Southwest Indian Ridge, Red Sea and Gulf of Aden

NASA Astrophysics Data System (ADS)

DeMets, C.; Merkouriev, S.

2016-10-01

Large gaps and inconsistencies remain in published estimates of Nubia-Somalia plate motion based on reconstructions of seafloor spreading data around Africa. Herein, we use newly available reconstructions of the Southwest Indian Ridge at ˜1-Myr intervals since 20 Ma to estimate Nubia-Somalia plate motion farther back in time than previously achieved and with an unprecedented degree of temporal resolution. At the northern end of the East African rift, our new estimates of Nubia-Somalia motion for six times from 0.78 Ma to 5.2 Ma differ by only 2 per cent from the rift-normal component of motion that is extrapolated from a recently estimated GPS angular velocity. The rate of rift-normal extension thus appears to have remained steady since at least 5.2 Ma. Our new rotations indicate that the two plates have moved relative to each other since at least 16 Ma and possibly longer. Motion has either been steady since at least 16 Ma or accelerated modestly between 6 and 5.2 Ma. Our Nubia-Somalia rotations predict 42.5 ± 3.8 km of rift-normal extension since 10.6 Ma across the well-studied, northern segment of the Main Ethiopian Rift, consistent with 40-50 km estimates for extension since 10.6 Myr based on seismological surveys of this narrow part of the plate boundary. Nubia-Somalia rotations are also derived by combining newly estimated Somalia-Arabia rotations that reconstruct the post-20-Ma opening of the Gulf of Aden with Nubia-Arabia rotations estimated via a probabilistic analysis of plausible opening scenarios for the Red Sea. These rotations predict Nubia-Somalia motion since 5.2 Myr that is consistent with that determined from Southwest Indian Ridge data and also predict 40 ± 3 km of rift-normal extension since 10.6 Ma across the Main Ethiopian Rift, consistent with our 42.5 ± 3.8 km Southwest Indian Ridge estimate. Our new rotations exclude at high confidence level previous estimates of 12 ± 13 and 123 ± 14 km for rift-normal extensions across the Main Ethiopian Rift since 10.6 Ma based on reconstructions of Chron 5n.2 along the Southwest Indian Ridge. Sparse coverage of magnetic reversals older than 16 Ma along the western third of the Southwest Indian Ridge precludes reliable determinations of Nubia-Somalia plate motion before 16 Ma, leaving unanswered the key question of when the motion between the two plates began.

MR-assisted PET Motion Correction for eurological Studies in an Integrated MR-PET Scanner

PubMed Central

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B.; Michel, Christian J.; El Fakhri, Georges; Schmand, Matthias; Sorensen, A. Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MR data can be used for motion tracking. In this work, a novel data processing and rigid-body motion correction (MC) algorithm for the MR-compatible BrainPET prototype scanner is described and proof-of-principle phantom and human studies are presented. Methods To account for motion, the PET prompts and randoms coincidences as well as the sensitivity data are processed in the line or response (LOR) space according to the MR-derived motion estimates. After sinogram space rebinning, the corrected data are summed and the motion corrected PET volume is reconstructed from these sinograms and the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed and motion estimates were obtained using two high temporal resolution MR-based motion tracking techniques. Results After accounting for the physical mismatch between the two scanners, perfectly co-registered MR and PET volumes are reproducibly obtained. The MR output gates inserted in to the PET list-mode allow the temporal correlation of the two data sets within 0.2 s. The Hoffman phantom volume reconstructed processing the PET data in the LOR space was similar to the one obtained processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the novel MC algorithm. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 seconds and 20 ms, respectively. Substantially improved PET images with excellent delineation of specific brain structures were obtained after applying the MC using these MR-based estimates. Conclusion A novel MR-based MC algorithm was developed for the integrated MR-PET scanner. High temporal resolution MR-derived motion estimates (obtained while simultaneously acquiring anatomical or functional MR data) can be used for PET MC. An MR-based MC has the potential to improve PET as a quantitative method, increasing its reliability and reproducibility which could benefit a large number of neurological applications. PMID:21189415

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Motion prediction of a non-cooperative space target

NASA Astrophysics Data System (ADS)

Zhou, Bang-Zhao; Cai, Guo-Ping; Liu, Yun-Meng; Liu, Pan

2018-01-01

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler's equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function's gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.

Automatic 3D motion estimation of left ventricle from C-arm rotational angiocardiography using a prior motion model and learning based boundary detector.

PubMed

Chen, Mingqing; Zheng, Yefeng; Wang, Yang; Mueller, Kerstin; Lauritsch, Guenter

2013-01-01

Compared to pre-operative imaging modalities, it is more convenient to estimate the current cardiac physiological status from C-arm angiocardiography since C-arm is a widely used intra-operative imaging modality to guide many cardiac interventions. The 3D shape and motion of the left ventricle (LV) estimated from rotational angiocardiography provide important cardiac function measurements, e.g., ejection fraction and myocardium motion dyssynchrony. However, automatic estimation of the 3D LV motion is difficult since all anatomical structures overlap on the 2D X-ray projections and the nearby confounding strong image boundaries (e.g., pericardium) often cause ambiguities to LV endocardium boundary detection. In this paper, a new framework is proposed to overcome the aforementioned difficulties: (1) A new learning-based boundary detector is developed by training a boosting boundary classifier combined with the principal component analysis of a local image patch; (2) The prior LV motion model is learned from a set of dynamic cardiac computed tomography (CT) sequences to provide a good initial estimate of the 3D LV shape of different cardiac phases; (3) The 3D motion trajectory is learned for each mesh point; (4) All these components are integrated into a multi-surface graph optimization method to extract the globally coherent motion. The method is tested on seven patient scans, showing significant improvement on the ambiguous boundary cases with a detection accuracy of 2.87 +/- 1.00 mm on LV endocardium boundary delineation in the 2D projections.

Incremental inverse kinematics based vision servo for autonomous robotic capture of non-cooperative space debris

NASA Astrophysics Data System (ADS)

Dong, Gangqi; Zhu, Z. H.

2016-04-01

This paper proposed a new incremental inverse kinematics based vision servo approach for robotic manipulators to capture a non-cooperative target autonomously. The target's pose and motion are estimated by a vision system using integrated photogrammetry and EKF algorithm. Based on the estimated pose and motion of the target, the instantaneous desired position of the end-effector is predicted by inverse kinematics and the robotic manipulator is moved incrementally from its current configuration subject to the joint speed limits. This approach effectively eliminates the multiple solutions in the inverse kinematics and increases the robustness of the control algorithm. The proposed approach is validated by a hardware-in-the-loop simulation, where the pose and motion of the non-cooperative target is estimated by a real vision system. The simulation results demonstrate the effectiveness and robustness of the proposed estimation approach for the target and the incremental control strategy for the robotic manipulator.

Ego-motion based on EM for bionic navigation

NASA Astrophysics Data System (ADS)

Yue, Xiaofeng; Wang, L. J.; Liu, J. G.

2015-12-01

Researches have proved that flying insects such as bees can achieve efficient and robust flight control, and biologists have explored some biomimetic principles regarding how they control flight. Based on those basic studies and principles acquired from the flying insects, this paper proposes a different solution of recovering ego-motion for low level navigation. Firstly, a new type of entropy flow is provided to calculate the motion parameters. Secondly, EKF, which has been used for navigation for some years to correct accumulated error, and estimation-Maximization, which is always used to estimate parameters, are put together to determine the ego-motion estimation of aerial vehicles. Numerical simulation on MATLAB has proved that this navigation system provides more accurate position and smaller mean absolute error than pure optical flow navigation. This paper has done pioneering work in bionic mechanism to space navigation.

Motion estimation using point cluster method and Kalman filter.

PubMed

Senesh, M; Wolf, A

2009-05-01

The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal instantaneous frequencies.

Estimation of contour motion and deformation for nonrigid object tracking

NASA Astrophysics Data System (ADS)

Shao, Jie; Porikli, Fatih; Chellappa, Rama

2007-08-01

We present an algorithm for nonrigid contour tracking in heavily cluttered background scenes. Based on the properties of nonrigid contour movements, a sequential framework for estimating contour motion and deformation is proposed. We solve the nonrigid contour tracking problem by decomposing it into three subproblems: motion estimation, deformation estimation, and shape regulation. First, we employ a particle filter to estimate the global motion parameters of the affine transform between successive frames. Then we generate a probabilistic deformation map to deform the contour. To improve robustness, multiple cues are used for deformation probability estimation. Finally, we use a shape prior model to constrain the deformed contour. This enables us to retrieve the occluded parts of the contours and accurately track them while allowing shape changes specific to the given object types. Our experiments show that the proposed algorithm significantly improves the tracker performance.

Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2015-04-01

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of cloud motion vectors from the GEO/LEO IR based precipitation estimates and the CFS Reanalysis (CFSR) precipitation fields. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the CFSR precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. Error function is experimented to best reflect the performance of the satellite IR based estimates and the CFSR in capturing the movements of precipitating cloud systems over different regions and for different seasons. Quantitative experiments are conducted to optimize the LEO IR based precipitation estimation technique and the 2D-VAR based motion vector analysis system. Detailed results will be reported at the EGU.

Adapting Surface Ground Motion Relations to Underground conditions: A case study for the Sudbury Neutrino Observatory in Sudbury, Ontario, Canada

NASA Astrophysics Data System (ADS)

Babaie Mahani, A.; Eaton, D. W.

2013-12-01

Ground Motion Prediction Equations (GMPEs) are widely used in Probabilistic Seismic Hazard Assessment (PSHA) to estimate ground-motion amplitudes at Earth's surface as a function of magnitude and distance. Certain applications, such as hazard assessment for caprock integrity in the case of underground storage of CO2, waste disposal sites, and underground pipelines, require subsurface estimates of ground motion; at present, such estimates depend upon theoretical modeling and simulations. The objective of this study is to derive correction factors for GMPEs to enable estimation of amplitudes in the subsurface. We use a semi-analytic approach along with finite-difference simulations of ground-motion amplitudes for surface and underground motions. Spectral ratios of underground to surface motions are used to calculate the correction factors. Two predictive methods are used. The first is a semi-analytic approach based on a quarter-wavelength method that is widely used for earthquake site-response investigations; the second is a numerical approach based on elastic finite-difference simulations of wave propagation. Both methods are evaluated using recordings of regional earthquakes by broadband seismometers installed at the surface and at depths of 1400 m and 2100 m in the Sudbury Neutrino Observatory, Canada. Overall, both methods provide a reasonable fit to the peaks and troughs observed in the ratios of real data. The finite-difference method, however, has the capability to simulate ground motion ratios more accurately than the semi-analytic approach.

Real-time motion compensated patient positioning and non-rigid deformation estimation using 4-D shape priors.

PubMed

Wasza, Jakob; Bauer, Sebastian; Hornegger, Joachim

2012-01-01

Over the last years, range imaging (RI) techniques have been proposed for patient positioning and respiration analysis in motion compensation. Yet, current RI based approaches for patient positioning employ rigid-body transformations, thus neglecting free-form deformations induced by respiratory motion. Furthermore, RI based respiration analysis relies on non-rigid registration techniques with run-times of several seconds. In this paper we propose a real-time framework based on RI to perform respiratory motion compensated positioning and non-rigid surface deformation estimation in a joint manner. The core of our method are pre-procedurally obtained 4-D shape priors that drive the intra-procedural alignment of the patient to the reference state, simultaneously yielding a rigid-body table transformation and a free-form deformation accounting for respiratory motion. We show that our method outperforms conventional alignment strategies by a factor of 3.0 and 2.3 in the rotation and translation accuracy, respectively. Using a GPU based implementation, we achieve run-times of 40 ms.

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Gu, Xuejun

2013-10-15

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstructionmore » to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.« less

Test suite for image-based motion estimation of the brain and tongue

NASA Astrophysics Data System (ADS)

Ramsey, Jordan; Prince, Jerry L.; Gomez, Arnold D.

2017-03-01

Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an "image synthesis" test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head- brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that inconsistent motion can yield "ghost" shear strains, which are a function of slice acquisition viability as opposed to a true physical deformation.

Test Suite for Image-Based Motion Estimation of the Brain and Tongue

PubMed Central

Ramsey, Jordan; Prince, Jerry L.; Gomez, Arnold D.

2017-01-01

Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an “image synthesis” test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head-brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that inconsistent motion can yield “ghost” shear strains, which are a function of slice acquisition viability as opposed to a true physical deformation. PMID:28781414

Motion prediction in MRI-guided radiotherapy based on interleaved orthogonal cine-MRI

NASA Astrophysics Data System (ADS)

Seregni, M.; Paganelli, C.; Lee, D.; Greer, P. B.; Baroni, G.; Keall, P. J.; Riboldi, M.

2016-01-01

In-room cine-MRI guidance can provide non-invasive target localization during radiotherapy treatment. However, in order to cope with finite imaging frequency and system latencies between target localization and dose delivery, tumour motion prediction is required. This work proposes a framework for motion prediction dedicated to cine-MRI guidance, aiming at quantifying the geometric uncertainties introduced by this process for both tumour tracking and beam gating. The tumour position, identified through scale invariant features detected in cine-MRI slices, is estimated at high-frequency (25 Hz) using three independent predictors, one for each anatomical coordinate. Linear extrapolation, auto-regressive and support vector machine algorithms are compared against systems that use no prediction or surrogate-based motion estimation. Geometric uncertainties are reported as a function of image acquisition period and system latency. Average results show that the tracking error RMS can be decreased down to a [0.2; 1.2] mm range, for acquisition periods between 250 and 750 ms and system latencies between 50 and 300 ms. Except for the linear extrapolator, tracking and gating prediction errors were, on average, lower than those measured for surrogate-based motion estimation. This finding suggests that cine-MRI guidance, combined with appropriate prediction algorithms, could relevantly decrease geometric uncertainties in motion compensated treatments.

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

Development of a Multiple Input Integrated Pole-to-Pole Global CMORPH

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.

2013-12-01

A test system is being developed at NOAA Climate Prediction Center (CPC) to produce a passive microwave (PMW), IR-based, and model integrated high-resolution precipitation estimation on a 0.05olat/lon grid covering the entire globe from pole to pole. Experiments have been conducted for a summer Test Bed period using data for July and August of 2009. The pole-to-pole global CMORPH system is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). First, retrievals of instantaneous precipitation rates from PMW observations aboard nine low earth orbit (LEO) satellites are decoded and pole-to-pole mapped onto a 0.05olat/lon grid over the globe. Also precipitation estimates from LEO AVHRR retrievals are derived using a PDF matching of LEO IR with calibrated microwave combined (MWCOMB) precipitation retrievals. The motion vectors for the precipitating cloud systems are defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed for the CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors utilizing a two-dimensional optimal interpolation (2D-OI) method, in which CFSR-derived motion vectors are used as the first guess and subsequently satellite derived vectors modify the first guess. Weights used to generate the combinations are defined under the OI framework as a function of error statistics for the CFSR and satellite IR based motion vectors. The screened and calibrated PMW and AVHRR derived precipitation estimates are then separately spatially propagated forward and backward in time, using precipitating cloud motion vectors, from their observation time to the next PMW observation. The PMW estimates propagated in both the forward and backward directions are then combined with propagated IR-based precipitation estimates under the Kalman Filter framework, with weights defined based on previously determined error statistics dependent on latitude, season, surface type, and temporal distance from observation time. Performance of the pole-to-pole global CMORPH and its key components, including combined PMW (MWCOMB), IR-based, and model precipitation, as well as model-derived, IR-based, and blended precipitation motion vectors, will be examined against NSSL Q2 radar observed precipitation estimates over CONUS, Finland FMI radar precipitation, and a daily gauge-based analysis including daily Canadian surface reports over global land. Also an initial investigation will be performed over a January - February 2010 winter Test Bed period. Detailed results will be reported at the Fall 2013 AGU Meeting.

Deblurring for spatial and temporal varying motion with optical computing

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Xue, Dongfeng; Hui, Zhao

2016-05-01

A way to estimate and remove spatially and temporally varying motion blur is proposed, which is based on an optical computing system. The translation and rotation motion can be independently estimated from the joint transform correlator (JTC) system without iterative optimization. The inspiration comes from the fact that the JTC system is immune to rotation motion in a Cartesian coordinate system. The work scheme of the JTC system is designed to keep switching between the Cartesian coordinate system and polar coordinate system in different time intervals with the ping-pang handover. In the ping interval, the JTC system works in the Cartesian coordinate system to obtain a translation motion vector with optical computing speed. In the pang interval, the JTC system works in the polar coordinate system. The rotation motion is transformed to the translation motion through coordinate transformation. Then the rotation motion vector can also be obtained from JTC instantaneously. To deal with continuous spatially variant motion blur, submotion vectors based on the projective motion path blur model are proposed. The submotion vectors model is more effective and accurate at modeling spatially variant motion blur than conventional methods. The simulation and real experiment results demonstrate its overall effectiveness.

Global velocity constrained cloud motion prediction for short-term solar forecasting

NASA Astrophysics Data System (ADS)

Chen, Yanjun; Li, Wei; Zhang, Chongyang; Hu, Chuanping

2016-09-01

Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.

Coupling reconstruction and motion estimation for dynamic MRI through optical flow constraint

NASA Astrophysics Data System (ADS)

Zhao, Ningning; O'Connor, Daniel; Gu, Wenbo; Ruan, Dan; Basarab, Adrian; Sheng, Ke

2018-03-01

This paper addresses the problem of dynamic magnetic resonance image (DMRI) reconstruction and motion estimation jointly. Because of the inherent anatomical movements in DMRI acquisition, reconstruction of DMRI using motion estimation/compensation (ME/MC) has been explored under the compressed sensing (CS) scheme. In this paper, by embedding the intensity based optical flow (OF) constraint into the traditional CS scheme, we are able to couple the DMRI reconstruction and motion vector estimation. Moreover, the OF constraint is employed in a specific coarse resolution scale in order to reduce the computational complexity. The resulting optimization problem is then solved using a primal-dual algorithm due to its efficiency when dealing with nondifferentiable problems. Experiments on highly accelerated dynamic cardiac MRI with multiple receiver coils validate the performance of the proposed algorithm.

Design, Implementation and Validation of the Three-Wheel Holonomic Motion System of the Assistant Personal Robot (APR).

PubMed

Moreno, Javier; Clotet, Eduard; Lupiañez, Ruben; Tresanchez, Marcel; Martínez, Dani; Pallejà, Tomàs; Casanovas, Jordi; Palacín, Jordi

2016-10-10

This paper presents the design, implementation and validation of the three-wheel holonomic motion system of a mobile robot designed to operate in homes. The holonomic motion system is described in terms of mechanical design and electronic control. The paper analyzes the kinematics of the motion system and validates the estimation of the trajectory comparing the displacement estimated with the internal odometry of the motors and the displacement estimated with a SLAM procedure based on LIDAR information. Results obtained in different experiments have shown a difference on less than 30 mm between the position estimated with the SLAM and odometry, and a difference in the angular orientation of the mobile robot lower than 5° in absolute displacements up to 1000 mm.

Design, Implementation and Validation of the Three-Wheel Holonomic Motion System of the Assistant Personal Robot (APR)

PubMed Central

Moreno, Javier; Clotet, Eduard; Lupiañez, Ruben; Tresanchez, Marcel; Martínez, Dani; Pallejà, Tomàs; Casanovas, Jordi; Palacín, Jordi

2016-01-01

This paper presents the design, implementation and validation of the three-wheel holonomic motion system of a mobile robot designed to operate in homes. The holonomic motion system is described in terms of mechanical design and electronic control. The paper analyzes the kinematics of the motion system and validates the estimation of the trajectory comparing the displacement estimated with the internal odometry of the motors and the displacement estimated with a SLAM procedure based on LIDAR information. Results obtained in different experiments have shown a difference on less than 30 mm between the position estimated with the SLAM and odometry, and a difference in the angular orientation of the mobile robot lower than 5° in absolute displacements up to 1000 mm. PMID:27735857

Estimating Shape and Micro-Motion Parameter of Rotationally Symmetric Space Objects from the Infrared Signature

PubMed Central

Wu, Yabei; Lu, Huanzhang; Zhao, Fei; Zhang, Zhiyong

2016-01-01

Shape serves as an important additional feature for space target classification, which is complementary to those made available. Since different shapes lead to different projection functions, the projection property can be regarded as one kind of shape feature. In this work, the problem of estimating the projection function from the infrared signature of the object is addressed. We show that the projection function of any rotationally symmetric object can be approximately represented as a linear combination of some base functions. Based on this fact, the signal model of the emissivity-area product sequence is constructed, which is a particular mathematical function of the linear coefficients and micro-motion parameters. Then, the least square estimator is proposed to estimate the projection function and micro-motion parameters jointly. Experiments validate the effectiveness of the proposed method. PMID:27763500

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

PubMed

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments

PubMed Central

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-01-01

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. PMID:25412217

Motion Estimation System Utilizing Point Cloud Registration

NASA Technical Reports Server (NTRS)

Chen, Qi (Inventor)

2016-01-01

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

Object-based attentional modulation of biological motion processing: spatiotemporal dynamics using functional magnetic resonance imaging and electroencephalography.

PubMed

Safford, Ashley S; Hussey, Elizabeth A; Parasuraman, Raja; Thompson, James C

2010-07-07

Although it is well documented that the ability to perceive biological motion is mediated by the lateral temporal cortex, whether and when neural activity in this brain region is modulated by attention is unknown. In particular, it is unclear whether the processing of biological motion requires attention or whether such stimuli are processed preattentively. Here, we used functional magnetic resonance imaging, high-density electroencephalography, and cortically constrained source estimation methods to investigate the spatiotemporal effects of attention on the processing of biological motion. Directing attention to tool motion in overlapping movies of biological motion and tool motion suppressed the blood oxygenation level-dependent (BOLD) response of the right superior temporal sulcus (STS)/middle temporal gyrus (MTG), while directing attention to biological motion suppressed the BOLD response of the left inferior temporal sulcus (ITS)/MTG. Similarly, category-based modulation of the cortical current source density estimates from the right STS/MTG and left ITS was observed beginning at approximately 450 ms following stimulus onset. Our results indicate that the cortical processing of biological motion is strongly modulated by attention. These findings argue against preattentive processing of biological motion in the presence of stimuli that compete for attention. Our findings also suggest that the attention-based segregation of motion category-specific responses only emerges relatively late (several hundred milliseconds) in processing.

A focused ultrasound treatment system for moving targets (part I): generic system design and in-silico first-stage evaluation.

PubMed

Schwenke, Michael; Strehlow, Jan; Demedts, Daniel; Haase, Sabrina; Barrios Romero, Diego; Rothlübbers, Sven; von Dresky, Caroline; Zidowitz, Stephan; Georgii, Joachim; Mihcin, Senay; Bezzi, Mario; Tanner, Christine; Sat, Giora; Levy, Yoav; Jenne, Jürgen; Günther, Matthias; Melzer, Andreas; Preusser, Tobias

2017-01-01

Focused ultrasound (FUS) is entering clinical routine as a treatment option. Currently, no clinically available FUS treatment system features automated respiratory motion compensation. The required quality standards make developing such a system challenging. A novel FUS treatment system with motion compensation is described, developed with the goal of clinical use. The system comprises a clinically available MR device and FUS transducer system. The controller is very generic and could use any suitable MR or FUS device. MR image sequences (echo planar imaging) are acquired for both motion observation and thermometry. Based on anatomical feature tracking, motion predictions are estimated to compensate for processing delays. FUS control parameters are computed repeatedly and sent to the hardware to steer the focus to the (estimated) target position. All involved calculations produce individually known errors, yet their impact on therapy outcome is unclear. This is solved by defining an intuitive quality measure that compares the achieved temperature to the static scenario, resulting in an overall efficiency with respect to temperature rise. To allow for extensive testing of the system over wide ranges of parameters and algorithmic choices, we replace the actual MR and FUS devices by a virtual system. It emulates the hardware and, using numerical simulations of FUS during motion, predicts the local temperature rise in the tissue resulting from the controls it receives. With a clinically available monitoring image rate of 6.67 Hz and 20 FUS control updates per second, normal respiratory motion is estimated to be compensable with an estimated efficiency of 80%. This reduces to about 70% for motion scaled by 1.5. Extensive testing (6347 simulated sonications) over wide ranges of parameters shows that the main source of error is the temporal motion prediction. A history-based motion prediction method performs better than a simple linear extrapolator. The estimated efficiency of the new treatment system is already suited for clinical applications. The simulation-based in-silico testing as a first-stage validation reduces the efforts of real-world testing. Due to the extensible modular design, the described approach might lead to faster translations from research to clinical practice.

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr

2015-05-15

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogrammore » with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of two conjugate PAR images. To evaluate the proposed algorithm, digital XCAT and physical dynamic cardiac phantom datasets are used. The XCAT phantom datasets were generated with heart rates of 70 and 100 bpm, respectively, by assuming a system rotation time of 300 ms. A physical dynamic cardiac phantom was scanned using a slowly rotating XCT system so that the effective heart rate will be 70 bpm for a system rotation speed of 300 ms. Results: In the XCAT phantom experiment, motion-compensated 3D images obtained from the proposed algorithm show coronary arteries with fewer motion artifacts for all phases. Moreover, object boundaries contaminated by motion are well restored. Even though object positions and boundary shapes are still somewhat different from the ground truth in some cases, the authors see that visibilities of coronary arteries are improved noticeably and motion artifacts are reduced considerably. The physical phantom study also shows that the visual quality of motion-compensated images is greatly improved. Conclusions: The authors propose a novel PAR image-based cardiac motion estimation and compensation algorithm. The algorithm requires an angular scan range of less than 360°. The excellent performance of the proposed algorithm is illustrated by using digital XCAT and physical dynamic cardiac phantom datasets.« less

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications

PubMed Central

Gleeson, Fergus V.; Brady, Michael; Schnabel, Julia A.

2018-01-01

Abstract. Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset. PMID:29662918

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications.

PubMed

Papież, Bartłomiej W; Franklin, James M; Heinrich, Mattias P; Gleeson, Fergus V; Brady, Michael; Schnabel, Julia A

2018-04-01

Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset.

Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Bayerl, P.; Neumann, H.

2007-12-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation of the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach. More specifically it relies on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The latter is a well-known line and shape detection method that is highly robust against incomplete data and noise. The rationale of using the HT in this context is that it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results in the case of synthetic sequences are compared with an implementation of the variational technique for local and global motion estimation, where it is shown that the results are accurate and robust to noise degradations. Results obtained with real cardiac magnetic resonance images are presented.

Lagrangian speckle model and tissue-motion estimation--theory.

PubMed

Maurice, R L; Bertrand, M

1999-07-01

It is known that when a tissue is subjected to movements such as rotation, shearing, scaling, etc., changes in speckle patterns that result act as a noise source, often responsible for most of the displacement-estimate variance. From a modeling point of view, these changes can be thought of as resulting from two mechanisms: one is the motion of the speckles and the other, the alterations of their morphology. In this paper, we propose a new tissue-motion estimator to counteract these speckle decorrelation effects. The estimator is based on a Lagrangian description of the speckle motion. This description allows us to follow local characteristics of the speckle field as if they were a material property. This method leads to an analytical description of the decorrelation in a way which enables the derivation of an appropriate inverse filter for speckle restoration. The filter is appropriate for linear geometrical transformation of the scattering function (LT), i.e., a constant-strain region of interest (ROI). As the LT itself is a parameter of the filter, a tissue-motion estimator can be formulated as a nonlinear minimization problem, seeking the best match between the pre-tissue-motion image and a restored-speckle post-motion image. The method is tested, using simulated radio-frequency (RF) images of tissue undergoing axial shear.

A Compact VLSI System for Bio-Inspired Visual Motion Estimation.

PubMed

Shi, Cong; Luo, Gang

2018-04-01

This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.

Research on Radar Micro-Doppler Feature Parameter Estimation of Propeller Aircraft

NASA Astrophysics Data System (ADS)

He, Zhihua; Tao, Feixiang; Duan, Jia; Luo, Jingsheng

2018-01-01

The micro-motion modulation effect of the rotated propellers to radar echo can be a steady feature for aircraft target recognition. Thus, micro-Doppler feature parameter estimation is a key to accurate target recognition. In this paper, the radar echo of rotated propellers is modelled and simulated. Based on which, the distribution characteristics of the micro-motion modulation energy in time, frequency and time-frequency domain are analyzed. The micro-motion modulation energy produced by the scattering points of rotating propellers is accumulated using the Inverse-Radon (I-Radon) transform, which can be used to accomplish the estimation of micro-modulation parameter. Finally, it is proved that the proposed parameter estimation method is effective with measured data. The micro-motion parameters of aircraft can be used as the features of radar target recognition.

Motion direction estimation based on active RFID with changing environment

NASA Astrophysics Data System (ADS)

Jie, Wu; Minghua, Zhu; Wei, He

2018-05-01

The gate system is used to estimate the direction of RFID tags carriers when they are going through the gate. Normally, it is difficult to achieve and keep a high accuracy in estimating motion direction of RFID tags because the received signal strength of tag changes sharply according to the changing electromagnetic environment. In this paper, a method of motion direction estimation for RFID tags is presented. To improve estimation accuracy, the machine leaning algorithm is used to get the fitting function of the received data by readers which are deployed inside and outside gate respectively. Then the fitted data are sampled to get the standard vector. We compare the stand vector with template vectors to get the motion direction estimation result. Then the corresponding template vector is updated according to the surrounding environment. We conducted the simulation and implement of the proposed method and the result shows that the proposed method in this work can improve and keep a high accuracy under the condition of the constantly changing environment.

Estimate of procession and polar motion errors from planetary encounter station location solutions

NASA Technical Reports Server (NTRS)

Pease, G. E.

1978-01-01

Jet Propulsion Laboratory Deep Space Station (DSS) location solutions based on two JPL planetary ephemerides, DE 84 and DE 96, at eight planetary encounters were used to obtain weighted least squares estimates of precession and polar motion errors. The solution for precession error in right ascension yields a value of 0.3 X 10 to the minus 5 power plus or minus 0.8 X 10 to the minus 6 power deg/year. This maps to a right ascension error of 1.3 X 10 to the minus 5 power plus or minus 0.4 X 10 to the minus 5 power deg at the first Voyager 1979 Jupiter encounter if the current JPL DSS location set is used. Solutions for precession and polar motion using station locations based on DE 84 agree well with the solution using station locations referenced to DE 96. The precession solution removes the apparent drift in station longitude and spin axis distance estimates, while the encounter polar motion solutions consistently decrease the scatter in station spin axis distance estimates.

Robust Parallel Motion Estimation and Mapping with Stereo Cameras in Underground Infrastructure

NASA Astrophysics Data System (ADS)

Liu, Chun; Li, Zhengning; Zhou, Yuan

2016-06-01

Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it's also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.

Intensity-Based Registration for Lung Motion Estimation

NASA Astrophysics Data System (ADS)

Cao, Kunlin; Ding, Kai; Amelon, Ryan E.; Du, Kaifang; Reinhardt, Joseph M.; Raghavan, Madhavan L.; Christensen, Gary E.

Image registration plays an important role within pulmonary image analysis. The task of registration is to find the spatial mapping that brings two images into alignment. Registration algorithms designed for matching 4D lung scans or two 3D scans acquired at different inflation levels can catch the temporal changes in position and shape of the region of interest. Accurate registration is critical to post-analysis of lung mechanics and motion estimation. In this chapter, we discuss lung-specific adaptations of intensity-based registration methods for 3D/4D lung images and review approaches for assessing registration accuracy. Then we introduce methods for estimating tissue motion and studying lung mechanics. Finally, we discuss methods for assessing and quantifying specific volume change, specific ventilation, strain/ stretch information and lobar sliding.

Cluster membership probability: polarimetric approach

NASA Astrophysics Data System (ADS)

Medhi, Biman J.; Tamura, Motohide

2013-04-01

Interstellar polarimetric data of the six open clusters Hogg 15, NGC 6611, NGC 5606, NGC 6231, NGC 5749 and NGC 6250 have been used to estimate the membership probability for the stars within them. For proper-motion member stars, the membership probability estimated using the polarimetric data is in good agreement with the proper-motion cluster membership probability. However, for proper-motion non-member stars, the membership probability estimated by the polarimetric method is in total disagreement with the proper-motion cluster membership probability. The inconsistencies in the determined memberships may be because of the fundamental differences between the two methods of determination: one is based on stellar proper motion in space and the other is based on selective extinction of the stellar output by the asymmetric aligned dust grains present in the interstellar medium. The results and analysis suggest that the scatter of the Stokes vectors q (per cent) and u (per cent) for the proper-motion member stars depends on the interstellar and intracluster differential reddening in the open cluster. It is found that this method could be used to estimate the cluster membership probability if we have additional polarimetric and photometric information for a star to identify it as a probable member/non-member of a particular cluster, such as the maximum wavelength value (λmax), the unit weight error of the fit (σ1), the dispersion in the polarimetric position angles (overline{ɛ }), reddening (E(B - V)) or the differential intracluster reddening (ΔE(B - V)). This method could also be used to estimate the membership probability of known member stars having no membership probability as well as to resolve disagreements about membership among different proper-motion surveys.

Refraction-compensated motion tracking of unrestrained small animals in positron emission tomography.

PubMed

Kyme, Andre; Meikle, Steven; Baldock, Clive; Fulton, Roger

2012-08-01

Motion-compensated radiotracer imaging of fully conscious rodents represents an important paradigm shift for preclinical investigations. In such studies, if motion tracking is performed through a transparent enclosure containing the awake animal, light refraction at the interface will introduce errors in stereo pose estimation. We have performed a thorough investigation of how this impacts the accuracy of pose estimates and the resulting motion correction, and developed an efficient method to predict and correct for refraction-based error. The refraction model underlying this study was validated using a state-of-the-art motion tracking system. Refraction-based error was shown to be dependent on tracking marker size, working distance, and interface thickness and tilt. Correcting for refraction error improved the spatial resolution and quantitative accuracy of motion-corrected positron emission tomography images. Since the methods are general, they may also be useful in other contexts where data are corrupted by refraction effects. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Source parameters of the 2013 Lushan, Sichuan, Ms7.0 earthquake and estimation of the near-fault strong ground motion

NASA Astrophysics Data System (ADS)

Meng, L.; Zhou, L.; Liu, J.

2013-12-01

Abstract: The April 20, 2013 Ms 7.0 earthquake in Lushan city, Sichuan province of China occurred as the result of east-west oriented reverse-type motion on a north-south striking fault. The source location suggests the event occurred on the Southern part of Longmenshan fault at a depth of 13km. The Lushan earthquake caused a great of loss of property and 196 deaths. The maximum intensity is up to VIII to IX at Boxing and Lushan city, which are located in the meizoseismal area. In this study, we analyzed the dynamic source process and calculated source spectral parameters, estimated the strong ground motion in the near-fault field based on the Brune's circle model at first. A dynamical composite source model (DCSM) has been developed further to simulate the near-fault strong ground motion with associated fault rupture properties at Boxing and Lushan city, respectively. The results indicate that the frictional undershoot behavior in the dynamic source process of Lushan earthquake, which is actually different from the overshoot activity of the Wenchuan earthquake. Based on the simulated results of the near-fault strong ground motion, described the intensity distribution of the Lushan earthquake field. The simulated intensity indicated that, the maximum intensity value is IX, and region with and above VII almost 16,000km2, which is consistence with observation intensity published online by China Earthquake Administration (CEA) on April 25. Moreover, the numerical modeling developed in this study has great application in the strong ground motion prediction and intensity estimation for the earthquake rescue purpose. In fact, the estimation methods based on the empirical relationship and numerical modeling developed in this study has great application in the strong ground motion prediction for the earthquake source process understand purpose. Keywords: Lushan, Ms7.0 earthquake; near-fault strong ground motion; DCSM; simulated intensity

Richardson-Lucy deblurring for the star scene under a thinning motion path

NASA Astrophysics Data System (ADS)

Su, Laili; Shao, Xiaopeng; Wang, Lin; Wang, Haixin; Huang, Yining

2015-05-01

This paper puts emphasis on how to model and correct image blur that arises from a camera's ego motion while observing a distant star scene. Concerning the significance of accurate estimation of point spread function (PSF), a new method is employed to obtain blur kernel by thinning star motion path. In particular, how the blurred star image can be corrected to reconstruct the clear scene with a thinning motion blur model which describes the camera's path is presented. This thinning motion path to build blur kernel model is more effective at modeling the spatially motion blur introduced by camera's ego motion than conventional blind estimation of kernel-based PSF parameterization. To gain the reconstructed image, firstly, an improved thinning algorithm is used to obtain the star point trajectory, so as to extract the blur kernel of the motion-blurred star image. Then how motion blur model can be incorporated into the Richardson-Lucy (RL) deblurring algorithm, which reveals its overall effectiveness, is detailed. In addition, compared with the conventional estimated blur kernel, experimental results show that the proposed method of using thinning algorithm to get the motion blur kernel is of less complexity, higher efficiency and better accuracy, which contributes to better restoration of the motion-blurred star images.

Precise Image-Based Motion Estimation for Autonomous Small Body Exploration

NASA Technical Reports Server (NTRS)

Johnson, Andrew Edie; Matthies, Larry H.

2000-01-01

We have developed and tested a software algorithm that enables onboard autonomous motion estimation near small bodies using descent camera imagery and laser altimetry. Through simulation and testing, we have shown that visual feature tracking can decrease uncertainty in spacecraft motion to a level that makes landing on small, irregularly shaped, bodies feasible. Possible future work will include qualification of the algorithm as a flight experiment for the Deep Space 4/Champollion comet lander mission currently under study at the Jet Propulsion Laboratory.

2-D Myocardial Deformation Imaging Based on RF-Based Nonrigid Image Registration.

PubMed

Chakraborty, Bidisha; Liu, Zhi; Heyde, Brecht; Luo, Jianwen; D'hooge, Jan

2018-06-01

Myocardial deformation imaging is a well-established echocardiographic technique for the assessment of myocardial function. Although some solutions make use of speckle tracking of the reconstructed B-mode images, others apply block matching (BM) on the underlying radio frequency (RF) data in order to increase sensitivity to small interframe motion and deformation. However, for both approaches, lateral motion estimation remains a challenge due to the relatively poor lateral resolution of the ultrasound image in combination with the lack of phase information in this direction. Hereto, nonrigid image registration (NRIR) of B-mode images has previously been proposed as an attractive solution. However, hereby, the advantages of RF-based tracking were lost. The aim of this paper was, therefore, to develop an NRIR motion estimator adapted to RF data sets. The accuracy of this estimator was quantified using synthetic data and was contrasted against a state-of-the-art BM solution. The results show that RF-based NRIR outperforms BM in terms of tracking accuracy, particularly, as hypothesized, in the lateral direction. Finally, this RF-based NRIR algorithm was applied clinically, illustrating its ability to estimate both in-plane velocity components in vivo.

Unsupervised motion-based object segmentation refined by color

NASA Astrophysics Data System (ADS)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the chance of the wrong position producing a good match. Consequently, a number of methods exist which combine motion and colour segmentation. These methods use colour segmentation as a base for the motion segmentation and estimation or perform an independent colour segmentation in parallel which is in some way combined with the motion segmentation. The presented method uses both techniques to complement each other by first segmenting on motion cues and then refining the segmentation with colour. To our knowledge few methods exist which adopt this approach. One example is te{meshrefine}. This method uses an irregular mesh, which hinders its efficient implementation in consumer electronics devices. Furthermore, the method produces a foreground/background segmentation, while our applications call for the segmentation of multiple objects. NEW METHOD As mentioned above we start with motion segmentation and refine the edges of this segmentation with a pixel resolution colour segmentation method afterwards. There are several reasons for this approach: + Motion segmentation does not produce the oversegmentation which colour segmentation methods normally produce, because objects are more likely to have colour discontinuities than motion discontinuities. In this way, the colour segmentation only has to be done at the edges of segments, confining the colour segmentation to a smaller part of the image. In such a part, it is more likely that the colour of an object is homogeneous. + This approach restricts the computationally expensive pixel resolution colour segmentation to a subset of the image. Together with the very efficient 3DRS motion estimation algorithm, this helps to reduce the computational complexity. + The motion cue alone is often enough to reliably distinguish objects from one another and the background. To obtain the motion vector fields, a variant of the 3DRS block-based motion estimator which analyses three frames of input was used. The 3DRS motion estimator is known for its ability to estimate motion vectors which closely resemble the true motion. BLOCK-BASED MOTION SEGMENTATION As mentioned above we start with a block-resolution segmentation based on motion vectors. The presented method is inspired by the well-known K-means segmentation method te{K-means}. Several other methods (e.g. te{kmeansc}) adapt K-means for connectedness by adding a weighted shape-error. This adds the additional difficulty of finding the correct weights for the shape-parameters. Also, these methods often bias one particular pre-defined shape. The presented method, which we call K-regions, encourages connectedness because only blocks at the edges of segments may be assigned to another segment. This constrains the segmentation method to such a degree that it allows the method to use least squares for the robust fitting of affine motion models for each segment. Contrary to te{parmkm}, the segmentation step still operates on vectors instead of model parameters. To make sure the segmentation is temporally consistent, the segmentation of the previous frame will be used as initialisation for every new frame. We also present a scheme which makes the algorithm independent of the initially chosen amount of segments. COLOUR-BASED INTRA-BLOCK SEGMENTATION The block resolution motion-based segmentation forms the starting point for the pixel resolution segmentation. The pixel resolution segmentation is obtained from the block resolution segmentation by reclassifying pixels only at the edges of clusters. We assume that an edge between two objects can be found in either one of two neighbouring blocks that belong to different clusters. This assumption allows us to do the pixel resolution segmentation on each pair of such neighbouring blocks separately. Because of the local nature of the segmentation, it largely avoids problems with heterogeneously coloured areas. Because no new segments are introduced in this step, it also does not suffer from oversegmentation problems. The presented method has no problems with bifurcations. For the pixel resolution segmentation itself we reclassify pixels such that we optimize an error norm which favour similarly coloured regions and straight edges. SEGMENTATION MEASURE To assist in the evaluation of the proposed algorithm we developed a quality metric. Because the problem does not have an exact specification, we decided to define a ground truth output which we find desirable for a given input. We define the measure for the segmentation quality as being how different the segmentation is from the ground truth. Our measure enables us to evaluate oversegmentation and undersegmentation seperately. Also, it allows us to evaluate which parts of a frame suffer from oversegmentation or undersegmentation. The proposed algorithm has been tested on several typical sequences. CONCLUSIONS In this abstract we presented a new video segmentation method which performs well in the segmentation of multiple independently moving foreground objects from each other and the background. It combines the strong points of both colour and motion segmentation in the way we expected. One of the weak points is that the segmentation method suffers from undersegmentation when adjacent objects display similar motion. In sequences with detailed backgrounds the segmentation will sometimes display noisy edges. Apart from these results, we think that some of the techniques, and in particular the K-regions technique, may be useful for other two-dimensional data segmentation problems.

Magnitude Estimation for the 2011 Tohoku-Oki Earthquake Based on Ground Motion Prediction Equations

NASA Astrophysics Data System (ADS)

Eshaghi, Attieh; Tiampo, Kristy F.; Ghofrani, Hadi; Atkinson, Gail M.

2015-08-01

This study investigates whether real-time strong ground motion data from seismic stations could have been used to provide an accurate estimate of the magnitude of the 2011 Tohoku-Oki earthquake in Japan. Ultimately, such an estimate could be used as input data for a tsunami forecast and would lead to more robust earthquake and tsunami early warning. We collected the strong motion accelerograms recorded by borehole and free-field (surface) Kiban Kyoshin network stations that registered this mega-thrust earthquake in order to perform an off-line test to estimate the magnitude based on ground motion prediction equations (GMPEs). GMPEs for peak ground acceleration and peak ground velocity (PGV) from a previous study by Eshaghi et al. in the Bulletin of the Seismological Society of America 103. (2013) derived using events with moment magnitude ( M) ≥ 5.0, 1998-2010, were used to estimate the magnitude of this event. We developed new GMPEs using a more complete database (1998-2011), which added only 1 year but approximately twice as much data to the initial catalog (including important large events), to improve the determination of attenuation parameters and magnitude scaling. These new GMPEs were used to estimate the magnitude of the Tohoku-Oki event. The estimates obtained were compared with real time magnitude estimates provided by the existing earthquake early warning system in Japan. Unlike the current operational magnitude estimation methods, our method did not saturate and can provide robust estimates of moment magnitude within ~100 s after earthquake onset for both catalogs. It was found that correcting for average shear-wave velocity in the uppermost 30 m () improved the accuracy of magnitude estimates from surface recordings, particularly for magnitude estimates of PGV (Mpgv). The new GMPEs also were used to estimate the magnitude of all earthquakes in the new catalog with at least 20 records. Results show that the magnitude estimate from PGV values using borehole recordings had the smallest standard deviation among the estimated magnitudes and produced more stable and robust magnitude estimates. This suggests that incorporating borehole strong ground-motion records immediately available after the occurrence of large earthquakes can provide robust and accurate magnitude estimation.

A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs.

PubMed

Han, Lianghao; Dong, Hua; McClelland, Jamie R; Han, Liangxiu; Hawkes, David J; Barratt, Dean C

2017-07-01

This paper presents a new hybrid biomechanical model-based non-rigid image registration method for lung motion estimation. In the proposed method, a patient-specific biomechanical modelling process captures major physically realistic deformations with explicit physical modelling of sliding motion, whilst a subsequent non-rigid image registration process compensates for small residuals. The proposed algorithm was evaluated with 10 4D CT datasets of lung cancer patients. The target registration error (TRE), defined as the Euclidean distance of landmark pairs, was significantly lower with the proposed method (TRE = 1.37 mm) than with biomechanical modelling (TRE = 3.81 mm) and intensity-based image registration without specific considerations for sliding motion (TRE = 4.57 mm). The proposed method achieved a comparable accuracy as several recently developed intensity-based registration algorithms with sliding handling on the same datasets. A detailed comparison on the distributions of TREs with three non-rigid intensity-based algorithms showed that the proposed method performed especially well on estimating the displacement field of lung surface regions (mean TRE = 1.33 mm, maximum TRE = 5.3 mm). The effects of biomechanical model parameters (such as Poisson's ratio, friction and tissue heterogeneity) on displacement estimation were investigated. The potential of the algorithm in optimising biomechanical models of lungs through analysing the pattern of displacement compensation from the image registration process has also been demonstrated. Copyright © 2017 Elsevier B.V. All rights reserved.

Dual respiratory and cardiac motion estimation in PET imaging: Methods design and quantitative evaluation.

PubMed

Feng, Tao; Wang, Jizhe; Tsui, Benjamin M W

2018-04-01

The goal of this study was to develop and evaluate four post-reconstruction respiratory and cardiac (R&C) motion vector field (MVF) estimation methods for cardiac 4D PET data. In Method 1, the dual R&C motions were estimated directly from the dual R&C gated images. In Method 2, respiratory motion (RM) and cardiac motion (CM) were separately estimated from the respiratory gated only and cardiac gated only images. The effects of RM on CM estimation were modeled in Method 3 by applying an image-based RM correction on the cardiac gated images before CM estimation, the effects of CM on RM estimation were neglected. Method 4 iteratively models the mutual effects of RM and CM during dual R&C motion estimations. Realistic simulation data were generated for quantitative evaluation of four methods. Almost noise-free PET projection data were generated from the 4D XCAT phantom with realistic R&C MVF using Monte Carlo simulation. Poisson noise was added to the scaled projection data to generate additional datasets of two more different noise levels. All the projection data were reconstructed using a 4D image reconstruction method to obtain dual R&C gated images. The four dual R&C MVF estimation methods were applied to the dual R&C gated images and the accuracy of motion estimation was quantitatively evaluated using the root mean square error (RMSE) of the estimated MVFs. Results show that among the four estimation methods, Methods 2 performed the worst for noise-free case while Method 1 performed the worst for noisy cases in terms of quantitative accuracy of the estimated MVF. Methods 4 and 3 showed comparable results and achieved RMSE lower by up to 35% than that in Method 1 for noisy cases. In conclusion, we have developed and evaluated 4 different post-reconstruction R&C MVF estimation methods for use in 4D PET imaging. Comparison of the performance of four methods on simulated data indicates separate R&C estimation with modeling of RM before CM estimation (Method 3) to be the best option for accurate estimation of dual R&C motion in clinical situation. © 2018 American Association of Physicists in Medicine.

Accurate estimation of human body orientation from RGB-D sensors.

PubMed

Liu, Wu; Zhang, Yongdong; Tang, Sheng; Tang, Jinhui; Hong, Richang; Li, Jintao

2013-10-01

Accurate estimation of human body orientation can significantly enhance the analysis of human behavior, which is a fundamental task in the field of computer vision. However, existing orientation estimation methods cannot handle the various body poses and appearances. In this paper, we propose an innovative RGB-D-based orientation estimation method to address these challenges. By utilizing the RGB-D information, which can be real time acquired by RGB-D sensors, our method is robust to cluttered environment, illumination change and partial occlusions. Specifically, efficient static and motion cue extraction methods are proposed based on the RGB-D superpixels to reduce the noise of depth data. Since it is hard to discriminate all the 360 (°) orientation using static cues or motion cues independently, we propose to utilize a dynamic Bayesian network system (DBNS) to effectively employ the complementary nature of both static and motion cues. In order to verify our proposed method, we build a RGB-D-based human body orientation dataset that covers a wide diversity of poses and appearances. Our intensive experimental evaluations on this dataset demonstrate the effectiveness and efficiency of the proposed method.

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

PubMed Central

Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

2016-01-01

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: 1) the reconstruction algorithms do not make full use of projection statistics; and 2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10 to 40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET. PMID:27385378

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

NASA Astrophysics Data System (ADS)

Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

2016-08-01

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

Improved optical flow motion estimation for digital image stabilization

NASA Astrophysics Data System (ADS)

Lai, Lijun; Xu, Zhiyong; Zhang, Xuyao

2015-11-01

Optical flow is the instantaneous motion vector at each pixel in the image frame at a time instant. The gradient-based approach for optical flow computation can't work well when the video motion is too large. To alleviate such problem, we incorporate this algorithm into a pyramid multi-resolution coarse-to-fine search strategy. Using pyramid strategy to obtain multi-resolution images; Using iterative relationship from the highest level to the lowest level to obtain inter-frames' affine parameters; Subsequence frames compensate back to the first frame to obtain stabilized sequence. The experiment results demonstrate that the promoted method has good performance in global motion estimation.

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Toward an affordable and user-friendly visual motion capture system.

PubMed

Bonnet, V; Sylla, N; Cherubini, A; Gonzáles, A; Azevedo Coste, C; Fraisse, P; Venture, G

2014-01-01

The present study aims at designing and evaluating a low-cost, simple and portable system for arm joint angle estimation during grasping-like motions. The system is based on a single RGB-D camera and three customized markers. The automatically detected and tracked marker positions were used as inputs to an offline inverse kinematic process based on bio-mechanical constraints to reduce noise effect and handle marker occlusion. The method was validated on 4 subjects with different motions. The joint angles were estimated both with the proposed low-cost system and, a stereophotogrammetric system. Comparative analysis shows good accuracy with high correlation coefficient (r= 0.92) and low average RMS error (3.8 deg).

Motion correction for improved estimation of heart rate using a visual spectrum camera

NASA Astrophysics Data System (ADS)

Tarbox, Elizabeth A.; Rios, Christian; Kaur, Balvinder; Meyer, Shaun; Hirt, Lauren; Tran, Vy; Scott, Kaitlyn; Ikonomidou, Vasiliki

2017-05-01

Heart rate measurement using a visual spectrum recording of the face has drawn interest over the last few years as a technology that can have various health and security applications. In our previous work, we have shown that it is possible to estimate the heart beat timing accurately enough to perform heart rate variability analysis for contactless stress detection. However, a major confounding factor in this approach is the presence of movement, which can interfere with the measurements. To mitigate the effects of movement, in this work we propose the use of face detection and tracking based on the Karhunen-Loewe algorithm in order to counteract measurement errors introduced by normal subject motion, as expected during a common seated conversation setting. We analyze the requirements on image acquisition for the algorithm to work, and its performance under different ranges of motion, changes of distance to the camera, as well and the effect of illumination changes due to different positioning with respect to light sources on the acquired signal. Our results suggest that the effect of face tracking on visual-spectrum based cardiac signal estimation depends on the amplitude of the motion. While for larger-scale conversation-induced motion it can significantly improve estimation accuracy, with smaller-scale movements, such as the ones caused by breathing or talking without major movement errors in facial tracking may interfere with signal estimation. Overall, employing facial tracking is a crucial step in adapting this technology to real-life situations with satisfactory results.

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

NASA Technical Reports Server (NTRS)

Smith, Phillip N.; Sridhar, Banavar; Suorsa, Raymond E.

1993-01-01

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Wind estimates from cloud motions: Phase 1 of an in situ aircraft verification experiment

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Shenk, W. E.; Skillman, W.

1974-01-01

An initial experiment was conducted to verify geostationary satellite derived cloud motion wind estimates with in situ aircraft wind velocity measurements. Case histories of one-half hour to two hours were obtained for 3-10km diameter cumulus cloud systems on 6 days. Also, one cirrus cloud case was obtained. In most cases the clouds were discrete enough that both the cloud motion and the ambient wind could be measured with the same aircraft Inertial Navigation System (INS). Since the INS drift error is the same for both the cloud motion and wind measurements, the drift error subtracts out of the relative motion determinations. The magnitude of the vector difference between the cloud motion and the ambient wind at the cloud base averaged 1.2 m/sec. The wind vector at higher levels in the cloud layer differed by about 3 m/sec to 5 m/sec from the cloud motion vector.

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

A novel procedure for detecting and focusing moving objects with SAR based on the Wigner-Ville distribution

NASA Astrophysics Data System (ADS)

Barbarossa, S.; Farina, A.

A novel scheme for detecting moving targets with synthetic aperture radar (SAR) is presented. The proposed approach is based on the use of the Wigner-Ville distribution (WVD) for simultaneously detecting moving targets and estimating their motion kinematic parameters. The estimation plays a key role for focusing the target and correctly locating it with respect to the stationary background. The method has a number of advantages: (i) the detection is efficiently performed on the samples in the time-frequency domain, provided the WVD, without resorting to the use of a bank of filters, each one matched to possible values of the unknown target motion parameters; (ii) the estimation of the target motion parameters can be done on the same time-frequency domain by locating the line where the maximum energy of the WVD is concentrated. A validation of the approach is given by both analytical and simulation means. In addition, the estimation of the target kinematic parameters and the corresponding image focusing are also demonstrated.

A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts.

PubMed

Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

2017-02-16

The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Flow Mapping Based on the Motion-Integration Errors of Autonomous Underwater Vehicles

NASA Astrophysics Data System (ADS)

Chang, D.; Edwards, C. R.; Zhang, F.

2016-02-01

Knowledge of a flow field is crucial in the navigation of autonomous underwater vehicles (AUVs) since the motion of AUVs is affected by ambient flow. Due to the imperfect knowledge of the flow field, it is typical to observe a difference between the actual and predicted trajectories of an AUV, which is referred to as a motion-integration error (also known as a dead-reckoning error if an AUV navigates via dead-reckoning). The motion-integration error has been essential for an underwater glider to compute its flow estimate from the travel information of the last leg and to improve navigation performance by using the estimate for the next leg. However, the estimate by nature exhibits a phase difference compared to ambient flow experienced by gliders, prohibiting its application in a flow field with strong temporal and spatial gradients. In our study, to mitigate the phase problem, we have developed a local ocean model by combining the flow estimate based on the motion-integration error with flow predictions from a tidal ocean model. Our model has been used to create desired trajectories of gliders for guidance. Our method is validated by Long Bay experiments in 2012 and 2013 in which we deployed multiple gliders on the shelf of South Atlantic Bight and near the edge of Gulf Stream. In our recent study, the application of the motion-integration error is further extended to create a spatial flow map. Considering that the motion-integration errors of AUVs accumulate along their trajectories, the motion-integration error is formulated as a line integral of ambient flow which is then reformulated into algebraic equations. By solving an inverse problem for these algebraic equations, we obtain the knowledge of such flow in near real time, allowing more effective and precise guidance of AUVs in a dynamic environment. This method is referred to as motion tomography. We provide the results of non-parametric and parametric flow mapping from both simulated and experimental data.

3D motion and strain estimation of the heart: initial clinical findings

NASA Astrophysics Data System (ADS)

Barbosa, Daniel; Hristova, Krassimira; Loeckx, Dirk; Rademakers, Frank; Claus, Piet; D'hooge, Jan

2010-03-01

The quantitative assessment of regional myocardial function remains an important goal in clinical cardiology. As such, tissue Doppler imaging and speckle tracking based methods have been introduced to estimate local myocardial strain. Recently, volumetric ultrasound has become more readily available, allowing therefore the 3D estimation of motion and myocardial deformation. Our lab has previously presented a method based on spatio-temporal elastic registration of ultrasound volumes to estimate myocardial motion and deformation in 3D, overcoming the spatial limitations of the existing methods. This method was optimized on simulated data sets in previous work and is currently tested in a clinical setting. In this manuscript, 10 healthy volunteers, 10 patient with myocardial infarction and 10 patients with arterial hypertension were included. The cardiac strain values extracted with the proposed method were compared with the ones estimated with 1D tissue Doppler imaging and 2D speckle tracking in all patient groups. Although the absolute values of the 3D strain components assessed by this new methodology were not identical to the reference methods, the relationship between the different patient groups was similar.

A head motion estimation algorithm for motion artifact correction in dental CT imaging

NASA Astrophysics Data System (ADS)

Hernandez, Daniel; Elsayed Eldib, Mohamed; Hegazy, Mohamed A. A.; Hye Cho, Myung; Cho, Min Hyoung; Lee, Soo Yeol

2018-03-01

A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.

Robust cardiac motion estimation using ultrafast ultrasound data: a low-rank topology-preserving approach

NASA Astrophysics Data System (ADS)

Aviles, Angelica I.; Widlak, Thomas; Casals, Alicia; Nillesen, Maartje M.; Ammari, Habib

2017-06-01

Cardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.

How many records should be used in ASCE/SEI-7 ground motion scaling procedure?

USGS Publications Warehouse

Reyes, Juan C.; Kalkan, Erol

2012-01-01

U.S. national building codes refer to the ASCE/SEI-7 provisions for selecting and scaling ground motions for use in nonlinear response history analysis of structures. Because the limiting values for the number of records in the ASCE/SEI-7 are based on engineering experience, this study examines the required number of records statistically, such that the scaled records provide accurate, efficient, and consistent estimates of “true” structural responses. Based on elastic–perfectly plastic and bilinear single-degree-of-freedom systems, the ASCE/SEI-7 scaling procedure is applied to 480 sets of ground motions; the number of records in these sets varies from three to ten. As compared to benchmark responses, it is demonstrated that the ASCE/SEI-7 scaling procedure is conservative if fewer than seven ground motions are employed. Utilizing seven or more randomly selected records provides more accurate estimate of the responses. Selecting records based on their spectral shape and design spectral acceleration increases the accuracy and efficiency of the procedure.

High-resolution estimates of Nubia-Somalia plate motion since 20 Ma from reconstructions of the Southwest Indian Ridge, Red Sea, and Gulf of Aden

NASA Astrophysics Data System (ADS)

DeMets, C.; Merkuryev, S. A.

2015-12-01

We estimate Nubia-Somalia rotations at ~1-Myr intervals for the past 20 Myr from newly available, high-resolution reconstructions of the Southwest Indian Ridge and reconstructions of the Red Sea and Gulf of Aden. The former rotations are based on many more data, extend farther back in time, and have more temporal resolution than has previously been the case. Nubia-Somalia plate motion has remained remarkably steady since 5.2 Ma. For example, at the northern end of the East Africa rift, our Nubia-Somalia plate motion estimates at six different times between 0.78 Ma and 5.2 Ma agree to within 3% with the rift-normal component of motion that is extrapolated from the recently estimated Saria et al. (2014) GPS angular velocity. Over the past 10.6 Myr, the Nubia-Somalia rotations predict 42±4 km of rift-normal extension across the northern segment of the Main Ethiopian Rift. This agrees with approximate minimum and maximum estimates of 40 km and 53 km for post-10.6-Myr extension from seismological surveys of this narrow part of the plate boundary and is also close to 55-km and 48±3 km estimates from published and our own reconstructions of the Nubia-Arabia and Somalia-Arabia seafloorspreading histories for the Red Sea and Gulf of Aden. Our new rotations exclude at high confidence level two previously published estimates of Nubia-Somalia motion based on inversions of Chron 5n.2 along the Southwest Indian Ridge, which predict rift-normal extensions of 13±14 km and 129±16 km across the Main Ethiopian Rift since 11 Ma. Constraints on Nubia-Somalia motion before ~15 Ma are weaker due to sparse coverage of pre-15-Myr magnetic reversals along the Nubia-Antarctic plate boundary, but appear to require motion before 15 Ma. Nubia-Somalia rotations that we estimate from a probabilistic analysis of geometric and age constraints from the Red Sea and Gulf of Aden are consistent with those determined from Southwest Indian Ridge data, particularly for the past 11 Myr. Nubia-Somalia rotations determined from the Red Sea/Gulf of Aden rotations and Southwest Indian Ridge rotations independently predict that motion during its oldest phase was highly oblique to the rift and a factor-of-two or more faster than at present, although large uncertainties remain in the rotation estimates for times before ~15 Ma.

Optical Flow Estimation for Flame Detection in Videos

PubMed Central

Mueller, Martin; Karasev, Peter; Kolesov, Ivan; Tannenbaum, Allen

2014-01-01

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise. PMID:23613042

Dipolar filtered magic-sandwich-echoes as a tool for probing molecular motions using time domain NMR

NASA Astrophysics Data System (ADS)

Filgueiras, Jefferson G.; da Silva, Uilson B.; Paro, Giovanni; d'Eurydice, Marcel N.; Cobo, Márcio F.; deAzevedo, Eduardo R.

2017-12-01

We present a simple 1 H NMR approach for characterizing intermediate to fast regime molecular motions using 1 H time-domain NMR at low magnetic field. The method is based on a Goldmann Shen dipolar filter (DF) followed by a Mixed Magic Sandwich Echo (MSE). The dipolar filter suppresses the signals arising from molecular segments presenting sub kHz mobility, so only signals from mobile segments are detected. Thus, the temperature dependence of the signal intensities directly evidences the onset of molecular motions with rates higher than kHz. The DF-MSE signal intensity is described by an analytical function based on the Anderson Weiss theory, from where parameters related to the molecular motion (e.g. correlation times and activation energy) can be estimated when performing experiments as function of the temperature. Furthermore, we propose the use of the Tikhonov regularization for estimating the width of the distribution of correlation times.

Plate motions and deformations from geologic and geodetic data

NASA Technical Reports Server (NTRS)

Jordan, T. H.

1986-01-01

Research effort on behalf of the Crustal Dynamics Project focused on the development of methodologies suitable for the analysis of space-geodetic data sets for the estimation of crustal motions, in conjunction with results derived from land-based geodetic data, neo-tectonic studies, and other geophysical data. These methodologies were used to provide estimates of both global plate motions and intraplate deformation in the western U.S. Results from the satellite ranging experiment for the rate of change of the baseline length between San Diego and Quincy, California indicated that relative motion between the North American and Pacific plates over the course of the observing period during 1972 to 1982 were consistent with estimates calculated from geologic data averaged over the past few million years. This result, when combined with other kinematic constraints on western U.S. deformation derived from land-based geodesy, neo-tectonic studies, and other geophysical data, places limits on the possible extension of the Basin and Range province, and implies significant deformation is occurring west of the San Andreas fault. A new methodology was developed to analyze vector-position space-geodetic data to provide estimates of relative vector motions of the observing sites. The algorithm is suitable for the reduction of large, inhomogeneous data sets, and takes into account the full position covariances, errors due to poorly resolved Earth orientation parameters and vertical positions, and reduces baises due to inhomogeneous sampling of the data. This methodology was applied to the problem of estimating the rate-scaling parameter of a global plate tectonic model using satellite laser ranging observations over a five-year interval. The results indicate that the mean rate of global plate motions for that interval are consistent with those averaged over several million years, and are not consistent with quiescent or greatly accelerated plate motions. This methodology was also used to provide constraints on deformation in the western U.S. using very long baseline interferometry observations over a two-year period.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Whole-Body Human Inverse Dynamics with Distributed Micro-Accelerometers, Gyros and Force Sensing †

PubMed Central

Latella, Claudia; Kuppuswamy, Naveen; Romano, Francesco; Traversaro, Silvio; Nori, Francesco

2016-01-01

Human motion tracking is a powerful tool used in a large range of applications that require human movement analysis. Although it is a well-established technique, its main limitation is the lack of estimation of real-time kinetics information such as forces and torques during the motion capture. In this paper, we present a novel approach for a human soft wearable force tracking for the simultaneous estimation of whole-body forces along with the motion. The early stage of our framework encompasses traditional passive marker based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational technique for estimating dynamic quantities, originally proposed in the domain of humanoid robot control. We present experimental analysis on subjects performing a two degrees-of-freedom bowing task, and we estimate the motion and kinetics quantities. The results demonstrate the validity of the proposed method. We discuss the possible use of this technique in the design of a novel soft wearable force tracking device and its potential applications. PMID:27213394

Autonomous Landmark Calibration Method for Indoor Localization

PubMed Central

Kim, Jae-Hoon; Kim, Byoung-Seop

2017-01-01

Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. PMID:28837071

VO2 estimation using 6-axis motion sensor with sports activity classification.

PubMed

Nagata, Takashi; Nakamura, Naoteru; Miyatake, Masato; Yuuki, Akira; Yomo, Hiroyuki; Kawabata, Takashi; Hara, Shinsuke

2016-08-01

In this paper, we focus on oxygen consumption (VO2) estimation using 6-axis motion sensor (3-axis accelerometer and 3-axis gyroscope) for people playing sports with diverse intensities. The VO2 estimated with a small motion sensor can be used to calculate the energy expenditure, however, its accuracy depends on the intensities of various types of activities. In order to achieve high accuracy over a wide range of intensities, we employ an estimation framework that first classifies activities with a simple machine-learning based classification algorithm. We prepare different coefficients of linear regression model for different types of activities, which are determined with training data obtained by experiments. The best-suited model is used for each type of activity when VO2 is estimated. The accuracy of the employed framework depends on the trade-off between the degradation due to classification errors and improvement brought by applying separate, optimum model to VO2 estimation. Taking this trade-off into account, we evaluate the accuracy of the employed estimation framework by using a set of experimental data consisting of VO2 and motion data of people with a wide range of intensities of exercises, which were measured by a VO2 meter and motion sensor, respectively. Our numerical results show that the employed framework can improve the estimation accuracy in comparison to a reference method that uses a common regression model for all types of activities.

Image Motion Detection And Estimation: The Modified Spatio-Temporal Gradient Scheme

NASA Astrophysics Data System (ADS)

Hsin, Cheng-Ho; Inigo, Rafael M.

1990-03-01

The detection and estimation of motion are generally involved in computing a velocity field of time-varying images. A completely new modified spatio-temporal gradient scheme to determine motion is proposed. This is derived by using gradient methods and properties of biological vision. A set of general constraints is proposed to derive motion constraint equations. The constraints are that the second directional derivatives of image intensity at an edge point in the smoothed image will be constant at times t and t+L . This scheme basically has two stages: spatio-temporal filtering, and velocity estimation. Initially, image sequences are processed by a set of oriented spatio-temporal filters which are designed using a Gaussian derivative model. The velocity is then estimated for these filtered image sequences based on the gradient approach. From a computational stand point, this scheme offers at least three advantages over current methods. The greatest advantage of the modified spatio-temporal gradient scheme over the traditional ones is that an infinite number of motion constraint equations are derived instead of only one. Therefore, it solves the aperture problem without requiring any additional assumptions and is simply a local process. The second advantage is that because of the spatio-temporal filtering, the direct computation of image gradients (discrete derivatives) is avoided. Therefore the error in gradients measurement is reduced significantly. The third advantage is that during the processing of motion detection and estimation algorithm, image features (edges) are produced concurrently with motion information. The reliable range of detected velocity is determined by parameters of the oriented spatio-temporal filters. Knowing the velocity sensitivity of a single motion detection channel, a multiple-channel mechanism for estimating image velocity, seldom addressed by other motion schemes in machine vision, can be constructed by appropriately choosing and combining different sets of parameters. By applying this mechanism, a great range of velocity can be detected. The scheme has been tested for both synthetic and real images. The results of simulations are very satisfactory.

Different motion cues are used to estimate time-to-arrival for frontoparallel and looming trajectories

PubMed Central

Calabro, Finnegan J.; Beardsley, Scott A.; Vaina, Lucia M.

2012-01-01

Estimation of time-to-arrival for moving objects is critical to obstacle interception and avoidance, as well as to timing actions such as reaching and grasping moving objects. The source of motion information that conveys arrival time varies with the trajectory of the object raising the question of whether multiple context-dependent mechanisms are involved in this computation. To address this question we conducted a series of psychophysical studies to measure observers’ performance on time-to-arrival estimation when object trajectory was specified by angular motion (“gap closure” trajectories in the frontoparallel plane), looming (colliding trajectories, TTC) or both (passage courses, TTP). We measured performance of time-to-arrival judgments in the presence of irrelevant motion, in which a perpendicular motion vector was added to the object trajectory. Data were compared to models of expected performance based on the use of different components of optical information. Our results demonstrate that for gap closure, performance depended only on the angular motion, whereas for TTC and TTP, both angular and looming motion affected performance. This dissociation of inputs suggests that gap closures are mediated by a separate mechanism than that used for the detection of time-to-collision and time-to-passage. We show that existing models of TTC and TTP estimation make systematic errors in predicting subject performance, and suggest that a model which weights motion cues by their relative time-to-arrival provides a better account of performance. PMID:22056519

Constrained motion estimation-based error resilient coding for HEVC

NASA Astrophysics Data System (ADS)

Guo, Weihan; Zhang, Yongfei; Li, Bo

2018-04-01

Unreliable communication channels might lead to packet losses and bit errors in the videos transmitted through it, which will cause severe video quality degradation. This is even worse for HEVC since more advanced and powerful motion estimation methods are introduced to further remove the inter-frame dependency and thus improve the coding efficiency. Once a Motion Vector (MV) is lost or corrupted, it will cause distortion in the decoded frame. More importantly, due to motion compensation, the error will propagate along the motion prediction path, accumulate over time, and significantly degrade the overall video presentation quality. To address this problem, we study the problem of encoder-sider error resilient coding for HEVC and propose a constrained motion estimation scheme to mitigate the problem of error propagation to subsequent frames. The approach is achieved by cutting off MV dependencies and limiting the block regions which are predicted by temporal motion vector. The experimental results show that the proposed method can effectively suppress the error propagation caused by bit errors of motion vector and can improve the robustness of the stream in the bit error channels. When the bit error probability is 10-5, an increase of the decoded video quality (PSNR) by up to1.310dB and on average 0.762 dB can be achieved, compared to the reference HEVC.

Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator.

PubMed

Jiang, Wenwen; Ong, Frank; Johnson, Kevin M; Nagle, Scott K; Hope, Thomas A; Lustig, Michael; Larson, Peder E Z

2018-06-01

To achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data. Five-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states. Respiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients. An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

Qian, Jiuchao; Pei, Ling; Ma, Jiabin; Ying, Rendong; Liu, Peilin

2015-01-01

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts. PMID:25738763

An interdimensional correlation framework for real-time estimation of six degree of freedom target motion using a single x-ray imager during radiotherapy

NASA Astrophysics Data System (ADS)

Nguyen, D. T.; Bertholet, J.; Kim, J.-H.; O'Brien, R.; Booth, J. T.; Poulsen, P. R.; Keall, P. J.

2018-01-01

Increasing evidence suggests that intrafraction tumour motion monitoring needs to include both 3D translations and 3D rotations. Presently, methods to estimate the rotation motion require the 3D translation of the target to be known first. However, ideally, translation and rotation should be estimated concurrently. We present the first method to directly estimate six-degree-of-freedom (6DoF) motion from the target’s projection on a single rotating x-ray imager in real-time. This novel method is based on the linear correlations between the superior-inferior translations and the motion in the other five degrees-of-freedom. The accuracy of the method was evaluated in silico with 81 liver tumour motion traces from 19 patients with three implanted markers. The ground-truth motion was estimated using the current gold standard method where each marker’s 3D position was first estimated using a Gaussian probability method, and the 6DoF motion was then estimated from the 3D positions using an iterative method. The 3D position of each marker was projected onto a gantry-mounted imager with an imaging rate of 11 Hz. After an initial 110° gantry rotation (200 images), a correlation model between the superior-inferior translations and the five other DoFs was built using a least square method. The correlation model was then updated after each subsequent frame to estimate 6DoF motion in real-time. The proposed algorithm had an accuracy (±precision) of  -0.03  ±  0.32 mm, -0.01  ±  0.13 mm and 0.03  ±  0.52 mm for translations in the left-right (LR), superior-inferior (SI) and anterior-posterior (AP) directions respectively; and, 0.07  ±  1.18°, 0.07  ±  1.00° and 0.06  ±  1.32° for rotations around the LR, SI and AP axes respectively on the dataset. The first method to directly estimate real-time 6DoF target motion from segmented marker positions on a 2D imager was devised. The algorithm was evaluated using 81 motion traces from 19 liver patients and was found to have sub-mm and sub-degree accuracy.

Development and validation of a rebinner with rigid motion correction for the Siemens PET-MR scanner: Application to a large cohort of [11C]-PIB scans.

PubMed

Reilhac, Anthonin; Merida, Ines; Irace, Zacharie; Stephenson, Mary; Weekes, Ashley; Chen, Christopher; Totman, John; Townsend, David W; Fayad, Hadi; Costes, Nicolas

2018-04-13

Objective: Head motion occuring during brain PET studies leads to image blurring and to bias in measured local quantities. Our first objective was to implement an accurate list-mode-based rigid motion correction method for PET data acquired with the mMR synchronous Positron Emission Tomography/Magnetic Resonance (PET/MR) scanner. Our second objective was to optimize the correction for [ 11 C]-PIB scans using simulated and actual data with well-controlled motions. Results: An efficient list-mode based motion correction approach has been implemented, fully optimized and validated using simulated as well as actual PET data. The average spatial resolution loss induced by inaccuracies in motion parameter estimates as well as by the rebinning process was estimated to correspond to a 1 mm increase in Full Width Half Maximum (FWHM) with motion parameters estimated directly from the PET data with a temporal frequency of 20 secs. The results show that it can be safely applied to the [ 11 C]-PIB scans, allowing almost complete removal of motion induced artifacts.The application of the correction method on a large cohort of 11C-PIB scans led to the following observations: i) more than 21% of the scans were affected by a motion greater than 10 mm (39% for subjects with Mini-Mental State Examination -MMSE scores below 20) and ii), the correction led to quantitative changes in Alzheimer-specific cortical regions of up to 30%. Conclusion: The rebinner allows an accurate motion correction at a cost of minimal resolution reduction. The application of the correction to a large cohort of [ 11 C]-PIB scans confirmed the necessity to systematically correct for motion for quantitative results. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Methodology for estimating human perception to tremors in high-rise buildings

NASA Astrophysics Data System (ADS)

Du, Wenqi; Goh, Key Seng; Pan, Tso-Chien

2017-07-01

Human perception to tremors during earthquakes in high-rise buildings is usually associated with psychological discomfort such as fear and anxiety. This paper presents a methodology for estimating the level of perception to tremors for occupants living in high-rise buildings subjected to ground motion excitations. Unlike other approaches based on empirical or historical data, the proposed methodology performs a regression analysis using the analytical results of two generic models of 15 and 30 stories. The recorded ground motions in Singapore are collected and modified for structural response analyses. Simple predictive models are then developed to estimate the perception level to tremors based on a proposed ground motion intensity parameter—the average response spectrum intensity in the period range between 0.1 and 2.0 s. These models can be used to predict the percentage of occupants in high-rise buildings who may perceive the tremors at a given ground motion intensity. Furthermore, the models are validated with two recent tremor events reportedly felt in Singapore. It is found that the estimated results match reasonably well with the reports in the local newspapers and from the authorities. The proposed methodology is applicable to urban regions where people living in high-rise buildings might feel tremors during earthquakes.

Motion estimation under location uncertainty for turbulent fluid flows

NASA Astrophysics Data System (ADS)

Cai, Shengze; Mémin, Etienne; Dérian, Pierre; Xu, Chao

2018-01-01

In this paper, we propose a novel optical flow formulation for estimating two-dimensional velocity fields from an image sequence depicting the evolution of a passive scalar transported by a fluid flow. This motion estimator relies on a stochastic representation of the flow allowing to incorporate naturally a notion of uncertainty in the flow measurement. In this context, the Eulerian fluid flow velocity field is decomposed into two components: a large-scale motion field and a small-scale uncertainty component. We define the small-scale component as a random field. Subsequently, the data term of the optical flow formulation is based on a stochastic transport equation, derived from the formalism under location uncertainty proposed in Mémin (Geophys Astrophys Fluid Dyn 108(2):119-146, 2014) and Resseguier et al. (Geophys Astrophys Fluid Dyn 111(3):149-176, 2017a). In addition, a specific regularization term built from the assumption of constant kinetic energy involves the very same diffusion tensor as the one appearing in the data transport term. Opposite to the classical motion estimators, this enables us to devise an optical flow method dedicated to fluid flows in which the regularization parameter has now a clear physical interpretation and can be easily estimated. Experimental evaluations are presented on both synthetic and real world image sequences. Results and comparisons indicate very good performance of the proposed formulation for turbulent flow motion estimation.

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, J; Nguyen, D; O’Brien, R

Purpose: Kilovoltage intrafraction monitoring (KIM) scheme has been successfully used to simultaneously monitor 3D tumor motion during radiotherapy. Recently, an iterative closest point (ICP) algorithm was implemented in KIM to also measure rotations about three axes, enabling real-time tracking of tumor motion in six degrees-of-freedom (DoF). This study aims to evaluate the accuracy of the six DoF motion estimates of KIM by comparing it with the corresponding motion (i) measured by the Calypso; and (ii) derived from kV/MV triangulation. Methods: (i) Various motions (static and dynamic) were applied to a CIRS phantom with three embedded electromagnetic transponders (Calypso Medical) usingmore » a 5D motion platform (HexaMotion) and a rotating treatment couch while both KIM and Calypso were used to concurrently track the phantom motion in six DoF. (ii) KIM was also used to retrospectively estimate six DoF motion from continuous sets of kV projections of a prostate, implanted with three gold fiducial markers (2 patients with 80 fractions in total), acquired during the treatment. Corresponding motion was obtained from kV/MV triangulation using a closed form least squares method based on three markers’ positions. Only the frames where all three markers were present were used in the analysis. The mean differences between the corresponding motion estimates were calculated for each DoF. Results: Experimental results showed that the mean of absolute differences in six DoF phantom motion measured by Calypso and KIM were within 1.1° and 0.7 mm. kV/MV triangulation derived six DoF prostate tumor better agreed with KIM estimated motion with the mean (s.d.) difference of up to 0.2° (1.36°) and 0.2 (0.25) mm for rotation and translation, respectively. Conclusion: These results suggest that KIM can provide an accurate six DoF intrafraction tumor during radiotherapy.« less

On-chip visual perception of motion: a bio-inspired connectionist model on FPGA.

PubMed

Torres-Huitzil, César; Girau, Bernard; Castellanos-Sánchez, Claudio

2005-01-01

Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented. The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering. The architecture is constituted by three main modules that perform spatial, temporal, and excitatory-inhibitory connectionist processing. The biomimetic architecture is modeled, simulated and validated in VHDL. The synthesis results on a Field Programmable Gate Array (FPGA) device show the potential achievement of real-time performance at an affordable silicon area.

FPGA-based fused smart sensor for dynamic and vibration parameter extraction in industrial robot links.

PubMed

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

PubMed Central

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA). PMID:22319345

A variational reconstruction method for undersampled dynamic x-ray tomography based on physical motion models

NASA Astrophysics Data System (ADS)

Burger, Martin; Dirks, Hendrik; Frerking, Lena; Hauptmann, Andreas; Helin, Tapio; Siltanen, Samuli

2017-12-01

In this paper we study the reconstruction of moving object densities from undersampled dynamic x-ray tomography in two dimensions. A particular motivation of this study is to use realistic measurement protocols for practical applications, i.e. we do not assume to have a full Radon transform in each time step, but only projections in few angular directions. This restriction enforces a space-time reconstruction, which we perform by incorporating physical motion models and regularization of motion vectors in a variational framework. The methodology of optical flow, which is one of the most common methods to estimate motion between two images, is utilized to formulate a joint variational model for reconstruction and motion estimation. We provide a basic mathematical analysis of the forward model and the variational model for the image reconstruction. Moreover, we discuss the efficient numerical minimization based on alternating minimizations between images and motion vectors. A variety of results are presented for simulated and real measurement data with different sampling strategy. A key observation is that random sampling combined with our model allows reconstructions of similar amount of measurements and quality as a single static reconstruction.

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Restoration of motion blurred images

NASA Astrophysics Data System (ADS)

Gaxiola, Leopoldo N.; Juarez-Salazar, Rigoberto; Diaz-Ramirez, Victor H.

2017-08-01

Image restoration is a classic problem in image processing. Image degradations can occur due to several reasons, for instance, imperfections of imaging systems, quantization errors, atmospheric turbulence, relative motion between camera or objects, among others. Motion blur is a typical degradation in dynamic imaging systems. In this work, we present a method to estimate the parameters of linear motion blur degradation from a captured blurred image. The proposed method is based on analyzing the frequency spectrum of a captured image in order to firstly estimate the degradation parameters, and then, to restore the image with a linear filter. The performance of the proposed method is evaluated by processing synthetic and real-life images. The obtained results are characterized in terms of accuracy of image restoration given by an objective criterion.

Fidelity of the ensemble code for visual motion in primate retina.

PubMed

Frechette, E S; Sher, A; Grivich, M I; Petrusca, D; Litke, A M; Chichilnisky, E J

2005-07-01

Sensory experience typically depends on the ensemble activity of hundreds or thousands of neurons, but little is known about how populations of neurons faithfully encode behaviorally important sensory information. We examined how precisely speed of movement is encoded in the population activity of magnocellular-projecting parasol retinal ganglion cells (RGCs) in macaque monkey retina. Multi-electrode recordings were used to measure the activity of approximately 100 parasol RGCs simultaneously in isolated retinas stimulated with moving bars. To examine how faithfully the retina signals motion, stimulus speed was estimated directly from recorded RGC responses using an optimized algorithm that resembles models of motion sensing in the brain. RGC population activity encoded speed with a precision of approximately 1%. The elementary motion signal was conveyed in approximately 10 ms, comparable to the interspike interval. Temporal structure in spike trains provided more precise speed estimates than time-varying firing rates. Correlated activity between RGCs had little effect on speed estimates. The spatial dispersion of RGC receptive fields along the axis of motion influenced speed estimates more strongly than along the orthogonal direction, as predicted by a simple model based on RGC response time variability and optimal pooling. on and off cells encoded speed with similar and statistically independent variability. Simulation of downstream speed estimation using populations of speed-tuned units showed that peak (winner take all) readout provided more precise speed estimates than centroid (vector average) readout. These findings reveal how faithfully the retinal population code conveys information about stimulus speed and the consequences for motion sensing in the brain.

Vehicle dynamics control of four in-wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation

NASA Astrophysics Data System (ADS)

Xiong, Lu; Yu, Zhuoping; Wang, Yang; Yang, Chen; Meng, Yufeng

2012-06-01

This paper focuses on the vehicle dynamic control system for a four in-wheel motor drive electric vehicle, aiming at improving vehicle stability under critical driving conditions. The vehicle dynamics controller is composed of three modules, i.e. motion following control, control allocation and vehicle state estimation. Considering the strong nonlinearity of the tyres under critical driving conditions, the yaw motion of the vehicle is regulated by gain scheduling control based on the linear quadratic regulator theory. The feed-forward and feedback gains of the controller are updated in real-time by online estimation of the tyre cornering stiffness, so as to ensure the control robustness against environmental disturbances as well as parameter uncertainty. The control allocation module allocates the calculated generalised force requirements to each in-wheel motor based on quadratic programming theory while taking the tyre longitudinal/lateral force coupling characteristic into consideration. Simulations under a variety of driving conditions are carried out to verify the control algorithm. Simulation results indicate that the proposed vehicle stability controller can effectively stabilise the vehicle motion under critical driving conditions.

A Preliminary Examination of the Second Generation CMORPH Real-time Production

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.; Wu, S.

2017-12-01

The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05olat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and precipitation simulations from the NCEP operational global forecast system (GFS). Inputs from the various sources are first inter-calibrated to ensure quantitative consistencies in representing precipitation events of different intensities through PDF calibration against a common reference standard. The inter-calibrated PMW retrievals and IR-based precipitation estimates are then propagated from their respective observation times to the target analysis time along the motion vectors of the precipitating clouds. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the GFS precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. The propagated PMW and IR based precipitation estimates are finally integrated into a single field of global precipitation through the Kalman Filter framework. A set of procedures have been established to examine the performance of the CMORPH2 real-time production. CMORPH2 satellite precipitation estimates are compared against the CPC daily gauge analysis, Stage IV radar precipitation over the CONUS, and numerical model forecasts to discover potential shortcomings and quantify improvements against the first generation CMORPH. Special attention has been focused on the CMORPH behavior over high-latitude areas beyond the coverage of the first generation CMORPH. Detailed results will be reported at the AGU.

WE-D-303-02: Applications of Volumetric Images Generated with a Respiratory Motion Model Based On An External Surrogate Signal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hurwitz, M; Williams, C; Dhou, S

Purpose: Respiratory motion can vary significantly over the course of simulation and treatment. Our goal is to use volumetric images generated with a respiratory motion model to improve the definition of the internal target volume (ITV) and the estimate of delivered dose. Methods: Ten irregular patient breathing patterns spanning 35 seconds each were incorporated into a digital phantom. Ten images over the first five seconds of breathing were used to emulate a 4DCT scan, build the ITV, and generate a patient-specific respiratory motion model which correlated the measured trajectories of markers placed on the patients’ chests with the motion ofmore » the internal anatomy. This model was used to generate volumetric images over the subsequent thirty seconds of breathing. The increase in the ITV taking into account the full 35 seconds of breathing was assessed with ground-truth and model-generated images. For one patient, a treatment plan based on the initial ITV was created and the delivered dose was estimated using images from the first five seconds as well as ground-truth and model-generated images from the next 30 seconds. Results: The increase in the ITV ranged from 0.2 cc to 6.9 cc for the ten patients based on ground-truth information. The model predicted this increase in the ITV with an average error of 0.8 cc. The delivered dose to the tumor (D95) changed significantly from 57 Gy to 41 Gy when estimated using 5 seconds and 30 seconds, respectively. The model captured this effect, giving an estimated D95 of 44 Gy. Conclusion: A respiratory motion model generating volumetric images of the internal patient anatomy could be useful in estimating the increase in the ITV due to irregular breathing during simulation and in assessing delivered dose during treatment. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc. and Radiological Society of North America Research Scholar Grant #RSCH1206.« less

WE-AB-204-09: Respiratory Motion Correction in 4D-PET by Simultaneous Motion Estimation and Image Reconstruction (SMEIR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalantari, F; Wang, J; Li, T

2015-06-15

Purpose: In conventional 4D-PET, images from different frames are reconstructed individually and aligned by registration methods. Two issues with these approaches are: 1) Reconstruction algorithms do not make full use of all projections statistics; and 2) Image registration between noisy images can Result in poor alignment. In this study we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) method for cone beam CT for motion estimation/correction in 4D-PET. Methods: Modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM- TV) is used to obtain a primary motion-compensated PET (pmc-PET) from all projection data using Demons derivedmore » deformation vector fields (DVFs) as initial. Motion model update is done to obtain an optimal set of DVFs between the pmc-PET and other phases by matching the forward projection of the deformed pmc-PET and measured projections of other phases. Using updated DVFs, OSEM- TV image reconstruction is repeated and new DVFs are estimated based on updated images. 4D XCAT phantom with typical FDG biodistribution and a 10mm diameter tumor was used to evaluate the performance of the SMEIR algorithm. Results: Image quality of 4D-PET is greatly improved by the SMEIR algorithm. When all projections are used to reconstruct a 3D-PET, motion blurring artifacts are present, leading to a more than 5 times overestimation of the tumor size and 54% tumor to lung contrast ratio underestimation. This error reduced to 37% and 20% for post reconstruction registration methods and SMEIR respectively. Conclusion: SMEIR method can be used for motion estimation/correction in 4D-PET. The statistics is greatly improved since all projection data are combined together to update the image. The performance of the SMEIR algorithm for 4D-PET is sensitive to smoothness control parameters in the DVF estimation step.« less

Gyroscope-reduced inertial navigation system for flight vehicle motion estimation

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiao, Lu

2017-01-01

In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.

On event-based optical flow detection

PubMed Central

Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

2015-01-01

Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

A robotic orbital emulator with lidar-based SLAM and AMCL for multiple entity pose estimation

NASA Astrophysics Data System (ADS)

Shen, Dan; Xiang, Xingyu; Jia, Bin; Wang, Zhonghai; Chen, Genshe; Blasch, Erik; Pham, Khanh

2018-05-01

This paper revises and evaluates an orbital emulator (OE) for space situational awareness (SSA). The OE can produce 3D satellite movements using capabilities generated from omni-wheeled robot and robotic arm motions. The 3D motion of satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The 3D actions are emulated by omni-wheeled robot models while the up-down motions are performed by a stepped-motorcontrolled- ball along a rod (robotic arm), which is attached to the robot. Lidar only measurements are used to estimate the pose information of the multiple robots. SLAM (simultaneous localization and mapping) is running on one robot to generate the map and compute the pose for the robot. Based on the SLAM map maintained by the robot, the other robots run the adaptive Monte Carlo localization (AMCL) method to estimate their poses. The controller is designed to guide the robot to follow a given orbit. The controllability is analyzed by using a feedback linearization method. Experiments are conducted to show the convergence of AMCL and the orbit tracking performance.

Aging persons' estimates of vehicular motion.

PubMed

Schiff, W; Oldak, R; Shah, V

1992-12-01

Estimated arrival times of moving autos were examined in relation to viewer age, gender, motion trajectory, and velocity. Direct push-button judgments were compared with verbal estimates derived from velocity and distance, which were based on assumptions that perceivers compute arrival time from perceived distance and velocity. Experiment 1 showed that direct estimates of younger Ss were most accurate. Older women made the shortest (highly cautious) estimates of when cars would arrive. Verbal estimates were much lower than direct estimates, with little correlation between them. Experiment 2 extended target distances and velocities of targets, with the results replicating the main findings of Experiment 1. Judgment accuracy increased with target velocity, and verbal estimates were again poorer estimates of arrival time than direct ones, with different patterns of findings. Using verbal estimates to approximate judgments in traffic situations appears questionable.

Representation of Reserves Through a Brownian Motion Model

NASA Astrophysics Data System (ADS)

Andrade, M.; Ferreira, M. A. M.; Filipe, J. A.

2012-11-01

The Brownian Motion is commonly used as an approximation for some Random Walks and also for the Classic Risk Process. As the Random Walks and the Classic Risk Process are used frequently as stochastic models to represent reserves, it is natural to consider the Brownian Motion with the same purpose. In this study a model, based on the Brownian Motion, is presented to represent reserves. The Brownian Motion is used in this study to estimate the ruin probability of a fund. This kind of models is considered often in the study of pensions funds.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.

PubMed

Tannous, Halim; Istrate, Dan; Benlarbi-Delai, Aziz; Sarrazin, Julien; Gamet, Didier; Ho Ba Tho, Marie Christine; Dao, Tien Tuan

2016-11-15

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

MR-assisted PET motion correction in simultaneous PET/MRI studies of dementia subjects.

PubMed

Chen, Kevin T; Salcedo, Stephanie; Chonde, Daniel B; Izquierdo-Garcia, David; Levine, Michael A; Price, Julie C; Dickerson, Bradford C; Catana, Ciprian

2018-03-08

Subject motion in positron emission tomography (PET) studies leads to image blurring and artifacts; simultaneously acquired magnetic resonance imaging (MRI) data provides a means for motion correction (MC) in integrated PET/MRI scanners. To assess the effect of realistic head motion and MR-based MC on static [ 18 F]-fluorodeoxyglucose (FDG) PET images in dementia patients. Observational study. Thirty dementia subjects were recruited. 3T hybrid PET/MR scanner where EPI-based and T 1 -weighted sequences were acquired simultaneously with the PET data. Head motion parameters estimated from high temporal resolution MR volumes were used for PET MC. The MR-based MC method was compared to PET frame-based MC methods in which motion parameters were estimated by coregistering 5-minute frames before and after accounting for the attenuation-emission mismatch. The relative changes in standardized uptake value ratios (SUVRs) between the PET volumes processed with the various MC methods, without MC, and the PET volumes with simulated motion were compared in relevant brain regions. The absolute value of the regional SUVR relative change was assessed with pairwise paired t-tests testing at the P = 0.05 level, comparing the values obtained through different MR-based MC processing methods as well as across different motion groups. The intraregion voxelwise variability of regional SUVRs obtained through different MR-based MC processing methods was also assessed with pairwise paired t-tests testing at the P = 0.05 level. MC had a greater impact on PET data quantification in subjects with larger amplitude motion (higher than 18% in the medial orbitofrontal cortex) and greater changes were generally observed for the MR-based MC method compared to the frame-based methods. Furthermore, a mean relative change of ∼4% was observed after MC even at the group level, suggesting the importance of routinely applying this correction. The intraregion voxelwise variability of regional SUVRs was also decreased using MR-based MC. All comparisons were significant at the P = 0.05 level. Incorporating temporally correlated MR data to account for intraframe motion has a positive impact on the FDG PET image quality and data quantification in dementia patients. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Estimating the accuracy of the technique of reconstructing the rotational motion of a satellite based on the measurements of its angular velocity and the magnetic field of the Earth

NASA Astrophysics Data System (ADS)

Belyaev, M. Yu.; Volkov, O. N.; Monakhov, M. I.; Sazonov, V. V.

2017-09-01

The paper has studied the accuracy of the technique that allows the rotational motion of the Earth artificial satellites (AES) to be reconstructed based on the data of onboard measurements of angular velocity vectors and the strength of the Earth magnetic field (EMF). The technique is based on kinematic equations of the rotational motion of a rigid body. Both types of measurement data collected over some time interval have been processed jointly. The angular velocity measurements have been approximated using convenient formulas, which are substituted into the kinematic differential equations for the quaternion that specifies the transition from the body-fixed coordinate system of a satellite to the inertial coordinate system. Thus obtained equations represent a kinematic model of the rotational motion of a satellite. The solution of these equations, which approximate real motion, has been found by the least-square method from the condition of best fitting between the data of measurements of the EMF strength vector and its calculated values. The accuracy of the technique has been estimated by processing the data obtained from the board of the service module of the International Space Station ( ISS). The reconstruction of station motion using the aforementioned technique has been compared with the telemetry data on the actual motion of the station. The technique has allowed us to reconstruct the station motion in the orbital orientation mode with a maximum error less than 0.6° and the turns with a maximal error of less than 1.2°.

Nonrigid registration-based coronary artery motion correction for cardiac computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhagalia, Roshni; Pack, Jed D.; Miller, James V.

2012-07-15

Purpose: X-ray computed tomography angiography (CTA) is the modality of choice to noninvasively monitor and diagnose heart disease with coronary artery health and stenosis detection being of particular interest. Reliable, clinically relevant coronary artery imaging mandates high spatiotemporal resolution. However, advances in intrinsic scanner spatial resolution (CT scanners are available which combine nearly 900 detector columns with focal spot oversampling) can be tempered by motion blurring, particularly in patients with unstable heartbeats. As a result, recently numerous methods have been devised to improve coronary CTA imaging. Solutions involving hardware, multisector algorithms, or {beta}-blockers are limited by cost, oversimplifying assumptions aboutmore » cardiac motion, and populations showing contraindications to drugs, respectively. This work introduces an inexpensive algorithmic solution that retrospectively improves the temporal resolution of coronary CTA without significantly affecting spatial resolution. Methods: Given the goal of ruling out coronary stenosis, the method focuses on 'deblurring' the coronary arteries. The approach makes no assumptions about cardiac motion, can be used on exams acquired at high heart rates (even over 75 beats/min), and draws on a fast and accurate three-dimensional (3D) nonrigid bidirectional labeled point matching approach to estimate the trajectories of the coronary arteries during image acquisition. Motion compensation is achieved by employing a 3D warping of a series of partial reconstructions based on the estimated motion fields. Each of these partial reconstructions is created from data acquired over a short time interval. For brevity, the algorithm 'Subphasic Warp and Add' (SWA) reconstruction. Results: The performance of the new motion estimation-compensation approach was evaluated by a systematic observer study conducted using nine human cardiac CTA exams acquired over a range of average heart rates between 68 and 86 beats/min. Algorithm performance was based-lined against exams reconstructed using standard filtered-backprojection (FBP). The study was performed by three experienced reviewers using the American Heart Association's 15-segment model. All vessel segments were evaluated to quantify their viability to allow a clinical diagnosis before and after motion estimation-compensation using SWA. To the best of the authors' knowledge this is the first such observer study to show that an image processing-based software approach can improve the clinical diagnostic value of CTA for coronary artery evaluation. Conclusions: Results from the observer study show that the SWA method described here can dramatically reduce coronary artery motion and preserve real pathology, without affecting spatial resolution. In particular, the method successfully mitigated motion artifacts in 75% of all initially nondiagnostic coronary artery segments, and in over 45% of the cases this improvement was enough to make a previously nondiagnostic vessel segment clinically diagnostic.« less

A Comprehensive Motion Estimation Technique for the Improvement of EIS Methods Based on the SURF Algorithm and Kalman Filter.

PubMed

Cheng, Xuemin; Hao, Qun; Xie, Mengdi

2016-04-07

Video stabilization is an important technology for removing undesired motion in videos. This paper presents a comprehensive motion estimation method for electronic image stabilization techniques, integrating the speeded up robust features (SURF) algorithm, modified random sample consensus (RANSAC), and the Kalman filter, and also taking camera scaling and conventional camera translation and rotation into full consideration. Using SURF in sub-pixel space, feature points were located and then matched. The false matched points were removed by modified RANSAC. Global motion was estimated by using the feature points and modified cascading parameters, which reduced the accumulated errors in a series of frames and improved the peak signal to noise ratio (PSNR) by 8.2 dB. A specific Kalman filter model was established by considering the movement and scaling of scenes. Finally, video stabilization was achieved with filtered motion parameters using the modified adjacent frame compensation. The experimental results proved that the target images were stabilized even when the vibrating amplitudes of the video become increasingly large.

Analysis of Nematode Motion Using an Improved Light-Scatter Based System

PubMed Central

Nutting, Chuck S.; Eversole, Rob R.; Blair, Kevin; Specht, Sabine; Nutman, Thomas B.; Klion, Amy D.; Wanji, Samuel; Boussinesq, Michel; Mackenzie, Charles D.

2015-01-01

Background The detailed assessment of nematode activity and viability still remains a relatively undeveloped area of biological and medical research. Computer-based approaches to assessing the motility of larger nematode stages have been developed, yet these lack the capability to detect and analyze the more subtle and important characteristics of the motion of nematodes. There is currently a need to improved methods of assessing the viability and health of parasitic worms. Methods We describe here a system that converts the motion of nematodes through a light-scattering system into an electrical waveform, and allows for reproducible, and wholly non-subjective, assessment of alterations in motion, as well as estimation of the number of nematode worms of different forms and sizes. Here we have used Brugia sp. microfilariae (L1), infective larvae (L3) and adults, together with the free-living nematode Caenorhabditis elegans. Results The motion of worms in a small (200ul) volume can be detected, with the presence of immotile worms not interfering with the readings at practical levels (up to at least 500 L1 /200ul). Alterations in the frequency of parasite movement following the application of the anti-parasitic drugs, (chloroquine and imatinib); the anti-filarial effect of the latter agent is the first demonstrated here for the first time. This system can also be used to estimate the number of parasites, and shortens the time required to estimate parasites numbers, and eliminates the need for microscopes and trained technicians to provide an estimate of microfilarial sample sizes up to 1000 parasites/ml. Alterations in the form of motion of the worms can also be depicted. Conclusions This new instrument, named a "WiggleTron", offers exciting opportunities to further study nematode biology and to aid drug discovery, as well as contributing to a rapid estimate of parasite numbers in various biological samples. PMID:25695776

Analysis of nematode motion using an improved light-scatter based system.

PubMed

Nutting, Chuck S; Eversole, Rob R; Blair, Kevin; Specht, Sabine; Nutman, Thomas B; Klion, Amy D; Wanji, Samuel; Boussinesq, Michel; Mackenzie, Charles D

2015-02-01

The detailed assessment of nematode activity and viability still remains a relatively undeveloped area of biological and medical research. Computer-based approaches to assessing the motility of larger nematode stages have been developed, yet these lack the capability to detect and analyze the more subtle and important characteristics of the motion of nematodes. There is currently a need to improved methods of assessing the viability and health of parasitic worms. We describe here a system that converts the motion of nematodes through a light-scattering system into an electrical waveform, and allows for reproducible, and wholly non-subjective, assessment of alterations in motion, as well as estimation of the number of nematode worms of different forms and sizes. Here we have used Brugia sp. microfilariae (L1), infective larvae (L3) and adults, together with the free-living nematode Caenorhabditis elegans. The motion of worms in a small (200 ul) volume can be detected, with the presence of immotile worms not interfering with the readings at practical levels (up to at least 500 L1 /200 ul). Alterations in the frequency of parasite movement following the application of the anti-parasitic drugs, (chloroquine and imatinib); the anti-filarial effect of the latter agent is the first demonstrated here for the first time. This system can also be used to estimate the number of parasites, and shortens the time required to estimate parasites numbers, and eliminates the need for microscopes and trained technicians to provide an estimate of microfilarial sample sizes up to 1000 parasites/ml. Alterations in the form of motion of the worms can also be depicted. This new instrument, named a "WiggleTron", offers exciting opportunities to further study nematode biology and to aid drug discovery, as well as contributing to a rapid estimate of parasite numbers in various biological samples.

Dislocation model for aseismic fault slip in the transverse ranges of Southern California

NASA Technical Reports Server (NTRS)

Cheng, A.; Jackson, D. D.; Matsuura, M.

1985-01-01

Geodetic data at a plate boundary can reveal the pattern of subsurface displacements that accompany plate motion. These displacements are modelled as the sum of rigid block motion and the elastic effects of frictional interaction between blocks. The frictional interactions are represented by uniform dislocation on each of several rectangular fault patches. The block velocities and fault parameters are then estimated from geodetic data. Bayesian inversion procedure employs prior estimates based on geological and seismological data. The method is applied to the Transverse Ranges, using prior geological and seismological data and geodetic data from the USGS trilateration networks. Geodetic data imply a displacement rate of about 20 mm/yr across the San Andreas Fault, while the geologic estimates exceed 30 mm/yr. The prior model and the final estimates both imply about 10 mm/yr crustal shortening normal to the trend of the San Andreas Fault. Aseismic fault motion is a major contributor to plate motion. The geodetic data can help to identify faults that are suffering rapid stress accumulation; in the Transverse Ranges those faults are the San Andreas and the Santa Susana.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Global optimization for motion estimation with applications to ultrasound videos of carotid artery plaques

NASA Astrophysics Data System (ADS)

Murillo, Sergio; Pattichis, Marios; Soliz, Peter; Barriga, Simon; Loizou, C. P.; Pattichis, C. S.

2010-03-01

Motion estimation from digital video is an ill-posed problem that requires a regularization approach. Regularization introduces a smoothness constraint that can reduce the resolution of the velocity estimates. The problem is further complicated for ultrasound videos (US), where speckle noise levels can be significant. Motion estimation using optical flow models requires the modification of several parameters to satisfy the optical flow constraint as well as the level of imposed smoothness. Furthermore, except in simulations or mostly unrealistic cases, there is no ground truth to use for validating the velocity estimates. This problem is present in all real video sequences that are used as input to motion estimation algorithms. It is also an open problem in biomedical applications like motion analysis of US of carotid artery (CA) plaques. In this paper, we study the problem of obtaining reliable ultrasound video motion estimates for atherosclerotic plaques for use in clinical diagnosis. A global optimization framework for motion parameter optimization is presented. This framework uses actual carotid artery motions to provide optimal parameter values for a variety of motions and is tested on ten different US videos using two different motion estimation techniques.

Insitu aircraft verification of the quality of satellite cloud winds over oceanic regions

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Skillman, W. C.

1979-01-01

A five year aircraft experiment to verify the quality of satellite cloud winds over oceans using in situ aircraft inertial navigation system wind measurements is presented. The final results show that satellite measured cumulus cloud motions are very good estimators of the cloud base wind for trade wind and subtropical high regions. The average magnitude of the vector differences between the cloud motion and the cloud base wind is given. For cumulus clouds near frontal regions, the cloud motion agreed best with the mean cloud layer wind. For a very limited sample, cirrus cloud motions also most closely followed the mean wind in the cloud layer.

Adaptive correlation filter-based video stabilization without accumulative global motion estimation

NASA Astrophysics Data System (ADS)

Koh, Eunjin; Lee, Chanyong; Jeong, Dong Gil

2014-12-01

We present a digital video stabilization approach that provides both robustness and efficiency for practical applications. In this approach, we adopt a stabilization model that maintains spatio-temporal information of past input frames efficiently and can track original stabilization position. Because of the stabilization model, the proposed method does not need accumulative global motion estimation and can recover the original position even if there is a failure in interframe motion estimation. It can also intelligently overcome the situation of damaged or interrupted video sequences. Moreover, because it is simple and suitable to parallel scheme, we implement it on a commercial field programmable gate array and a graphics processing unit board with compute unified device architecture in a breeze. Experimental results show that the proposed approach is both fast and robust.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

NASA Astrophysics Data System (ADS)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

Nonlinear circuits for naturalistic visual motion estimation

PubMed Central

Fitzgerald, James E; Clark, Damon A

2015-01-01

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator. DOI: http://dx.doi.org/10.7554/eLife.09123.001 PMID:26499494

Undisturbed upright stance control in the elderly: Part 2. Postural-control impairments of elderly fallers.

PubMed

Berger, L; Chuzel, M; Buisson, G; Rougier, P

2005-09-01

A common way of predicting falling risks in elderly people can be to study center of pressure (CP) trajectories during undisturbed upright stance maintenance. By estimating the difference between CP and center of gravity (CG) motions (CP - CGv), one can estimate the neuromuscular activity. The results of this study, which included 34 sedentary elderly persons aged over 75 years (21 fallers and 13 nonfallers), demonstrated significantly increased CGh and CP - CGv motions in both axes for the fallers. In addition, the fallers presented larger CGh motions in the mediolateral axis, suggesting an enlarged loading-unloading mechanism, which could have reflected the adoption of a step-initiating strategy. As highlighted by fractional Brownian motion modeling, the distance covered by the CP - CGv motions before the successive control mechanisms switched was enhanced for the fallers in both axes, therefore increasing the risk that the CG would be outside of the base of support.

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

Broad-Band Analysis of Polar Motion Excitations

NASA Astrophysics Data System (ADS)

Chen, J.

2016-12-01

Earth rotational changes, i.e. polar motion and length-of-day (LOD), are driven by two types of geophysical excitations: 1) mass redistribution within the Earth system, and 2) angular momentum exchange between the solid Earth (more precisely the crust) and other components of the Earth system. Accurate quantification of Earth rotational excitations has been difficult, due to the lack of global-scale observations of mass redistribution and angular momentum exchange. The over 14-years time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) have provided a unique means for quantifying Earth rotational excitations from mass redistribution in different components of the climate system. Comparisons between observed Earth rotational changes and geophysical excitations estimated from GRACE, satellite laser ranging (SLR) and climate models show that GRACE-derived excitations agree remarkably well with polar motion observations over a broad-band of frequencies. GRACE estimates also suggest that accelerated polar region ice melting in recent years and corresponding sea level rise have played an important role in driving long-term polar motion as well. With several estimates of polar motion excitations, it is possible to estimate broad-band noise variance and noise power spectra in each, given reasonable assumptions about noise independence. Results based on GRACE CSR RL05 solutions clearly outperform other estimates with the lowest noise levels over a broad band of frequencies.

Geometric Brownian Motion with Tempered Stable Waiting Times

NASA Astrophysics Data System (ADS)

Gajda, Janusz; Wyłomańska, Agnieszka

2012-08-01

One of the earliest system that was used to asset prices description is Black-Scholes model. It is based on geometric Brownian motion and was used as a tool for pricing various financial instruments. However, when it comes to data description, geometric Brownian motion is not capable to capture many properties of present financial markets. One can name here for instance periods of constant values. Therefore we propose an alternative approach based on subordinated tempered stable geometric Brownian motion which is a combination of the popular geometric Brownian motion and inverse tempered stable subordinator. In this paper we introduce the mentioned process and present its main properties. We propose also the estimation procedure and calibrate the analyzed system to real data.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

PubMed Central

Mishra, Pankaj; Li, Ruijiang; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H.

2014-01-01

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient. PMID:25086523

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Pankaj, E-mail: pankaj.mishra@varian.com; Mak, Raymond H.; Rottmann, Joerg

2014-08-15

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculatedmore » through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient.« less

Quantifying and correcting motion artifacts in MRI

NASA Astrophysics Data System (ADS)

Bones, Philip J.; Maclaren, Julian R.; Millane, Rick P.; Watts, Richard

2006-08-01

Patient motion during magnetic resonance imaging (MRI) can produce significant artifacts in a reconstructed image. Since measurements are made in the spatial frequency domain ('k-space'), rigid-body translational motion results in phase errors in the data samples while rotation causes location errors. A method is presented to detect and correct these errors via a modified sampling strategy, thereby achieving more accurate image reconstruction. The strategy involves sampling vertical and horizontal strips alternately in k-space and employs phase correlation within the overlapping segments to estimate translational motion. An extension, also based on correlation, is employed to estimate rotational motion. Results from simulations with computer-generated phantoms suggest that the algorithm is robust up to realistic noise levels. The work is being extended to physical phantoms. Provided that a reference image is available and the object is of limited extent, it is shown that a measure related to the amount of energy outside the support can be used to objectively compare the severity of motion-induced artifacts.

Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture

PubMed Central

Karatsidis, Angelos; Bellusci, Giovanni; Schepers, H. Martin; de Zee, Mark; Andersen, Michael S.; Veltink, Peter H.

2016-01-01

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory. PMID:28042857

SENSITIVITY OF STRUCTURAL RESPONSE TO GROUND MOTION SOURCE AND SITE PARAMETERS.

USGS Publications Warehouse

Safak, Erdal; Brebbia, C.A.; Cakmak, A.S.; Abdel Ghaffar, A.M.

1985-01-01

Designing structures to withstand earthquakes requires an accurate estimation of the expected ground motion. While engineers use the peak ground acceleration (PGA) to model the strong ground motion, seismologists use physical characteristics of the source and the rupture mechanism, such as fault length, stress drop, shear wave velocity, seismic moment, distance, and attenuation. This study presents a method for calculating response spectra from seismological models using random vibration theory. It then investigates the effect of various source and site parameters on peak response. Calculations are based on a nonstationary stochastic ground motion model, which can incorporate all the parameters both in frequency and time domains. The estimation of the peak response accounts for the effects of the non-stationarity, bandwidth and peak correlations of the response.

Method to estimate center of rigidity using vibration recordings

USGS Publications Warehouse

Safak, Erdal; Çelebi, Mehmet

1990-01-01

A method to estimate the center of rigidity of buildings by using vibration recordings is presented. The method is based on the criterion that the coherence of translational motions with the rotational motion is minimum at the center of rigidity. Since the coherence is a function of frequency, a gross but frequency-independent measure of the coherency is defined as the integral of the coherence function over the frequency. The center of rigidity is determined by minimizing this integral. The formulation is given for two-dimensional motions. Two examples are presented for the method; a rectangular building with ambient-vibration recordings, and a triangular building with earthquake-vibration recordings. Although the examples given are for buildings, the method can be applied to any structure with two-dimensional motions.

Shear-wave velocity compilation for Northridge strong-motion recording sites

USGS Publications Warehouse

Borcherdt, Roger D.; Fumal, Thomas E.

2002-01-01

Borehole and other geotechnical information collected at the strong-motion recording sites of the Northridge earthquake of January 17, 1994 provide an important new basis for the characterization of local site conditions. These geotechnical data, when combined with analysis of strong-motion recordings, provide an empirical basis to evaluate site coefficients used in current versions of US building codes. Shear-wave-velocity estimates to a depth of 30 meters are derived for 176 strong-motion recording sites. The estimates are based on borehole shear-velocity logs, physical property logs, correlations with physical properties and digital geologic maps. Surface-wave velocity measurements and standard penetration data are compiled as additional constraints. These data as compiled from a variety of databases are presented via GIS maps and corresponding tables to facilitate use by other investigators.

An improved multi-paths optimization method for video stabilization

NASA Astrophysics Data System (ADS)

Qin, Tao; Zhong, Sheng

2018-03-01

For video stabilization, the difference between original camera motion path and the optimized one is proportional to the cropping ratio and warping ratio. A good optimized path should preserve the moving tendency of the original one meanwhile the cropping ratio and warping ratio of each frame should be kept in a proper range. In this paper we use an improved warping-based motion representation model, and propose a gauss-based multi-paths optimization method to get a smoothing path and obtain a stabilized video. The proposed video stabilization method consists of two parts: camera motion path estimation and path smoothing. We estimate the perspective transform of adjacent frames according to warping-based motion representation model. It works well on some challenging videos where most previous 2D methods or 3D methods fail for lacking of long features trajectories. The multi-paths optimization method can deal well with parallax, as we calculate the space-time correlation of the adjacent grid, and then a kernel of gauss is used to weigh the motion of adjacent grid. Then the multi-paths are smoothed while minimize the crop ratio and the distortion. We test our method on a large variety of consumer videos, which have casual jitter and parallax, and achieve good results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, H; Chen, Z; Nath, R

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertaintymore » through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the tumor is within the margin or initialize motion compensation if it is out of the margin.« less

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array.

PubMed

Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

2016-03-11

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile's rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm.

Cascade and parallel combination (CPC) of adaptive filters for estimating heart rate during intensive physical exercise from photoplethysmographic signal

PubMed Central

Islam, Mohammad Tariqul; Tanvir Ahmed, Sk.; Zabir, Ishmam; Shahnaz, Celia

2018-01-01

Photoplethysmographic (PPG) signal is getting popularity for monitoring heart rate in wearable devices because of simplicity of construction and low cost of the sensor. The task becomes very difficult due to the presence of various motion artefacts. In this study, an algorithm based on cascade and parallel combination (CPC) of adaptive filters is proposed in order to reduce the effect of motion artefacts. First, preliminary noise reduction is performed by averaging two channel PPG signals. Next in order to reduce the effect of motion artefacts, a cascaded filter structure consisting of three cascaded adaptive filter blocks is developed where three-channel accelerometer signals are used as references to motion artefacts. To further reduce the affect of noise, a scheme based on convex combination of two such cascaded adaptive noise cancelers is introduced, where two widely used adaptive filters namely recursive least squares and least mean squares filters are employed. Heart rates are estimated from the noise reduced PPG signal in spectral domain. Finally, an efficient heart rate tracking algorithm is designed based on the nature of the heart rate variability. The performance of the proposed CPC method is tested on a widely used public database. It is found that the proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach. PMID:29515812

An octahedral shear strain-based measure of SNR for 3D MR elastography

NASA Astrophysics Data System (ADS)

McGarry, M. D. J.; Van Houten, E. E. W.; Perriñez, P. R.; Pattison, A. J.; Weaver, J. B.; Paulsen, K. D.

2011-07-01

A signal-to-noise ratio (SNR) measure based on the octahedral shear strain (the maximum shear strain in any plane for a 3D state of strain) is presented for magnetic resonance elastography (MRE), where motion-based SNR measures are commonly used. The shear strain, γ, is directly related to the shear modulus, μ, through the definition of shear stress, τ = μγ. Therefore, noise in the strain is the important factor in determining the quality of motion data, rather than the noise in the motion. Motion and strain SNR measures were found to be correlated for MRE of gelatin phantoms and the human breast. Analysis of the stiffness distributions of phantoms reconstructed from the measured motion data revealed a threshold for both strain and motion SNR where MRE stiffness estimates match independent mechanical testing. MRE of the feline brain showed significantly less correlation between the two SNR measures. The strain SNR measure had a threshold above which the reconstructed stiffness values were consistent between cases, whereas the motion SNR measure did not provide a useful threshold, primarily due to rigid body motion effects.

EEG-based learning system for online motion sickness level estimation in a dynamic vehicle environment.

PubMed

Lin, Chin-Teng; Tsai, Shu-Fang; Ko, Li-Wei

2013-10-01

Motion sickness is a common experience for many people. Several previous researches indicated that motion sickness has a negative effect on driving performance and sometimes leads to serious traffic accidents because of a decline in a person's ability to maintain self-control. This safety issue has motivated us to find a way to prevent vehicle accidents. Our target was to determine a set of valid motion sickness indicators that would predict the occurrence of a person's motion sickness as soon as possible. A successful method for the early detection of motion sickness will help us to construct a cognitive monitoring system. Such a monitoring system can alert people before they become sick and prevent them from being distracted by various motion sickness symptoms while driving or riding in a car. In our past researches, we investigated the physiological changes that occur during the transition of a passenger's cognitive state using electroencephalography (EEG) power spectrum analysis, and we found that the EEG power responses in the left and right motors, parietal, lateral occipital, and occipital midline brain areas were more highly correlated to subjective sickness levels than other brain areas. In this paper, we propose the use of a self-organizing neural fuzzy inference network (SONFIN) to estimate a driver's/passenger's sickness level based on EEG features that have been extracted online from five motion sickness-related brain areas, while either in real or virtual vehicle environments. The results show that our proposed learning system is capable of extracting a set of valid motion sickness indicators that originated from EEG dynamics, and through SONFIN, a neuro-fuzzy prediction model, we successfully translated the set of motion sickness indicators into motion sickness levels. The overall performance of this proposed EEG-based learning system can achieve an average prediction accuracy of ~82%.

Insensitivity of GNSS to geocenter motion through the network shift approach (Invited)

NASA Astrophysics Data System (ADS)

Rebischung, P.; Altamimi, Z.; Springer, T.

2013-12-01

As a satellite-based technique, GNSS should be sensitive to motions of the Earth's center of mass (CM) with respect to the Earth's crust. In theory, the weekly solutions of the Analysis Centers of the International GNSS Service (IGS ACs) should indeed have the "instantaneous" CM as their origin, and the net translations between the weekly AC frames and a secular frame such as ITRF2008 should thus approximate the non-linear motion of CM with respect to the Earth's center of figure. However, the comparison of the AC translation time series with each other, with SLR geocenter estimates or with geophysical models reveals that this way of observing geocenter motion with GNSS currently gives unreliable results. We addressed the problem of observing geocenter motion with GNSS through this network shift approach from the perspective of collinearity (or multicollinearity) among the parameters of a least-squares regression. A collinearity diagnosis, based on the notion of variance inflation factor, was therefore developed and allows handling several peculiarities of the GNSS geocenter determination problem. Its application reveals that the determination of all three components of geocenter motion with GNSS suffers from serious collinearity issues, with a comparable level as in the problem of determining the terrestrial scale simultaneously with the GNSS satellite phase center offsets. We show that the inability of current GNSS, as opposed to Satellite Laser Ranging (SLR), to properly sense geocenter motion is mostly explained by the estimation, in the GNSS case, of epoch-wise station and satellite clock offsets simultaneously with tropospheric parameters. The empirical satellite accelerations, as estimated by most IGS ACs, slightly amplify the collinearity of the Z geocenter coordinate, but their role remains secondary.

High resolution reconstructions of Southwest Indian Ridge plate motions during the Neogene: Comparison to GPS estimates and implications for global plate motion estimates

NASA Astrophysics Data System (ADS)

DeMets, C.; Merkouriev, S.; Sauter, D.; Calais, E.

2013-12-01

Plate kinematic data from the slow-spreading Southwest Indian Ridge (SWIR) are the primary source of information about relative movements between Antarctica and Africa over geologic time and are critical for linking the movements of plates in the Atlantic and Indian Ocean basins. We describe the first high-resolution model of SWIR plate kinematics from the present to 20 Ma, consisting of rotations based on 21 magnetic reversals with ~1 million-year spacing. The new rotations, which are derived from 4822 identifications of magnetic reversals C1n to C6no and 6000 crossings of 21 fracture zones and transform faults, describe in detail the ultra-slow motions of the Nubia, Lwandle, and Somalia plates north of the SWIR relative to the Antarctic plate. A search for the Nubia-Lwandle-Antarctic triple junction with all data since C5n.2 (11.0 Ma) gives a best location at the Andrew Bain transform fault (~32E), in accord with previous work. Plate kinematic data from the SWIR east of the Andrew Bain fracture zone support the existence of the previously proposed Lwandle plate at high confidence level. The likely diffuse Lwandle-Somalia plate boundary north of the SWIR is however only loosely constrained to 45E-52E. After calibrating the new rotations for the biasing effects of finite-width magnetic polarity transition zones (i.e. outward displacement), the new rotations reveal that SWIR plate motion has remained steady from the present back to 7.5 Ma, but was modestly faster (~25%) from 19.6 Ma to 7.5 Ma. GPS estimates of present SWIR plate motions based on more than 100 continuous GPS sites on the Antarctic, Nubia, and Somalia plates are remarkably consistent with SWIR velocities determined with the new geological reconstructions. The superb agreement between the two independent plate motion estimates validates both sets of estimates and our calibration for outward displacement. Implications of the new estimates, including evidence for anomalously wide outward displacement across parts of the SWIR, will be discussed

A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons

PubMed Central

Kim, HyungGoo R.; Pitkow, Xaq; Angelaki, Dora E.

2016-01-01

Sensory input reflects events that occur in the environment, but multiple events may be confounded in sensory signals. For example, under many natural viewing conditions, retinal image motion reflects some combination of self-motion and movement of objects in the world. To estimate one stimulus event and ignore others, the brain can perform marginalization operations, but the neural bases of these operations are poorly understood. Using computational modeling, we examine how multisensory signals may be processed to estimate the direction of self-motion (i.e., heading) and to marginalize out effects of object motion. Multisensory neurons represent heading based on both visual and vestibular inputs and come in two basic types: “congruent” and “opposite” cells. Congruent cells have matched heading tuning for visual and vestibular cues and have been linked to perceptual benefits of cue integration during heading discrimination. Opposite cells have mismatched visual and vestibular heading preferences and are ill-suited for cue integration. We show that decoding a mixed population of congruent and opposite cells substantially reduces errors in heading estimation caused by object motion. In addition, we present a general formulation of an optimal linear decoding scheme that approximates marginalization and can be implemented biologically by simple reinforcement learning mechanisms. We also show that neural response correlations induced by task-irrelevant variables may greatly exceed intrinsic noise correlations. Overall, our findings suggest a general computational strategy by which neurons with mismatched tuning for two different sensory cues may be decoded to perform marginalization operations that dissociate possible causes of sensory inputs. PMID:27334948

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Gated Sensor Fusion: A way to Improve the Precision of Ambulatory Human Body Motion Estimation.

PubMed

Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, Gonzalo

2014-01-01

Human body motion is usually variable in terms of intensity and, therefore, any Inertial Measurement Unit attached to a subject will measure both low and high angular rate and accelerations. This can be a problem for the accuracy of orientation estimation algorithms based on adaptive filters such as the Kalman filter, since both the variances of the process noise and the measurement noise are set at the beginning of the algorithm and remain constant during its execution. Setting fixed noise parameters burdens the adaptation capability of the filter if the intensity of the motion changes rapidly. In this work we present a conjoint novel algorithm which uses a motion intensity detector to dynamically vary the noise statistical parameters of different approaches of the Kalman filter. Results show that the precision of the estimated orientation in terms of the RMSE can be improved up to 29% with respect to the standard fixed-parameters approaches.

Estimation of multiple accelerated motions using chirp-Fourier transform and clustering.

PubMed

Alexiadis, Dimitrios S; Sergiadis, George D

2007-01-01

Motion estimation in the spatiotemporal domain has been extensively studied and many methodologies have been proposed, which, however, cannot handle both time-varying and multiple motions. Extending previously published ideas, we present an efficient method for estimating multiple, linearly time-varying motions. It is shown that the estimation of accelerated motions is equivalent to the parameter estimation of superpositioned chirp signals. From this viewpoint, one can exploit established signal processing tools such as the chirp-Fourier transform. It is shown that accelerated motion results in energy concentration along planes in the 4-D space: spatial frequencies-temporal frequency-chirp rate. Using fuzzy c-planes clustering, we estimate the plane/motion parameters. The effectiveness of our method is verified on both synthetic as well as real sequences and its advantages are highlighted.

Marker-free motion correction in weight-bearing cone-beam CT of the knee joint.

PubMed

Berger, M; Müller, K; Aichert, A; Unberath, M; Thies, J; Choi, J-H; Fahrig, R; Maier, A

2016-03-01

To allow for a purely image-based motion estimation and compensation in weight-bearing cone-beam computed tomography of the knee joint. Weight-bearing imaging of the knee joint in a standing position poses additional requirements for the image reconstruction algorithm. In contrast to supine scans, patient motion needs to be estimated and compensated. The authors propose a method that is based on 2D/3D registration of left and right femur and tibia segmented from a prior, motion-free reconstruction acquired in supine position. Each segmented bone is first roughly aligned to the motion-corrupted reconstruction of a scan in standing or squatting position. Subsequently, a rigid 2D/3D registration is performed for each bone to each of K projection images, estimating 6 × 4 × K motion parameters. The motion of individual bones is combined into global motion fields using thin-plate-spline extrapolation. These can be incorporated into a motion-compensated reconstruction in the backprojection step. The authors performed visual and quantitative comparisons between a state-of-the-art marker-based (MB) method and two variants of the proposed method using gradient correlation (GC) and normalized gradient information (NGI) as similarity measure for the 2D/3D registration. The authors evaluated their method on four acquisitions under different squatting positions of the same patient. All methods showed substantial improvement in image quality compared to the uncorrected reconstructions. Compared to NGI and MB, the GC method showed increased streaking artifacts due to misregistrations in lateral projection images. NGI and MB showed comparable image quality at the bone regions. Because the markers are attached to the skin, the MB method performed better at the surface of the legs where the authors observed slight streaking of the NGI and GC methods. For a quantitative evaluation, the authors computed the universal quality index (UQI) for all bone regions with respect to the motion-free reconstruction. The authors quantitative evaluation over regions around the bones yielded a mean UQI of 18.4 for no correction, 53.3 and 56.1 for the proposed method using GC and NGI, respectively, and 53.7 for the MB reference approach. In contrast to the authors registration-based corrections, the MB reference method caused slight nonrigid deformations at bone outlines when compared to a motion-free reference scan. The authors showed that their method based on the NGI similarity measure yields reconstruction quality close to the MB reference method. In contrast to the MB method, the proposed method does not require any preparation prior to the examination which will improve the clinical workflow and patient comfort. Further, the authors found that the MB method causes small, nonrigid deformations at the bone outline which indicates that markers may not accurately reflect the internal motion close to the knee joint. Therefore, the authors believe that the proposed method is a promising alternative to MB motion management.

Marker-free motion correction in weight-bearing cone-beam CT of the knee joint

PubMed Central

Berger, M.; Müller, K.; Aichert, A.; Unberath, M.; Thies, J.; Choi, J.-H.; Fahrig, R.; Maier, A.

2016-01-01

Purpose: To allow for a purely image-based motion estimation and compensation in weight-bearing cone-beam computed tomography of the knee joint. Methods: Weight-bearing imaging of the knee joint in a standing position poses additional requirements for the image reconstruction algorithm. In contrast to supine scans, patient motion needs to be estimated and compensated. The authors propose a method that is based on 2D/3D registration of left and right femur and tibia segmented from a prior, motion-free reconstruction acquired in supine position. Each segmented bone is first roughly aligned to the motion-corrupted reconstruction of a scan in standing or squatting position. Subsequently, a rigid 2D/3D registration is performed for each bone to each of K projection images, estimating 6 × 4 × K motion parameters. The motion of individual bones is combined into global motion fields using thin-plate-spline extrapolation. These can be incorporated into a motion-compensated reconstruction in the backprojection step. The authors performed visual and quantitative comparisons between a state-of-the-art marker-based (MB) method and two variants of the proposed method using gradient correlation (GC) and normalized gradient information (NGI) as similarity measure for the 2D/3D registration. Results: The authors evaluated their method on four acquisitions under different squatting positions of the same patient. All methods showed substantial improvement in image quality compared to the uncorrected reconstructions. Compared to NGI and MB, the GC method showed increased streaking artifacts due to misregistrations in lateral projection images. NGI and MB showed comparable image quality at the bone regions. Because the markers are attached to the skin, the MB method performed better at the surface of the legs where the authors observed slight streaking of the NGI and GC methods. For a quantitative evaluation, the authors computed the universal quality index (UQI) for all bone regions with respect to the motion-free reconstruction. The authors quantitative evaluation over regions around the bones yielded a mean UQI of 18.4 for no correction, 53.3 and 56.1 for the proposed method using GC and NGI, respectively, and 53.7 for the MB reference approach. In contrast to the authors registration-based corrections, the MB reference method caused slight nonrigid deformations at bone outlines when compared to a motion-free reference scan. Conclusions: The authors showed that their method based on the NGI similarity measure yields reconstruction quality close to the MB reference method. In contrast to the MB method, the proposed method does not require any preparation prior to the examination which will improve the clinical workflow and patient comfort. Further, the authors found that the MB method causes small, nonrigid deformations at the bone outline which indicates that markers may not accurately reflect the internal motion close to the knee joint. Therefore, the authors believe that the proposed method is a promising alternative to MB motion management. PMID:26936708

A System for Video Surveillance and Monitoring CMU VSAM Final Report

DTIC Science & Technology

1999-11-30

motion-based skeletonization, neural network , spatio-temporal salience Patterns inside image chips, spurious motion rejection, model -based... network of sensors with respect to the model coordinate system, computation of 3D geolocation estimates, and graphical display of object hypotheses...rithms have been developed. The first uses view dependent visual properties to train a neural network classifier to recognize four classes: single

Practical Applications for Earthquake Scenarios Using ShakeMap

NASA Astrophysics Data System (ADS)

Wald, D. J.; Worden, B.; Quitoriano, V.; Goltz, J.

2001-12-01

In planning and coordinating emergency response, utilities, local government, and other organizations are best served by conducting training exercises based on realistic earthquake situations-ones that they are most likely to face. Scenario earthquakes can fill this role; they can be generated for any geologically plausible earthquake or for actual historic earthquakes. ShakeMap Web pages now display selected earthquake scenarios (www.trinet.org/shake/archive/scenario/html) and more events will be added as they are requested and produced. We will discuss the methodology and provide practical examples where these scenarios are used directly for risk reduction. Given a selected event, we have developed tools to make it relatively easy to generate a ShakeMap earthquake scenario using the following steps: 1) Assume a particular fault or fault segment will (or did) rupture over a certain length, 2) Determine the magnitude of the earthquake based on assumed rupture dimensions, 3) Estimate the ground shaking at all locations in the chosen area around the fault, and 4) Represent these motions visually by producing ShakeMaps and generating ground motion input for loss estimation modeling (e.g., FEMA's HAZUS). At present, ground motions are estimated using empirical attenuation relationships to estimate peak ground motions on rock conditions. We then correct the amplitude at that location based on the local site soil (NEHRP) conditions as we do in the general ShakeMap interpolation scheme. Finiteness is included explicitly, but directivity enters only through the empirical relations. Although current ShakeMap earthquake scenarios are empirically based, substantial improvements in numerical ground motion modeling have been made in recent years. However, loss estimation tools, HAZUS for example, typically require relatively high frequency (3 Hz) input for predicting losses, above the range of frequencies successfully modeled to date. Achieving full-synthetic ground motion estimates that will substantially improve over empirical relations at these frequencies will require developing cost-effective numerical tools for proper theoretical inclusion of known complex ground motion effects. Current efforts underway must continue in order to obtain site, basin, and deeper crustal structure, and to characterize and test 3D earth models (including attenuation and nonlinearity). In contrast, longer period synthetics (>2 sec) are currently being generated in a deterministic fashion to include 3D and shallow site effects, an improvement on empirical estimates alone. As progress is made, we will naturally incorporate such advances into the ShakeMap scenario earthquake and processing methodology. Our scenarios are currently used heavily in emergency response planning and loss estimation. Primary users include city, county, state and federal government agencies (e.g., the California Office of Emergency Services, FEMA, the County of Los Angeles) as well as emergency response planners and managers for utilities, businesses, and other large organizations. We have found the scenarios are also of fundamental interest to many in the media and the general community interested in the nature of the ground shaking likely experienced in past earthquakes as well as effects of rupture on known faults in the future.

Motion compensation using origin ensembles in awake small animal positron emission tomography

NASA Astrophysics Data System (ADS)

Gillam, John E.; Angelis, Georgios I.; Kyme, Andre Z.; Meikle, Steven R.

2017-02-01

In emission tomographic imaging, the stochastic origin ensembles algorithm provides unique information regarding the detected counts given the measured data. Precision in both voxel and region-wise parameters may be determined for a single data set based on the posterior distribution of the count density allowing uncertainty estimates to be allocated to quantitative measures. Uncertainty estimates are of particular importance in awake animal neurological and behavioral studies for which head motion, unique for each acquired data set, perturbs the measured data. Motion compensation can be conducted when rigid head pose is measured during the scan. However, errors in pose measurements used for compensation can degrade the data and hence quantitative outcomes. In this investigation motion compensation and detector resolution models were incorporated into the basic origin ensembles algorithm and an efficient approach to computation was developed. The approach was validated against maximum liklihood—expectation maximisation and tested using simulated data. The resultant algorithm was then used to analyse quantitative uncertainty in regional activity estimates arising from changes in pose measurement precision. Finally, the posterior covariance acquired from a single data set was used to describe correlations between regions of interest providing information about pose measurement precision that may be useful in system analysis and design. The investigation demonstrates the use of origin ensembles as a powerful framework for evaluating statistical uncertainty of voxel and regional estimates. While in this investigation rigid motion was considered in the context of awake animal PET, the extension to arbitrary motion may provide clinical utility where respiratory or cardiac motion perturb the measured data.

Dynamic Estimation of Rigid Motion from Perspective Views via Recursive Identification of Exterior Differential Systems with Parameters on a Topological Manifold

DTIC Science & Technology

1994-02-15

0. Faugeras. Three dimensional vision, a geometric viewpoint. MIT Press, 1993. [19] 0 . D. Faugeras and S. Maybank . Motion from point mathces...multiplicity of solutions. Int. J. of Computer Vision, 1990. 1201 0.D. Faugeras, Q.T. Luong, and S.J. Maybank . Camera self-calibration: theory and...Kalrnan filter-based algorithms for estimating depth from image sequences. Int. J. of computer vision, 1989. [41] S. Maybank . Theory of

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy

NASA Astrophysics Data System (ADS)

Stemkens, Bjorn; Tijssen, Rob H. N.; de Senneville, Baudouin Denis; Lagendijk, Jan J. W.; van den Berg, Cornelis A. T.

2016-07-01

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy.

PubMed

Stemkens, Bjorn; Tijssen, Rob H N; de Senneville, Baudouin Denis; Lagendijk, Jan J W; van den Berg, Cornelis A T

2016-07-21

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

Relationships of earthquakes (and earthquake-associated mass movements) and polar motion as determined by Kalman filtered, Very-Long-Baseline-Interferometry

NASA Technical Reports Server (NTRS)

Preisig, Joseph Richard Mark

1988-01-01

A Kalman filter was designed to yield optimal estimates of geophysical parameters from Very Long Baseline Interferometry (VLBI) group delay data. The geophysical parameters are the polar motion components, adjustments to nutation in obliquity and longitude, and a change in the length of day parameter. The VLBI clock (and clock rate) parameters and atmospheric zenith delay parameters are estimated simultaneously. Filter background is explained. The IRIS (International Radio Interferometric Surveying) VLBI data are Kalman filtered. The resulting polar motion estimates are examined. There are polar motion signatures at the times of three large earthquakes occurring in 1984 to 1986: Mexico, 19 September, 1985 (Magnitude M sub s = 8.1); Chile, 3 March, 1985 (M sub s = 7.8); and Taiwan, 14 November, 1986 (M sub s = 7.8). Breaks in polar motion occurring about 20 days after the earthquakes appear to correlate well with the onset of increased regional seismic activity and a return to more normal seismicity (respectively). While the contribution of these three earthquakes to polar motion excitations is small, the cumulative excitation due to earthquakes, or seismic phenomena over a Chandler wobble damping period may be significant. Mechanisms for polar motion excitation due to solid earth phenomena are examined. Excitation functions are computed, but the data spans are too short to draw conclusions based on these data.

Gravity Compensation Method for Combined Accelerometer and Gyro Sensors Used in Cardiac Motion Measurements.

PubMed

Krogh, Magnus Reinsfelt; Nghiem, Giang M; Halvorsen, Per Steinar; Elle, Ole Jakob; Grymyr, Ole-Johannes; Hoff, Lars; Remme, Espen W

2017-05-01

A miniaturized accelerometer fixed to the heart can be used for monitoring of cardiac function. However, an accelerometer cannot differentiate between acceleration caused by motion and acceleration due to gravity. The accuracy of motion measurements is therefore dependent on how well the gravity component can be estimated and filtered from the measured signal. In this study we propose a new method for estimating the gravity, based on strapdown inertial navigation, using a combined accelerometer and gyro. The gyro was used to estimate the orientation of the gravity field and thereby remove it. We compared this method with two previously proposed gravity filtering methods in three experimental models using: (1) in silico computer simulated heart motion; (2) robot mimicked heart motion; and (3) in vivo measured motion on the heart in an animal model. The new method correlated excellently with the reference (r 2  > 0.93) and had a deviation from reference peak systolic displacement (6.3 ± 3.9 mm) below 0.2 ± 0.5 mm for the robot experiment model. The new method performed significantly better than the two previously proposed methods (p < 0.001). The results show that the proposed method using gyro can measure cardiac motion with high accuracy and performs better than existing methods for filtering the gravity component from the accelerometer signal.

90Y Liver Radioembolization Imaging Using Amplitude-Based Gated PET/CT.

PubMed

Osborne, Dustin R; Acuff, Shelley; Neveu, Melissa; Kaman, Austin; Syed, Mumtaz; Fu, Yitong

2017-05-01

The usage of PET/CT to monitor patients with hepatocellular carcinoma following Y radioembolization has increased; however, image quality is often poor because of low count efficiency and respiratory motion. Motion can be corrected using gating techniques but at the expense of additional image noise. Amplitude-based gating has been shown to improve quantification in FDG PET, but few have used this technique in Y liver imaging. The patients shown in this work indicate that amplitude-based gating can be used in Y PET/CT liver imaging to provide motion-corrected images with higher estimates of activity concentration that may improve posttherapy dosimetry.

Bilayer segmentation of webcam videos using tree-based classifiers.

PubMed

Yin, Pei; Criminisi, Antonio; Winn, John; Essa, Irfan

2011-01-01

This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The frames are segmented into foreground and background layers that comprise a subject (participant) and other objects and individuals. The algorithm produces correct segmentations even in the presence of large background motion with a nearly stationary foreground. This research makes three key contributions: First, we introduce a novel motion representation, referred to as "motons," inspired by research in object recognition. Second, we propose estimating the segmentation likelihood from the spatial context of motion. The estimation is efficiently learned by random forests. Third, we introduce a general taxonomy of tree-based classifiers that facilitates both theoretical and experimental comparisons of several known classification algorithms and generates new ones. In our bilayer segmentation algorithm, diverse visual cues such as motion, motion context, color, contrast, and spatial priors are fused by means of a conditional random field (CRF) model. Segmentation is then achieved by binary min-cut. Experiments on many sequences of our videochat application demonstrate that our algorithm, which requires no initialization, is effective in a variety of scenes, and the segmentation results are comparable to those obtained by stereo systems.

Seismic evidence for convection-driven motion of the North American plate.

PubMed

Eaton, David W; Frederiksen, Andrew

2007-03-22

Since the discovery of plate tectonics, the relative importance of driving forces of plate motion has been debated. Resolution of this issue has been hindered by uncertainties in estimates of basal traction, which controls the coupling between lithospheric plates and underlying mantle convection. Hotspot tracks preserve records of past plate motion and provide markers with which the relative motion between a plate's surface and underlying mantle regions may be examined. Here we show that the 115-140-Myr surface expression of the Great Meteor hotspot track in eastern North America is misaligned with respect to its location at 200 km depth, as inferred from plate-reconstruction models and seismic tomographic studies. The misalignment increases with age and is consistent with westward displacement of the base of the plate relative to its surface, at an average rate of 3.8 +/- 1.8 mm yr(-1). Here age-constrained 'piercing points' have enabled direct estimation of relative motion between the surface and underside of a plate. The relative displacement of the base is approximately parallel to seismic fast axes and calculated mantle flow, suggesting that asthenospheric flow may be deforming the lithospheric keel and exerting a driving force on this part of the North American plate.

Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments

PubMed Central

Sun, Tongyang; Duan, Lihong; Wang, Yulong

2017-01-01

The hemiplegic rehabilitation state diagnosing performed by therapists can be biased due to their subjective experience, which may deteriorate the rehabilitation effect. In order to improve this situation, a quantitative evaluation is proposed. Though many motion analysis systems are available, they are too complicated for practical application by therapists. In this paper, a method for detecting the motion of human lower limbs including all degrees of freedom (DOFs) via the inertial sensors is proposed, which permits analyzing the patient's motion ability. This method is applicable to arbitrary walking directions and tracks of persons under study, and its results are unbiased, as compared to therapist qualitative estimations. Using the simplified mathematical model of a human body, the rotation angles for each lower limb joint are calculated from the input signals acquired by the inertial sensors. Finally, the rotation angle versus joint displacement curves are constructed, and the estimated values of joint motion angle and motion ability are obtained. The experimental verification of the proposed motion detection and analysis method was performed, which proved that it can efficiently detect the differences between motion behaviors of disabled and healthy persons and provide a reliable quantitative evaluation of the rehabilitation state. PMID:29065575

Three-dimensional ultrasound strain imaging of skeletal muscles

NASA Astrophysics Data System (ADS)

Gijsbertse, K.; Sprengers, A. M. J.; Nillesen, M. M.; Hansen, H. H. G.; Lopata, R. G. P.; Verdonschot, N.; de Korte, C. L.

2017-01-01

In this study, a multi-dimensional strain estimation method is presented to assess local relative deformation in three orthogonal directions in 3D space of skeletal muscles during voluntary contractions. A rigid translation and compressive deformation of a block phantom, that mimics muscle contraction, is used as experimental validation of the 3D technique and to compare its performance with respect to a 2D based technique. Axial, lateral and (in case of 3D) elevational displacements are estimated using a cross-correlation based displacement estimation algorithm. After transformation of the displacements to a Cartesian coordinate system, strain is derived using a least-squares strain estimator. The performance of both methods is compared by calculating the root-mean-squared error of the estimated displacements with the calculated theoretical displacements of the phantom experiments. We observe that the 3D technique delivers more accurate displacement estimations compared to the 2D technique, especially in the translation experiment where out-of-plane motion hampers the 2D technique. In vivo application of the 3D technique in the musculus vastus intermedius shows good resemblance between measured strain and the force pattern. Similarity of the strain curves of repetitive measurements indicates the reproducibility of voluntary contractions. These results indicate that 3D ultrasound is a valuable imaging tool to quantify complex tissue motion, especially when there is motion in three directions, which results in out-of-plane errors for 2D techniques.

Estimating satellite pose and motion parameters using a novelty filter and neural net tracker

NASA Technical Reports Server (NTRS)

Lee, Andrew J.; Casasent, David; Vermeulen, Pieter; Barnard, Etienne

1989-01-01

A system for determining the position, orientation and motion of a satellite with respect to a robotic spacecraft using video data is advanced. This system utilizes two levels of pose and motion estimation: an initial system which provides coarse estimates of pose and motion, and a second system which uses the coarse estimates and further processing to provide finer pose and motion estimates. The present paper emphasizes the initial coarse pose and motion estimation sybsystem. This subsystem utilizes novelty detection and filtering for locating novel parts and a neural net tracker to track these parts over time. Results of using this system on a sequence of images of a spin stabilized satellite are presented.

Estimation of vulnerability functions based on a global earthquake damage database

NASA Astrophysics Data System (ADS)

Spence, R. J. S.; Coburn, A. W.; Ruffle, S. J.

2009-04-01

Developing a better approach to the estimation of future earthquake losses, and in particular to the understanding of the inherent uncertainties in loss models, is vital to confidence in modelling potential losses in insurance or for mitigation. For most areas of the world there is currently insufficient knowledge of the current building stock for vulnerability estimates to be based on calculations of structural performance. In such areas, the most reliable basis for estimating vulnerability is performance of the building stock in past earthquakes, using damage databases, and comparison with consistent estimates of ground motion. This paper will present a new approach to the estimation of vulnerabilities using the recently launched Cambridge University Damage Database (CUEDD). CUEDD is based on data assembled by the Martin Centre at Cambridge University since 1980, complemented by other more-recently published and some unpublished data. The database assembles in a single, organised, expandable and web-accessible database, summary information on worldwide post-earthquake building damage surveys which have been carried out since the 1960's. Currently it contains data on the performance of more than 750,000 individual buildings, in 200 surveys following 40 separate earthquakes. The database includes building typologies, damage levels, location of each survey. It is mounted on a GIS mapping system and links to the USGS Shakemaps of each earthquake which enables the macroseismic intensity and other ground motion parameters to be defined for each survey and location. Fields of data for each building damage survey include: · Basic earthquake data and its sources · Details of the survey location and intensity and other ground motion observations or assignments at that location · Building and damage level classification, and tabulated damage survey results · Photos showing typical examples of damage. In future planned extensions of the database information on human casualties will also be assembled. The database also contains analytical tools enabling data from similar locations, building classes or ground motion levels to be assembled and thus vulnerability relationships derived for any chosen ground motion parameter, for a given class of building, and for particular countries or regions. The paper presents examples of vulnerability relationships for particular classes of buildings and regions of the world, together with the estimated uncertainty ranges. It will discuss the applicability of such vulnerability functions in earthquake loss assessment for insurance purposes or for earthquake risk mitigation.

WE-G-BRD-01: A Data-Driven 4D-MRI Motion Model to Estimate Full Field-Of-View Abdominal Motion From 2D Image Navigators During MR-Linac Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stemkens, B; Tijssen, RHN; Denis de Senneville, B Denis

2015-06-15

Purpose: To estimate full field-of-view abdominal respiratory motion from fast 2D image navigators using a 4D-MRI based motion model. This will allow for radiation dose accumulation mapping during MR-Linac treatment. Methods: Experiments were conducted on a Philips Ingenia 1.5T MRI. First, a retrospectively ordered 4D-MRI was constructed using 3D transient-bSSFP with radial in-plane sampling. Motion fields were calculated through 3D non-rigid registration. From these motion fields a PCA-based abdominal motion model was constructed and used to warp a 3D reference volume to fast 2D cine-MR image navigators that can be used for real-time tracking. To test this procedure, a time-seriesmore » consisting of two interleaved orthogonal slices (sagittal and coronal), positioned on the pancreas or kidneys, were acquired for 1m38s (dynamic scan-time=0.196ms), during normal, shallow, or deep breathing. The coronal slices were used to update the optimal weights for the first two PCA components, in order to warp the 3D reference image and construct a dynamic 4D-MRI time-series. The interleaved sagittal slices served as an independent measure to test the model’s accuracy and fit. Spatial maps of the root-mean-squared error (RMSE) and histograms of the motion differences within the pancreas and kidneys were used to evaluate the method. Results: Cranio-caudal motion was accurately calculated within the pancreas using the model for normal and shallow breathing with an RMSE of 1.6mm and 1.5mm and a histogram median and standard deviation below 0.2 and 1.7mm, respectively. For deep-breathing an underestimation of the inhale amplitude was observed (RMSE=4.1mm). Respiratory-induced antero-posterior and lateral motion were correctly mapped (RMSE=0.6/0.5mm). Kidney motion demonstrated good motion estimation with RMSE-values of 0.95 and 2.4mm for the right and left kidney, respectively. Conclusion: We have demonstrated a method that can calculate dynamic 3D abdominal motion in a large volume, while acquiring real-time cine-MR images for MR-guided radiotherapy.« less

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Feasibility assessment of yttrium-90 liver radioembolization imaging using amplitude-based gated PET/CT

PubMed Central

Acuff, Shelley N.; Neveu, Melissa L.; Syed, Mumtaz; Kaman, Austin D.; Fu, Yitong

2018-01-01

Purpose The usage of PET/computed tomography (CT) to monitor hepatocellular carcinoma patients following yttrium-90 (90Y) radioembolization has increased. Respiratory motion causes liver movement, which can be corrected using gating techniques at the expense of added noise. This work examines the use of amplitude-based gating on 90Y-PET/CT and its potential impact on diagnostic integrity. Patients and methods Patients were imaged using PET/CT following 90Y radioembolization. A respiratory band was used to collect respiratory cycle data. Patient data were processed as both standard and motion-corrected images. Regions of interest were drawn and compared using three methods. Activity concentrations were calculated and converted into dose estimates using previously determined and published scaling factors. Diagnostic assessments were performed using a binary scale created from published 90Y-PET/CT image interpretation guidelines. Results Estimates of radiation dose were increased (P<0.05) when using amplitude-gating methods with 90Y PET/CT imaging. Motion-corrected images show increased noise, but the diagnostic determination of success, using the Kao criteria, did not change between static and motion-corrected data. Conclusion Amplitude-gated PET/CT following 90Y radioembolization is feasible and may improve 90Y dose estimates while maintaining diagnostic assessment integrity. PMID:29351124

Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

PubMed

Szczęsna, Agnieszka; Pruszowski, Przemysław

2016-01-01

Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

Myocardial motion estimation of tagged cardiac magnetic resonance images using tag motion constraints and multi-level b-splines interpolation.

PubMed

Liu, Hong; Yan, Meng; Song, Enmin; Wang, Jie; Wang, Qian; Jin, Renchao; Jin, Lianghai; Hung, Chih-Cheng

2016-05-01

Myocardial motion estimation of tagged cardiac magnetic resonance (TCMR) images is of great significance in clinical diagnosis and the treatment of heart disease. Currently, the harmonic phase analysis method (HARP) and the local sine-wave modeling method (SinMod) have been proven as two state-of-the-art motion estimation methods for TCMR images, since they can directly obtain the inter-frame motion displacement vector field (MDVF) with high accuracy and fast speed. By comparison, SinMod has better performance over HARP in terms of displacement detection, noise and artifacts reduction. However, the SinMod method has some drawbacks: 1) it is unable to estimate local displacements larger than half of the tag spacing; 2) it has observable errors in tracking of tag motion; and 3) the estimated MDVF usually has large local errors. To overcome these problems, we present a novel motion estimation method in this study. The proposed method tracks the motion of tags and then estimates the dense MDVF by using the interpolation. In this new method, a parameter estimation procedure for global motion is applied to match tag intersections between different frames, ensuring specific kinds of large displacements being correctly estimated. In addition, a strategy of tag motion constraints is applied to eliminate most of errors produced by inter-frame tracking of tags and the multi-level b-splines approximation algorithm is utilized, so as to enhance the local continuity and accuracy of the final MDVF. In the estimation of the motion displacement, our proposed method can obtain a more accurate MDVF compared with the SinMod method and our method can overcome the drawbacks of the SinMod method. However, the motion estimation accuracy of our method depends on the accuracy of tag lines detection and our method has a higher time complexity. Copyright © 2015 Elsevier Inc. All rights reserved.

Inertial Motion Capture Costume Design Study

PubMed Central

Szczęsna, Agnieszka; Skurowski, Przemysław; Lach, Ewa; Pruszowski, Przemysław; Pęszor, Damian; Paszkuta, Marcin; Słupik, Janusz; Lebek, Kamil; Janiak, Mateusz; Polański, Andrzej; Wojciechowski, Konrad

2017-01-01

The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results. PMID:28304337

High-resolution estimates of Southwest Indian Ridge plate motions, 20 Ma to present

NASA Astrophysics Data System (ADS)

DeMets, C.; Merkouriev, S.; Sauter, D.

2015-12-01

We present the first estimates of Southwest Indian Ridge (SWIR) plate motions at high temporal resolution during the Quaternary and Neogene based on nearly 5000 crossings of 21 magnetic reversals out to C6no (19.72 Ma) and the digitized traces of 17 fracture zones and transform faults. Our reconstructions of this slow-spreading mid-ocean ridge reveal several unexpected results with notable implications for regional and global plate reconstructions since 20 Ma. Extrapolations of seafloor opening distances to zero-age seafloor based on reconstructions of reversals C1n (0.78 Ma) through C3n.4 (5.2 Ma) reveal evidence for surprisingly large outward displacement of 5 ± 1 km west of 32°E, where motion between the Nubia and Antarctic plates occurs, but 2 ± 1 km east of 32°E, more typical of most mid-ocean ridges. Newly estimated SWIR seafloor spreading rates are up to 15 per cent slower everywhere along the ridge than previous estimates. Reconstructions of the numerous observations for times back to 11 Ma confirm the existence of the hypothesized Lwandle plate at high confidence level and indicate that the Lwandle plate's western and eastern boundaries respectively intersect the ridge near the Andrew Bain transform fault complex at 32°E and between ˜45°E and 52°E, in accord with previous results. The Nubia-Antarctic, Lwandle-Antarctic and Somalia-Antarctic rotation sequences that best fit many magnetic reversal, fracture zone and transform fault crossings define previously unknown changes in the Neogene motions of all three plate pairs, consisting of ˜20 per cent slowdowns in their spreading rates at 7.2^{+0.9 }_{ -1.4} Ma if we enforce a simultaneous change in motion everywhere along the SWIR and gradual 3°-7° anticlockwise rotations of the relative slip directions. We apply trans-dimensional Bayesian analysis to our noisy, best-fitting rotation sequences in order to estimate less-noisy rotation sequences suitable for use in future global plate reconstructions and geodynamic studies. Notably, our new Nubia-Antarctic reconstruction of C5n.2 (11.0 Ma) predicts 20 per cent less opening than do two previous estimates, with important implications for motion that is estimated between the Nubia and Somalia plates. A Nubia-Somalia rotation determined from our Nubia-Antarctic and Somalia-Antarctic plate rotations for C5n.2 (11.0 Ma) predicts cumulative opening of 45 ± 4 km (95 per cent uncertainty) across the northernmost East Africa rift since 11.0 Ma, 70 per cent less than a recent 129 ± 62 km opening estimate based on a now-superseded interpretation of Anomaly 5 along the western portion of the SWIR.

Linear Extended State Observer-Based Motion Synchronization Control for Hybrid Actuation System of More Electric Aircraft.

PubMed

Wang, Xingjian; Liao, Rui; Shi, Cun; Wang, Shaoping

2017-10-25

Moving towards the more electric aircraft (MEA), a hybrid actuator configuration provides an opportunity to introduce electromechanical actuator (EMA) into primary flight control. In the hybrid actuation system (HAS), an electro-hydraulic servo actuator (EHSA) and an EMA operate on the same control surface. In order to solve force fighting problem in HAS, this paper proposes a novel linear extended state observer (LESO)-based motion synchronization control method. To cope with the problem of unavailability of the state signals required by the motion synchronization controller, LESO is designed for EHSA and EMA to observe the state variables. Based on the observed states of LESO, motion synchronization controllers could enable EHSA and EMA to simultaneously track the desired motion trajectories. Additionally, nonlinearities, uncertainties and unknown disturbances as well as the coupling term between EHSA and EMA can be estimated and compensated by using the extended state of the proposed LESO. Finally, comparative simulation results indicate that the proposed LESO-based motion synchronization controller could reduce significant force fighting between EHSA and EMA.

Moving object detection using dynamic motion modelling from UAV aerial images.

PubMed

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Linear Extended State Observer-Based Motion Synchronization Control for Hybrid Actuation System of More Electric Aircraft

PubMed Central

Liao, Rui; Shi, Cun; Wang, Shaoping

2017-01-01

Moving towards the more electric aircraft (MEA), a hybrid actuator configuration provides an opportunity to introduce electromechanical actuator (EMA) into primary flight control. In the hybrid actuation system (HAS), an electro-hydraulic servo actuator (EHSA) and an EMA operate on the same control surface. In order to solve force fighting problem in HAS, this paper proposes a novel linear extended state observer (LESO)-based motion synchronization control method. To cope with the problem of unavailability of the state signals required by the motion synchronization controller, LESO is designed for EHSA and EMA to observe the state variables. Based on the observed states of LESO, motion synchronization controllers could enable EHSA and EMA to simultaneously track the desired motion trajectories. Additionally, nonlinearities, uncertainties and unknown disturbances as well as the coupling term between EHSA and EMA can be estimated and compensated by using the extended state of the proposed LESO. Finally, comparative simulation results indicate that the proposed LESO-based motion synchronization controller could reduce significant force fighting between EHSA and EMA. PMID:29068392

A hybrid approach to estimate the complex motions of clouds in sky images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, Zhenzhou; Yu, Dantong; Huang, Dong

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

A hybrid approach to estimate the complex motions of clouds in sky images

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2016-09-14

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

Measurement of motion detection of wireless capsule endoscope inside large intestine.

PubMed

Zhou, Mingda; Bao, Guanqun; Pahlavan, Kaveh

2014-01-01

Wireless Capsule Endoscope (WCE) provides a noninvasive way to inspect the entire Gastrointestinal (GI) tract, including large intestine, where intestinal diseases most likely occur. As a critical component of capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of detected intestinal diseases. Knowing how the capsule moves inside the large intestine would greatly complement the existing wireless localization systems by providing the motion information. Since the most recently released WCE can take up to 6 frames per second, it's possible to estimate the movement of the capsule by processing the successive image sequence. In this paper, a computer vision based approach without utilizing any external device is proposed to estimate the motion of WCE inside the large intestine. The proposed approach estimate the displacement and rotation of the capsule by calculating entropy and mutual information between frames using Fibonacci method. The obtained results of this approach show its stability and better performance over other existing approaches of motion measurements. Meanwhile, findings of this paper lay a foundation for motion pattern of WCEs inside the large intestine, which will benefit other medical applications.

Using frequency analysis to improve the precision of human body posture algorithms based on Kalman filters.

PubMed

Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, G

2016-05-01

With the advent of miniaturized inertial sensors many systems have been developed within the last decade to study and analyze human motion and posture, specially in the medical field. Data measured by the sensors are usually processed by algorithms based on Kalman Filters in order to estimate the orientation of the body parts under study. These filters traditionally include fixed parameters, such as the process and observation noise variances, whose value has large influence in the overall performance. It has been demonstrated that the optimal value of these parameters differs considerably for different motion intensities. Therefore, in this work, we show that, by applying frequency analysis to determine motion intensity, and varying the formerly fixed parameters accordingly, the overall precision of orientation estimation algorithms can be improved, therefore providing physicians with reliable objective data they can use in their daily practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

PubMed Central

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms. PMID:22164069

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array

PubMed Central

Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

2016-01-01

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile’s rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm. PMID:26978372

FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

PubMed

Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

Improved shear wave group velocity estimation method based on spatiotemporal peak and thresholding motion search

PubMed Central

Amador, Carolina; Chen, Shigao; Manduca, Armando; Greenleaf, James F.; Urban, Matthew W.

2017-01-01

Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocities values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index (BMI), ultrasound scanners, scanning protocols, ultrasound image quality, etc. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this study, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time (spatiotemporal peak, STP); the second method applies an amplitude filter (spatiotemporal thresholding, STTH) to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared to TTP in phantom. Moreover, in a cohort of 14 healthy subjects STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared to conventional TTP. PMID:28092532

Improved Shear Wave Group Velocity Estimation Method Based on Spatiotemporal Peak and Thresholding Motion Search.

PubMed

Amador Carrascal, Carolina; Chen, Shigao; Manduca, Armando; Greenleaf, James F; Urban, Matthew W

2017-04-01

Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocity values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index, ultrasound scanners, scanning protocols, and ultrasound image quality. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this paper, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time [spatiotemporal peak (STP)]; the second method applies an amplitude filter [spatiotemporal thresholding (STTH)] to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared with TTP in phantom. Moreover, in a cohort of 14 healthy subjects, STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared with conventional TTP.

Real-Time Implementation of an Asynchronous Vision-Based Target Tracking System for an Unmanned Aerial Vehicle

DTIC Science & Technology

2007-06-01

Chin Khoon Quek. “Vision Based Control and Target Range Estimation for Small Unmanned Aerial Vehicle.” Master’s Thesis, Naval Postgraduate School...December 2005. [6] Kwee Chye Yap. “Incorporating Target Mensuration System for Target Motion Estimation Along a Road Using Asynchronous Filter

An ice-motion tracking system at the Alaska SAR facility

NASA Technical Reports Server (NTRS)

Kwok, Ronald; Curlander, John C.; Pang, Shirley S.; Mcconnell, Ross

1990-01-01

An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.

Absolute plate motions relative to deep mantle plumes

NASA Astrophysics Data System (ADS)

Wang, Shimin; Yu, Hongzheng; Zhang, Qiong; Zhao, Yonghong

2018-05-01

Advances in whole waveform seismic tomography have revealed the presence of broad mantle plumes rooted at the base of the Earth's mantle beneath major hotspots. Hotspot tracks associated with these deep mantle plumes provide ideal constraints for inverting absolute plate motions as well as testing the fixed hotspot hypothesis. In this paper, 27 observed hotspot trends associated with 24 deep mantle plumes are used together with the MORVEL model for relative plate motions to determine an absolute plate motion model, in terms of a maximum likelihood optimization for angular data fitting, combined with an outlier data detection procedure based on statistical tests. The obtained T25M model fits 25 observed trends of globally distributed hotspot tracks to the statistically required level, while the other two hotspot trend data (Comores on Somalia and Iceland on Eurasia) are identified as outliers, which are significantly incompatible with other data. For most hotspots with rate data available, T25M predicts plate velocities significantly lower than the observed rates of hotspot volcanic migration, which cannot be fully explained by biased errors in observed rate data. Instead, the apparent hotspot motions derived by subtracting the observed hotspot migration velocities from the T25M plate velocities exhibit a combined pattern of being opposite to plate velocities and moving towards mid-ocean ridges. The newly estimated net rotation of the lithosphere is statistically compatible with three recent estimates, but differs significantly from 30 of 33 prior estimates.

PSHA in Israel by using the synthetic ground motions from simulated seismicity: the modified SvE procedure

NASA Astrophysics Data System (ADS)

Meirova, T.; Shapira, A.; Eppelbaum, L.

2018-05-01

In this study, we updated and modified the SvE approach of Shapira and van Eck (Nat Hazards 8:201-215, 1993) which may be applied as an alternative to the conventional probabilistic seismic hazard assessment (PSHA) in Israel and other regions of low and moderate seismicity where measurements of strong ground motions are scarce. The new computational code SvE overcomes difficulties associated with the description of the earthquake source model and regional ground-motion scaling. In the modified SvE procedure, generating suites of regional ground motion is based on the extended two-dimensional source model of Motazedian and Atkinson (Bull Seism Soc Amer 95:995-1010, 2005a) and updated regional ground-motion scaling (Meirova and Hofstteter, Bull Earth Eng 15:3417-3436, 2017). The analytical approach of Mavroeidis and Papageorgiou (Bull Seism Soc Amer 93:1099-1131, 2003) is used to simulate the near-fault acceleration with the near-fault effects. The comparison of hazard estimates obtained by using the conventional method implemented in the National Building Code for Design provisions for earthquake resistance of structures and the modified SvE procedure for rock-site conditions indicates a general agreement with some perceptible differences at the periods of 0.2 and 0.5 s. For the periods above 0.5 s, the SvE estimates are systematically greater and can increase by a factor of 1.6. For the soft-soil sites, the SvE hazard estimates at the period of 0.2 s are greater than those based on the CB2008 ground-motion prediction equation (GMPE) by a factor of 1.3-1.6. We suggest that the hazard estimates for the sites with soft-soil conditions calculated by the modified SvE procedure are more reliable than those which can be found by means of the conventional PSHA. This result agrees with the opinion that the use of a standard GMPE applying the NEHRP soil classification based on the V s, 30 parameter may be inappropriate for PSHA at many sites in Israel.

Hydrological signal in polar motion excitation from a combination of geophysical and gravimetric series

NASA Astrophysics Data System (ADS)

Nastula, Jolanta; Winska, Malgorzata; Salstein, David A.

2015-08-01

One can estimate the hydrological signal in polar motion excitation as a residual, namely the difference between observed geodetic excitation functions (Geodetic Angular Momentum, GAM) and the sum of Atmospheric Angular Momentum (AAM) and Oceanic Angular Momentum (OAM).The aim of this study is to find the optimal model and results for hydrological excitation functions in terms of their agreement with the computed difference between GAM and atmospheric and oceanic signals.The atmospheric and oceanic model-based data that we use in this study are the geophysical excitation functions of AAM, OAM available from the Special Bureaus for the Atmosphere and Oceans of the Geophysical Global Fluids Center (GGFC) of the International Earth Rotation and Reference Systems Service (IERS). For the atmosphere and ocean, these functions are based on the mass and motion fields of the fluids.Global models of land hydrology are used to estimate hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM). These HAM series are the mass of water substance determined from the various types of land-based hydrological reservoirs. In addition the HAM are estimated from spherical harmonic coefficients of the Earth’s gravity field. We use several sets of degree-2, order-1 harmonics of the Earth’s gravity field, derived from the Gravity Recovery and Climate Experiment (GRACE), Satellite Laser Ranging (SLR), and Global Navigation Satellite Systems (GNSS) data.Finally, these several different HAM series are used to determine the best model of hydrological excitation of polar motion. The model is found by looking for the combination of these series that fits the geodetic residuals using the least-square method.In addition, we will access model results from the Coupled Model Intercomparison Project, fifth experiment (CMIP-5) to examine atmospheric excitations from the twentieth century and estimates for the twenty-first century to see the possible signals and trends of these excitation series to help understand the potential range in the derived of hydrological excitation results.

Estimation of the axis of a screw motion from noisy data--a new method based on Plücker lines.

PubMed

Kiat Teu, Koon; Kim, Wangdo

2006-01-01

The problems of estimating the motion and orientation parameters of a body segment from two n point-set patterns are analyzed using the Plücker coordinates of a line (Plücker lines). The aim is to find algorithms less complex than those in conventional use, and thus facilitating more accurate computation of the unknown parameters. All conventional techniques use point transformation to calculate the screw axis. In this paper, we present a novel technique that directly estimates the axis of a screw motion as a Plücker line. The Plücker line can be transformed via the dual-number coordinate transformation matrix. This method is compared with Schwartz and Rozumalski [2005. A new method for estimating joint parameters from motion data. Journal of Biomechanics 38, 107-116] in simulations of random measurement errors and systematic skin movements. Simulation results indicate that the methods based on Plücker lines (Plücker line method) are superior in terms of extremely good results in the determination of the screw axis direction and position as well as a concise derivation of mathematical statements. This investigation yielded practical results, which can be used to locate the axis of a screw motion in a noisy environment. Developing the dual transformation matrix (DTM) from noisy data and determining the screw axis from a given DTM is done in a manner analogous to that for handling simple rotations. A more robust approach to solve for the dual vector associated with DTM is also addressed by using the eigenvector and the singular value decomposition.

On Inertial Body Tracking in the Presence of Model Calibration Errors

PubMed Central

Miezal, Markus; Taetz, Bertram; Bleser, Gabriele

2016-01-01

In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity. PMID:27455266

Hard-rock GMPEs versus Vs30-Kappa Host-to-Target Adjustment Techniques : Why so Large Differences in High Frequency Hard-Rock Motion ?

NASA Astrophysics Data System (ADS)

Bard, P. Y.; Laurendeau, A.; Hollender, F.; Perron, V.; Hernandez, B.; Foundotos, L.

2016-12-01

Assessment of local seismic hazard on hard rock sites (1000 < VS30 < 3000 m/s) is needed either for installations built on such hard rock, or as a reference motion for site response computation. Empirical ground motion prediction equations (GMPEs) are the traditional basis for estimating ground motion, but most of them are poorly constrained for VS30 larger than 1000 m/s. The presently used approach for estimating hard rock hazard consists of "host-to-target" adjustment techniques (HTTA) based on VS30 and κ0 values. Recent studies have investigated alternative methods to estimate reference motions on very hard rock through an original processing of the Japanese KiK-net recordings from stiff sites (500 < VS30 < 1350 m/s). The pairs of recordings at surface and depth, together with the knowledge of the velocity profile, allowed to derive two sets of "virtual" outcropping, hard-rock motion data for sites having velocities in the range [1000 - 3000 m/s]. The corrections are based either on a transformation of deep, within-motion to outcropping motion, or on a deconvolution of surface recordings using the velocity profile and 1D simulation, which has been performed both in the response spectrum and Fourier domains. Each of these virtual "outcropping hard-rock motion" data sets has then been used to derive GMPEs with simple functional forms, using as site condition proxy the S-wave velocity at depth (VSDH), ranging from 1000 to 3000 m/s. Both sets provide very similar predictions, which are much smaller at high frequencies (f > 10 Hz) than those estimated with the traditional HTTA technique - by a factor up to 3-4,. These differences decrease for decreasing frequency, and become negligible at low frequency (f < 1 Hz). The main focus will be to discuss the possible reasons of such differences, in relation with the implicit or explicit assumptions of either approach. Our present interpretation is related to the existence of a significant, high-frequency amplification on stiff soils and standard rocks, due to thin, shallow, moderate velocity layers. Not only this resonant amplification is not correctly accounted for by the quarter-wavelength approach used in the traditional HTTA adjustment techniques, but it may also significantly impact and bias the κ measurements, and the (VS30- κ0) relationships implicitly used in HTTA techniques.

Motion tracking in the liver: Validation of a method based on 4D ultrasound using a nonrigid registration technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vijayan, Sinara, E-mail: sinara.vijayan@ntnu.no; Klein, Stefan; Hofstad, Erlend Fagertun

Purpose: Treatments like radiotherapy and focused ultrasound in the abdomen require accurate motion tracking, in order to optimize dosage delivery to the target and minimize damage to critical structures and healthy tissues around the target. 4D ultrasound is a promising modality for motion tracking during such treatments. In this study, the authors evaluate the accuracy of motion tracking in the liver based on deformable registration of 4D ultrasound images. Methods: The offline analysis was performed using a nonrigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D image data sequencemore » in a groupwise optimization fashion, thus avoiding a bias toward a specifically chosen reference time point. Three healthy volunteers were scanned over several breathing cycles (12 s) from three different positions and angles on the abdomen; a total of nine 4D scans for the three volunteers. Well-defined anatomic landmarks were manually annotated in all 96 time frames for assessment of the automatic algorithm. The error of the automatic motion estimation method was compared with interobserver variability. The authors also performed experiments to investigate the influence of parameters defining the deformation field flexibility and evaluated how well the method performed with a lower temporal resolution in order to establish the minimum frame rate required for accurate motion estimation. Results: The registration method estimated liver motion with an error of 1 mm (75% percentile over all datasets), which was lower than the interobserver variability of 1.4 mm. The results were only slightly dependent on the degrees of freedom of the deformation model. The registration error increased to 2.8 mm with an eight times lower temporal resolution. Conclusions: The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors believe that the method has potential in interventions on moving abdominal organs such as MR or ultrasound guided focused ultrasound therapy and radiotherapy, pending the method is enabled to run in real-time. The data and the annotations used for this study are made publicly available for those who would like to test other methods on 4D liver ultrasound data.« less

Motion correction of PET brain images through deconvolution: I. Theoretical development and analysis in software simulations

NASA Astrophysics Data System (ADS)

Faber, T. L.; Raghunath, N.; Tudorascu, D.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

Crustal block motion model and interplate coupling along Ecuador-Colombia trench based on GNSS observation network

NASA Astrophysics Data System (ADS)

Ito, T.; Mora-Páez, H.; Peláez-Gaviria, J. R.; Kimura, H.; Sagiya, T.

2017-12-01

IntroductionEcuador-Colombia trench is located at the boundary between South-America plate, Nazca Plate and Caribrian plate. This region is very complexes such as subducting Caribrian plate and Nazca plate, and collision between Panama and northern part of the Andes mountains. The previous large earthquakes occurred along the subducting boundary of Nazca plate, such as 1906 (M8.8) and 1979 (M8.2). And also, earthquakes occurred inland, too. So, it is important to evaluate earthquake potentials for preparing huge damage due to large earthquake in near future. GNSS observation In the last decade, the GNSS observation was established in Columbia. The GNSS observation is called by GEORED, which is operated by servicing Geologico Colomiano. The purpose of GEORED is research of crustal deformation. The number of GNSS site of GEORED is consist of 60 continuous GNSS observation site at 2017 (Mora et al., 2017). The sampling interval of almost GNSS site is 30 seconds. These GNSS data were processed by PPP processing using GIPSY-OASYS II software. GEORED can obtain the detailed crustal deformation map in whole Colombia. In addition, we use 100 GNSS data at Ecuador-Peru region (Nocquet et al. 2014). Method We developed a crustal block movements model based on crustal deformation derived from GNSS observation. Our model considers to the block motion with pole location and angular velocity and the interplate coupling between each block boundaries, including subduction between the South-American plate and the Nazca plate. And also, our approach of estimation of crustal block motion and coefficient of interplate coupling are based on MCMC method. The estimated each parameter is obtained probably density function (PDF). Result We tested 11 crustal block models based on geological data, such as active fault trace at surface. The optimal number of crustal blocks is 11 for based on geological and geodetic data using AIC. We use optimal block motion model. And also, we estimate interplate coupling along the plate interface and rigid block motion. We can evaluate to contribution of elastic deformation and rigid motion. In result, weak plate coupling was found northern part of 3 degree in latitude. Almost crustal deformation are explained by rigid block motion.

Coupled orbit-attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

NASA Astrophysics Data System (ADS)

Misra, Gaurav; Izadi, Maziar; Sanyal, Amit; Scheeres, Daniel

2016-04-01

The effects of dynamical coupling between the rotational (attitude) and translational (orbital) motion of spacecraft near small Solar System bodies is investigated. This coupling arises due to the weak gravity of these bodies, as well as solar radiation pressure. The traditional approach assumes a point-mass spacecraft model to describe the translational motion of the spacecraft, while the attitude motion is considered to be completely decoupled from the translational motion. The model used here to describe the rigid-body spacecraft dynamics includes the non-uniform rotating gravity field of the small body up to second degree and order along with the attitude dependent terms, solar tide, and solar radiation pressure. This model shows that the second degree and order gravity terms due to the small body affect the dynamics of the spacecraft to the same extent as the orbit-attitude coupling due to the primary gravity (zeroth order) term. Variational integrators are used to simulate the dynamics of both the rigid spacecraft and the point mass. The small bodies considered here are modeled after Near-Earth Objects (NEO) 101955 Bennu, and 25143 Itokawa, and are assumed to be triaxial ellipsoids with uniform density. Differences in the numerically obtained trajectories of a rigid spacecraft and a point mass are then compared, to illustrate the impact of the orbit-attitude coupling on spacecraft dynamics in proximity of small bodies. Possible implications on the performance of model-based spacecraft control and on the station-keeping budget, if the orbit-attitude coupling is not accounted for in the model of the dynamics, are also discussed. An almost globally asymptotically stable motion estimation scheme based solely on visual/optical feedback that estimates the relative motion of the asteroid with respect to the spacecraft is also obtained. This estimation scheme does not require a model of the dynamics of the asteroid, which makes it perfectly suited for asteroids whose properties are not well known.

Hybrid Orientation Based Human Limbs Motion Tracking Method

PubMed Central

Glonek, Grzegorz; Wojciechowski, Adam

2017-01-01

One of the key technologies that lays behind the human–machine interaction and human motion diagnosis is the limbs motion tracking. To make the limbs tracking efficient, it must be able to estimate a precise and unambiguous position of each tracked human joint and resulting body part pose. In recent years, body pose estimation became very popular and broadly available for home users because of easy access to cheap tracking devices. Their robustness can be improved by different tracking modes data fusion. The paper defines the novel approach—orientation based data fusion—instead of dominating in literature position based approach, for two classes of tracking devices: depth sensors (i.e., Microsoft Kinect) and inertial measurement units (IMU). The detailed analysis of their working characteristics allowed to elaborate a new method that let fuse more precisely limbs orientation data from both devices and compensates their imprecisions. The paper presents the series of performed experiments that verified the method’s accuracy. This novel approach allowed to outperform the precision of position-based joints tracking, the methods dominating in the literature, of up to 18%. PMID:29232832

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

PubMed

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.

PubMed

Shao, Zhanpeng; Li, Youfu

2016-02-01

Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.

Accurate motion parameter estimation for colonoscopy tracking using a regression method

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2010-03-01

Co-located optical and virtual colonoscopy images have the potential to provide important clinical information during routine colonoscopy procedures. In our earlier work, we presented an optical flow based algorithm to compute egomotion from live colonoscopy video, permitting navigation and visualization of the corresponding patient anatomy. In the original algorithm, motion parameters were estimated using the traditional Least Sum of squares(LS) procedure which can be unstable in the context of optical flow vectors with large errors. In the improved algorithm, we use the Least Median of Squares (LMS) method, a robust regression method for motion parameter estimation. Using the LMS method, we iteratively analyze and converge toward the main distribution of the flow vectors, while disregarding outliers. We show through three experiments the improvement in tracking results obtained using the LMS method, in comparison to the LS estimator. The first experiment demonstrates better spatial accuracy in positioning the virtual camera in the sigmoid colon. The second and third experiments demonstrate the robustness of this estimator, resulting in longer tracked sequences: from 300 to 1310 in the ascending colon, and 410 to 1316 in the transverse colon.

Unsupervised markerless 3-DOF motion tracking in real time using a single low-budget camera.

PubMed

Quesada, Luis; León, Alejandro J

2012-10-01

Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on motion tracking. In this paper, we present a novel three degrees of freedom motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera that can be found installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a nonmodeled unmarked object that may be nonrigid, nonconvex, partially occluded, self-occluded, or motion blurred, given that it is opaque, evenly colored, enough contrasting with the background in each frame, and that it does not rotate. Our system is also able to determine the most relevant object to track in the screen. Our proposal does not impose additional constraints, therefore it allows a market-wide implementation of applications that require the estimation of the three position degrees of freedom of an object.

Vision System Measures Motions of Robot and External Objects

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2008-01-01

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yi, Jianbing, E-mail: yijianbing8@163.com; Yang, Xuan, E-mail: xyang0520@263.net; Li, Yan-Ran, E-mail: lyran@szu.edu.cn

2015-10-15

Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered atmore » points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors’ method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors’ method ranks 24 of 39. According to the index of the maximum shear stretch, the authors’ method is also efficient to describe the discontinuous motion at the lung boundaries. Conclusions: By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors’ method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.« less

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm.

PubMed

Yi, Jianbing; Yang, Xuan; Chen, Guoliang; Li, Yan-Ran

2015-10-01

Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. The performances of the authors' method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors' method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors' method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors' method ranks 24 of 39. According to the index of the maximum shear stretch, the authors' method is also efficient to describe the discontinuous motion at the lung boundaries. By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors' method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.

ARMA models for earthquake ground motions. Seismic safety margins research program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, M. K.; Kwiatkowski, J. W.; Nau, R. F.

1981-02-01

Four major California earthquake records were analyzed by use of a class of discrete linear time-domain processes commonly referred to as ARMA (Autoregressive/Moving-Average) models. It was possible to analyze these different earthquakes, identify the order of the appropriate ARMA model(s), estimate parameters, and test the residuals generated by these models. It was also possible to show the connections, similarities, and differences between the traditional continuous models (with parameter estimates based on spectral analyses) and the discrete models with parameters estimated by various maximum-likelihood techniques applied to digitized acceleration data in the time domain. The methodology proposed is suitable for simulatingmore » earthquake ground motions in the time domain, and appears to be easily adapted to serve as inputs for nonlinear discrete time models of structural motions. 60 references, 19 figures, 9 tables.« less

Estimation of ground motion parameters

USGS Publications Warehouse

Boore, David M.; Joyner, W.B.; Oliver, A.A.; Page, R.A.

1978-01-01

Strong motion data from western North America for earthquakes of magnitude greater than 5 are examined to provide the basis for estimating peak acceleration, velocity, displacement, and duration as a function of distance for three magnitude classes. A subset of the data (from the San Fernando earthquake) is used to assess the effects of structural size and of geologic site conditions on peak motions recorded at the base of structures. Small but statistically significant differences are observed in peak values of horizontal acceleration, velocity and displacement recorded on soil at the base of small structures compared with values recorded at the base of large structures. The peak acceleration tends to b3e less and the peak velocity and displacement tend to be greater on the average at the base of large structures than at the base of small structures. In the distance range used in the regression analysis (15-100 km) the values of peak horizontal acceleration recorded at soil sites in the San Fernando earthquake are not significantly different from the values recorded at rock sites, but values of peak horizontal velocity and displacement are significantly greater at soil sites than at rock sites. Some consideration is given to the prediction of ground motions at close distances where there are insufficient recorded data points. As might be expected from the lack of data, published relations for predicting peak horizontal acceleration give widely divergent estimates at close distances (three well known relations predict accelerations between 0.33 g to slightly over 1 g at a distance of 5 km from a magnitude 6.5 earthquake). After considering the physics of the faulting process, the few available data close to faults, and the modifying effects of surface topography, at the present time it would be difficult to accept estimates less than about 0.8 g, 110 cm/s, and 40 cm, respectively, for the mean values of peak acceleration, velocity, and displacement at rock sites within 5 km of fault rupture in a magnitude 6.5 earthquake. These estimates can be expected to change as more data become available.

An atlas of ShakeMaps for selected global earthquakes

USGS Publications Warehouse

Allen, Trevor I.; Wald, David J.; Hotovec, Alicia J.; Lin, Kuo-Wan; Earle, Paul S.; Marano, Kristin D.

2008-01-01

An atlas of maps of peak ground motions and intensity 'ShakeMaps' has been developed for almost 5,000 recent and historical global earthquakes. These maps are produced using established ShakeMap methodology (Wald and others, 1999c; Wald and others, 2005) and constraints from macroseismic intensity data, instrumental ground motions, regional topographically-based site amplifications, and published earthquake-rupture models. Applying the ShakeMap methodology allows a consistent approach to combine point observations with ground-motion predictions to produce descriptions of peak ground motions and intensity for each event. We also calculate an estimated ground-motion uncertainty grid for each earthquake. The Atlas of ShakeMaps provides a consistent and quantitative description of the distribution and intensity of shaking for recent global earthquakes (1973-2007) as well as selected historic events. As such, the Atlas was developed specifically for calibrating global earthquake loss estimation methodologies to be used in the U.S. Geological Survey Prompt Assessment of Global Earthquakes for Response (PAGER) Project. PAGER will employ these loss models to rapidly estimate the impact of global earthquakes as part of the USGS National Earthquake Information Center's earthquake-response protocol. The development of the Atlas of ShakeMaps has also led to several key improvements to the Global ShakeMap system. The key upgrades include: addition of uncertainties in the ground motion mapping, introduction of modern ground-motion prediction equations, improved estimates of global seismic-site conditions (VS30), and improved definition of stable continental region polygons. Finally, we have merged all of the ShakeMaps in the Atlas to provide a global perspective of earthquake ground shaking for the past 35 years, allowing comparison with probabilistic hazard maps. The online Atlas and supporting databases can be found at http://earthquake.usgs.gov/eqcenter/shakemap/atlas.php/.

Motion vector field phase-to-amplitude resampling for 4D motion-compensated cone-beam CT

NASA Astrophysics Data System (ADS)

Sauppe, Sebastian; Kuhm, Julian; Brehm, Marcus; Paysan, Pascal; Seghers, Dieter; Kachelrieß, Marc

2018-02-01

We propose a phase-to-amplitude resampling (PTAR) method to reduce motion blurring in motion-compensated (MoCo) 4D cone-beam CT (CBCT) image reconstruction, without increasing the computational complexity of the motion vector field (MVF) estimation approach. PTAR is able to improve the image quality in reconstructed 4D volumes, including both regular and irregular respiration patterns. The PTAR approach starts with a robust phase-gating procedure for the initial MVF estimation and then switches to a phase-adapted amplitude gating method. The switch implies an MVF-resampling, which makes them amplitude-specific. PTAR ensures that the MVFs, which have been estimated on phase-gated reconstructions, are still valid for all amplitude-gated reconstructions. To validate the method, we use an artificially deformed clinical CT scan with a realistic breathing pattern and several patient data sets acquired with a TrueBeamTM integrated imaging system (Varian Medical Systems, Palo Alto, CA, USA). Motion blurring, which still occurs around the area of the diaphragm or at small vessels above the diaphragm in artifact-specific cyclic motion compensation (acMoCo) images based on phase-gating, is significantly reduced by PTAR. Also, small lung structures appear sharper in the images. This is demonstrated both for simulated and real patient data. A quantification of the sharpness of the diaphragm confirms these findings. PTAR improves the image quality of 4D MoCo reconstructions compared to conventional phase-gated MoCo images, in particular for irregular breathing patterns. Thus, PTAR increases the robustness of MoCo reconstructions for CBCT. Because PTAR does not require any additional steps for the MVF estimation, it is computationally efficient. Our method is not restricted to CBCT but could rather be applied to other image modalities.

Integrated evaluation of visually induced motion sickness in terms of autonomic nervous regulation.

PubMed

Kiryu, Tohru; Tada, Gen; Toyama, Hiroshi; Iijima, Atsuhiko

2008-01-01

To evaluate visually-induced motion sickness, we integrated subjective and objective responses in terms of autonomic nervous regulation. Twenty-seven subjects viewed a 2-min-long first-person-view video section five times (total 10 min) continuously. Measured biosignals, the RR interval, respiration, and blood pressure, were used to estimate the indices related to autonomic nervous activity (ANA). Then we determined the trigger points and some sensation sections based on the time-varying behavior of ANA-related indices. We found that there was a suitable combination of biosignals to present the symptoms of visually-induced motion sickness. Based on the suitable combination, integrating trigger points and subjective scores allowed us to represent the time-distribution of subjective responses during visual exposure, and helps us to understand what types of camera motions will cause visually-induced motion sickness.

Estimation of two-dimensional motion velocity using ultrasonic signals beamformed in Cartesian coordinate for measurement of cardiac dynamics

NASA Astrophysics Data System (ADS)

Kaburaki, Kaori; Mozumi, Michiya; Hasegawa, Hideyuki

2018-07-01

Methods for the estimation of two-dimensional (2D) velocity and displacement of physiological tissues are necessary for quantitative diagnosis. In echocardiography with a phased array probe, the accuracy in the estimation of the lateral motion is lower than that of the axial motion. To improve the accuracy in the estimation of the lateral motion, in the present study, the coordinate system for ultrasonic beamforming was changed from the conventional polar coordinate to the Cartesian coordinate. In a basic experiment, the motion velocity of a phantom, which was moved at a constant speed, was estimated by the conventional and proposed methods. The proposed method reduced the bias error and standard deviation in the estimated motion velocities. In an in vivo measurement, intracardiac blood flow was analyzed by the proposed method.

Motion capture based identification of the human body inertial parameters.

PubMed

Venture, Gentiane; Ayusawa, Ko; Nakamura, Yoshihiko

2008-01-01

Identification of body inertia, masses and center of mass is an important data to simulate, monitor and understand dynamics of motion, to personalize rehabilitation programs. This paper proposes an original method to identify the inertial parameters of the human body, making use of motion capture data and contact forces measurements. It allows in-vivo painless estimation and monitoring of the inertial parameters. The method is described and then obtained experimental results are presented and discussed.

Plate motions and deformations from geologic and geodetic data

NASA Technical Reports Server (NTRS)

Jordan, T. H.

1986-01-01

A satellite laser ranging experiment conducted by NASA since 1972 has measured the relative motion between the North America and Pacific plates in California. Based on these measurements, the 896-km distance between San Diego and Quincy, California, is shortening at 62 + or - 9 mm/yr. This geodetic estimate is consistent with the rate of motion between the two plates, calculated from geological data to be 53 + or - 3 mm/yr averaged over the past few million years.

Patch-based frame interpolation for old films via the guidance of motion paths

NASA Astrophysics Data System (ADS)

Xia, Tianran; Ding, Youdong; Yu, Bing; Huang, Xi

2018-04-01

Due to improper preservation, traditional films will appear frame loss after digital. To deal with this problem, this paper presents a new adaptive patch-based method of frame interpolation via the guidance of motion paths. Our method is divided into three steps. Firstly, we compute motion paths between two reference frames using optical flow estimation. Then, the adaptive bidirectional interpolation with holes filled is applied to generate pre-intermediate frames. Finally, using patch match to interpolate intermediate frames with the most similar patches. Since the patch match is based on the pre-intermediate frames that contain the motion paths constraint, we show a natural and inartificial frame interpolation. We test different types of old film sequences and compare with other methods, the results prove that our method has a desired performance without hole or ghost effects.

A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor

PubMed Central

González, Diego; Botella, Guillermo; Meyer-Baese, Uwe; García, Carlos; Sanz, Concepción; Prieto-Matías, Manuel; Tirado, Francisco

2012-01-01

This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system. PMID:23201989

Method for measuring tri-axial lumbar motion angles using wearable sheet stretch sensors

PubMed Central

Nakamoto, Hiroyuki; Yamaji, Tokiya; Ootaka, Hideo; Bessho, Yusuke; Nakamura, Ryo; Ono, Rei

2017-01-01

Background Body movements, such as trunk flexion and rotation, are risk factors for low back pain in occupational settings, especially in healthcare workers. Wearable motion capture systems are potentially useful to monitor lower back movement in healthcare workers to help avoid the risk factors. In this study, we propose a novel system using sheet stretch sensors and investigate the system validity for estimating lower back movement. Methods Six volunteers (female:male = 1:1, mean age: 24.8 ± 4.0 years, height 166.7 ± 5.6 cm, weight 56.3 ± 7.6 kg) participated in test protocols that involved executing seven types of movements. The movements were three uniaxial trunk movements (i.e., trunk flexion-extension, trunk side-bending, and trunk rotation) and four multiaxial trunk movements (i.e., flexion + rotation, flexion + side-bending, side-bending + rotation, and moving around the cranial–caudal axis). Each trial lasted for approximately 30 s. Four stretch sensors were attached to each participant’s lower back. The lumbar motion angles were estimated using simple linear regression analysis based on the stretch sensor outputs and compared with those obtained by the optical motion capture system. Results The estimated lumbar motion angles showed a good correlation with the actual angles, with correlation values of r = 0.68 (SD = 0.35), r = 0.60 (SD = 0.19), and r = 0.72 (SD = 0.18) for the flexion-extension, side bending, and rotation movements, respectively (all P < 0.05). The estimation errors in all three directions were less than 3°. Conclusion The stretch sensors mounted on the back provided reasonable estimates of the lumbar motion angles. The novel motion capture system provided three directional angles without capture space limits. The wearable system possessed great potential to monitor the lower back movement in healthcare workers and helping prevent low back pain. PMID:29020053

Motion Tracker: Camera-Based Monitoring of Bodily Movements Using Motion Silhouettes

PubMed Central

Westlund, Jacqueline Kory; D’Mello, Sidney K.; Olney, Andrew M.

2015-01-01

Researchers in the cognitive and affective sciences investigate how thoughts and feelings are reflected in the bodily response systems including peripheral physiology, facial features, and body movements. One specific question along this line of research is how cognition and affect are manifested in the dynamics of general body movements. Progress in this area can be accelerated by inexpensive, non-intrusive, portable, scalable, and easy to calibrate movement tracking systems. Towards this end, this paper presents and validates Motion Tracker, a simple yet effective software program that uses established computer vision techniques to estimate the amount a person moves from a video of the person engaged in a task (available for download from http://jakory.com/motion-tracker/). The system works with any commercially available camera and with existing videos, thereby affording inexpensive, non-intrusive, and potentially portable and scalable estimation of body movement. Strong between-subject correlations were obtained between Motion Tracker’s estimates of movement and body movements recorded from the seat (r =.720) and back (r = .695 for participants with higher back movement) of a chair affixed with pressure-sensors while completing a 32-minute computerized task (Study 1). Within-subject cross-correlations were also strong for both the seat (r =.606) and back (r = .507). In Study 2, between-subject correlations between Motion Tracker’s movement estimates and movements recorded from an accelerometer worn on the wrist were also strong (rs = .801, .679, and .681) while people performed three brief actions (e.g., waving). Finally, in Study 3 the within-subject cross-correlation was high (r = .855) when Motion Tracker’s estimates were correlated with the movement of a person’s head as tracked with a Kinect while the person was seated at a desk (Study 3). Best-practice recommendations, limitations, and planned extensions of the system are discussed. PMID:26086771

Empirical evidence for site coefficients in building code provisions

USGS Publications Warehouse

Borcherdt, R.D.

2002-01-01

Site-response coefficients, Fa and Fv, used in U.S. building code provisions are based on empirical data for motions up to 0.1 g. For larger motions they are based on theoretical and laboratory results. The Northridge earthquake of 17 January 1994 provided a significant new set of empirical data up to 0.5 g. These data together with recent site characterizations based on shear-wave velocity measurements provide empirical estimates of the site coefficients at base accelerations up to 0.5 g for Site Classes C and D. These empirical estimates of Fa and Fnu; as well as their decrease with increasing base acceleration level are consistent at the 95 percent confidence level with those in present building code provisions, with the exception of estimates for Fa at levels of 0.1 and 0.2 g, which are less than the lower confidence bound by amounts up to 13 percent. The site-coefficient estimates are consistent at the 95 percent confidence level with those of several other investigators for base accelerations greater than 0.3 g. These consistencies and present code procedures indicate that changes in the site coefficients are not warranted. Empirical results for base accelerations greater than 0.2 g confirm the need for both a short- and a mid- or long-period site coefficient to characterize site response for purposes of estimating site-specific design spectra.

Hierarchical information fusion for global displacement estimation in microsensor motion capture.

PubMed

Meng, Xiaoli; Zhang, Zhi-Qiang; Wu, Jian-Kang; Wong, Wai-Choong

2013-07-01

This paper presents a novel hierarchical information fusion algorithm to obtain human global displacement for different gait patterns, including walking, running, and hopping based on seven body-worn inertial and magnetic measurement units. In the first-level sensor fusion, the orientation for each segment is achieved by a complementary Kalman filter (CKF) which compensates for the orientation error of the inertial navigation system solution through its error state vector. For each foot segment, the displacement is also estimated by the CKF, and zero velocity update is included for the drift reduction in foot displacement estimation. Based on the segment orientations and left/right foot locations, two global displacement estimates can be acquired from left/right lower limb separately using a linked biomechanical model. In the second-level geometric fusion, another Kalman filter is deployed to compensate for the difference between the two estimates from the sensor fusion and get more accurate overall global displacement estimation. The updated global displacement will be transmitted to left/right foot based on the human lower biomechanical model to restrict the drifts in both feet displacements. The experimental results have shown that our proposed method can accurately estimate human locomotion for the three different gait patterns with regard to the optical motion tracker.

Astrometric detectability of systems with unseen companions: effects of the Earth orbital motion

NASA Astrophysics Data System (ADS)

Butkevich, Alexey G.

2018-06-01

The astrometric detection of an unseen companion is based on an analysis of the apparent motion of its host star around the system's barycentre. Systems with an orbital period close to 1 yr may escape detection if the orbital motion of their host stars is observationally indistinguishable from the effects of parallax. Additionally, an astrometric solution may produce a biased parallax estimation for such systems. We examine the effects of the orbital motion of the Earth on astrometric detectability in terms of a correlation between the Earth's orbital position and the position of the star relative to its system barycentre. The χ2 statistic for parallax estimation is calculated analytically, leading to expressions that relate the decrease in detectability and accompanying parallax bias to the position correlation function. The impact of the Earth's motion critically depends on the exoplanet's orbital period, diminishing rapidly as the period deviates from 1 yr. Selection effects against 1-yr-period systems is, therefore, expected. Statistical estimation shows that the corresponding loss of sensitivity results in a typical 10 per cent increase in the detection threshold. Consideration of eccentric orbits shows that the Earth's motion has no effect on detectability for e≳ 0.5. The dependence of the detectability on other parameters, such as orbital phases and inclination of the orbital plane to the ecliptic, are smooth and monotonic because they are described by simple trigonometric functions.

Real-time stylistic prediction for whole-body human motions.

PubMed

Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

2012-01-01

The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

NASA Astrophysics Data System (ADS)

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-01

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology.

PubMed

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-13

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Estimating 3D L5/S1 moments and ground reaction forces during trunk bending using a full-body ambulatory inertial motion capture system.

PubMed

Faber, G S; Chang, C C; Kingma, I; Dennerlein, J T; van Dieën, J H

2016-04-11

Inertial motion capture (IMC) systems have become increasingly popular for ambulatory movement analysis. However, few studies have attempted to use these measurement techniques to estimate kinetic variables, such as joint moments and ground reaction forces (GRFs). Therefore, we investigated the performance of a full-body ambulatory IMC system in estimating 3D L5/S1 moments and GRFs during symmetric, asymmetric and fast trunk bending, performed by nine male participants. Using an ambulatory IMC system (Xsens/MVN), L5/S1 moments were estimated based on the upper-body segment kinematics using a top-down inverse dynamics analysis, and GRFs were estimated based on full-body segment accelerations. As a reference, a laboratory measurement system was utilized: GRFs were measured with Kistler force plates (FPs), and L5/S1 moments were calculated using a bottom-up inverse dynamics model based on FP data and lower-body kinematics measured with an optical motion capture system (OMC). Correspondence between the OMC+FP and IMC systems was quantified by calculating root-mean-square errors (RMSerrors) of moment/force time series and the interclass correlation (ICC) of the absolute peak moments/forces. Averaged over subjects, L5/S1 moment RMSerrors remained below 10Nm (about 5% of the peak extension moment) and 3D GRF RMSerrors remained below 20N (about 2% of the peak vertical force). ICCs were high for the peak L5/S1 extension moment (0.971) and vertical GRF (0.998). Due to lower amplitudes, smaller ICCs were found for the peak asymmetric L5/S1 moments (0.690-0.781) and horizontal GRFs (0.559-0.948). In conclusion, close correspondence was found between the ambulatory IMC-based and laboratory-based estimates of back load. Copyright © 2015 Elsevier Ltd. All rights reserved.

Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

PubMed Central

Xie, Weihong; Yu, Yang

2017-01-01

Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly. PMID:29124062

Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach.

PubMed

Liang, Fan; Xie, Weihong; Yu, Yang

2017-01-01

Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively "switch" from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

PubMed

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-07-07

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

PubMed Central

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-01-01

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method. PMID:26198231

Feature-based respiratory motion tracking in native fluoroscopic sequences for dynamic roadmaps during minimally invasive procedures in the thorax and abdomen

NASA Astrophysics Data System (ADS)

Wagner, Martin G.; Laeseke, Paul F.; Schubert, Tilman; Slagowski, Jordan M.; Speidel, Michael A.; Mistretta, Charles A.

2017-03-01

Fluoroscopic image guidance for minimally invasive procedures in the thorax and abdomen suffers from respiratory and cardiac motion, which can cause severe subtraction artifacts and inaccurate image guidance. This work proposes novel techniques for respiratory motion tracking in native fluoroscopic images as well as a model based estimation of vessel deformation. This would allow compensation for respiratory motion during the procedure and therefore simplify the workflow for minimally invasive procedures such as liver embolization. The method first establishes dynamic motion models for both the contrast-enhanced vasculature and curvilinear background features based on a native (non-contrast) and a contrast-enhanced image sequence acquired prior to device manipulation, under free breathing conditions. The model of vascular motion is generated by applying the diffeomorphic demons algorithm to an automatic segmentation of the subtraction sequence. The model of curvilinear background features is based on feature tracking in the native sequence. The two models establish the relationship between the respiratory state, which is inferred from curvilinear background features, and the vascular morphology during that same respiratory state. During subsequent fluoroscopy, curvilinear feature detection is applied to determine the appropriate vessel mask to display. The result is a dynamic motioncompensated vessel mask superimposed on the fluoroscopic image. Quantitative evaluation of the proposed methods was performed using a digital 4D CT-phantom (XCAT), which provides realistic human anatomy including sophisticated respiratory and cardiac motion models. Four groups of datasets were generated, where different parameters (cycle length, maximum diaphragm motion and maximum chest expansion) were modified within each image sequence. Each group contains 4 datasets consisting of the initial native and contrast enhanced sequences as well as a sequence, where the respiratory motion is tracked. The respiratory motion tracking error was between 1.00 % and 1.09 %. The estimated dynamic vessel masks yielded a Sørensen-Dice coefficient between 0.94 and 0.96. Finally, the accuracy of the vessel contours was measured in terms of the 99th percentile of the error, which ranged between 0.64 and 0.96 mm. The presented results show that the approach is feasible for respiratory motion tracking and compensation and could therefore considerably improve the workflow of minimally invasive procedures in the thorax and abdomen

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Mao, Zhu; Niezrecki, Christopher; Poozesh, Peyman

2018-05-01

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

Estimation of object motion parameters from noisy images.

PubMed

Broida, T J; Chellappa, R

1986-01-01

An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.

A novel Bayesian respiratory motion model to estimate and resolve uncertainty in image-guided cardiac interventions.

PubMed

Peressutti, Devis; Penney, Graeme P; Housden, R James; Kolbitsch, Christoph; Gomez, Alberto; Rijkhorst, Erik-Jan; Barratt, Dean C; Rhode, Kawal S; King, Andrew P

2013-05-01

In image-guided cardiac interventions, respiratory motion causes misalignments between the pre-procedure roadmap of the heart used for guidance and the intra-procedure position of the heart, reducing the accuracy of the guidance information and leading to potentially dangerous consequences. We propose a novel technique for motion-correcting the pre-procedural information that combines a probabilistic MRI-derived affine motion model with intra-procedure real-time 3D echocardiography (echo) images in a Bayesian framework. The probabilistic model incorporates a measure of confidence in its motion estimates which enables resolution of the potentially conflicting information supplied by the model and the echo data. Unlike models proposed so far, our method allows the final motion estimate to deviate from the model-produced estimate according to the information provided by the echo images, so adapting to the complex variability of respiratory motion. The proposed method is evaluated using gold-standard MRI-derived motion fields and simulated 3D echo data for nine volunteers and real 3D live echo images for four volunteers. The Bayesian method is compared to 5 other motion estimation techniques and results show mean/max improvements in estimation accuracy of 10.6%/18.9% for simulated echo images and 20.8%/41.5% for real 3D live echo data, over the best comparative estimation method. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

Estimation of heart rate variability using a compact radiofrequency motion sensor.

PubMed

Sugita, Norihiro; Matsuoka, Narumi; Yoshizawa, Makoto; Abe, Makoto; Homma, Noriyasu; Otake, Hideharu; Kim, Junghyun; Ohtaki, Yukio

2015-12-01

Physiological indices that reflect autonomic nervous activity are considered useful for monitoring peoples' health on a daily basis. A number of such indices are derived from heart rate variability, which is obtained by a radiofrequency (RF) motion sensor without making physical contact with the user's body. However, the bulkiness of RF motion sensors used in previous studies makes them unsuitable for home use. In this study, a new method to measure heart rate variability using a compact RF motion sensor that is sufficiently small to fit in a user's shirt pocket is proposed. To extract a heart rate related component from the sensor signal, an algorithm that optimizes a digital filter based on the power spectral density of the signal is proposed. The signals of the RF motion sensor were measured for 29 subjects during the resting state and their heart rate variability was estimated from the measured signals using the proposed method and a conventional method. A correlation coefficient between true heart rate and heart rate estimated from the proposed method was 0.69. Further, the experimental results showed the viability of the RF sensor for monitoring autonomic nervous activity. However, some improvements such as controlling the direction of sensing were necessary for stable measurement. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Scene-aware joint global and local homographic video coding

NASA Astrophysics Data System (ADS)

Peng, Xiulian; Xu, Jizheng; Sullivan, Gary J.

2016-09-01

Perspective motion is commonly represented in video content that is captured and compressed for various applications including cloud gaming, vehicle and aerial monitoring, etc. Existing approaches based on an eight-parameter homography motion model cannot deal with this efficiently, either due to low prediction accuracy or excessive bit rate overhead. In this paper, we consider the camera motion model and scene structure in such video content and propose a joint global and local homography motion coding approach for video with perspective motion. The camera motion is estimated by a computer vision approach, and camera intrinsic and extrinsic parameters are globally coded at the frame level. The scene is modeled as piece-wise planes, and three plane parameters are coded at the block level. Fast gradient-based approaches are employed to search for the plane parameters for each block region. In this way, improved prediction accuracy and low bit costs are achieved. Experimental results based on the HEVC test model show that up to 9.1% bit rate savings can be achieved (with equal PSNR quality) on test video content with perspective motion. Test sequences for the example applications showed a bit rate savings ranging from 3.7 to 9.1%.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

NASA Astrophysics Data System (ADS)

Bowen, S. R.; Nyflot, M. J.; Herrmann, C.; Groh, C. M.; Meyer, J.; Wollenweber, S. D.; Stearns, C. W.; Kinahan, P. E.; Sandison, G. A.

2015-05-01

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [18F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study.

PubMed

Bowen, S R; Nyflot, M J; Herrmann, C; Groh, C M; Meyer, J; Wollenweber, S D; Stearns, C W; Kinahan, P E; Sandison, G A

2015-05-07

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [(18)F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

PubMed Central

Bowen, S R; Nyflot, M J; Hermann, C; Groh, C; Meyer, J; Wollenweber, S D; Stearns, C W; Kinahan, P E; Sandison, G A

2015-01-01

Effective positron emission tomography/computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [18F]FDG. The lung lesion insert was driven by 6 different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy (VMAT) were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses (EUD), and 2%-2mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10–20%, treatment planning errors were 5–10%, and treatment delivery errors were 5–30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5–10% in PET/CT imaging, < 5% in treatment planning, and < 2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery. PMID:25884892

Arterial Mechanical Motion Estimation Based on a Semi-Rigid Body Deformation Approach

PubMed Central

Guzman, Pablo; Hamarneh, Ghassan; Ros, Rafael; Ros, Eduardo

2014-01-01

Arterial motion estimation in ultrasound (US) sequences is a hard task due to noise and discontinuities in the signal derived from US artifacts. Characterizing the mechanical properties of the artery is a promising novel imaging technique to diagnose various cardiovascular pathologies and a new way of obtaining relevant clinical information, such as determining the absence of dicrotic peak, estimating the Augmentation Index (AIx), the arterial pressure or the arterial stiffness. One of the advantages of using US imaging is the non-invasive nature of the technique unlike Intra Vascular Ultra Sound (IVUS) or angiography invasive techniques, plus the relative low cost of the US units. In this paper, we propose a semi rigid deformable method based on Soft Bodies dynamics realized by a hybrid motion approach based on cross-correlation and optical flow methods to quantify the elasticity of the artery. We evaluate and compare different techniques (for instance optical flow methods) on which our approach is based. The goal of this comparative study is to identify the best model to be used and the impact of the accuracy of these different stages in the proposed method. To this end, an exhaustive assessment has been conducted in order to decide which model is the most appropriate for registering the variation of the arterial diameter over time. Our experiments involved a total of 1620 evaluations within nine simulated sequences of 84 frames each and the estimation of four error metrics. We conclude that our proposed approach obtains approximately 2.5 times higher accuracy than conventional state-of-the-art techniques. PMID:24871987

Quantifying and Qualifying USGS ShakeMap Uncertainty

USGS Publications Warehouse

Wald, David J.; Lin, Kuo-Wan; Quitoriano, Vincent

2008-01-01

We describe algorithms for quantifying and qualifying uncertainties associated with USGS ShakeMap ground motions. The uncertainty values computed consist of latitude/longitude grid-based multiplicative factors that scale the standard deviation associated with the ground motion prediction equation (GMPE) used within the ShakeMap algorithm for estimating ground motions. The resulting grid-based 'uncertainty map' is essential for evaluation of losses derived using ShakeMaps as the hazard input. For ShakeMap, ground motion uncertainty at any point is dominated by two main factors: (i) the influence of any proximal ground motion observations, and (ii) the uncertainty of estimating ground motions from the GMPE, most notably, elevated uncertainty due to initial, unconstrained source rupture geometry. The uncertainty is highest for larger magnitude earthquakes when source finiteness is not yet constrained and, hence, the distance to rupture is also uncertain. In addition to a spatially-dependant, quantitative assessment, many users may prefer a simple, qualitative grading for the entire ShakeMap. We developed a grading scale that allows one to quickly gauge the appropriate level of confidence when using rapidly produced ShakeMaps as part of the post-earthquake decision-making process or for qualitative assessments of archived or historical earthquake ShakeMaps. We describe an uncertainty letter grading ('A' through 'F', for high to poor quality, respectively) based on the uncertainty map. A middle-range ('C') grade corresponds to a ShakeMap for a moderate-magnitude earthquake suitably represented with a point-source location. Lower grades 'D' and 'F' are assigned for larger events (M>6) where finite-source dimensions are not yet constrained. The addition of ground motion observations (or observed macroseismic intensities) reduces uncertainties over data-constrained portions of the map. Higher grades ('A' and 'B') correspond to ShakeMaps with constrained fault dimensions and numerous stations, depending on the density of station/data coverage. Due to these dependencies, the letter grade can change with subsequent ShakeMap revisions if more data are added or when finite-faulting dimensions are added. We emphasize that the greatest uncertainties are associated with unconstrained source dimensions for large earthquakes where the distance term in the GMPE is most uncertain; this uncertainty thus scales with magnitude (and consequently rupture dimension). Since this distance uncertainty produces potentially large uncertainties in ShakeMap ground-motion estimates, this factor dominates over compensating constraints for all but the most dense station distributions.

A rate-constrained fast full-search algorithm based on block sum pyramid.

PubMed

Song, Byung Cheol; Chun, Kang-Wook; Ra, Jong Beom

2005-03-01

This paper presents a fast full-search algorithm (FSA) for rate-constrained motion estimation. The proposed algorithm, which is based on the block sum pyramid frame structure, successively eliminates unnecessary search positions according to rate-constrained criterion. This algorithm provides the identical estimation performance to a conventional FSA having rate constraint, while achieving considerable reduction in computation.

Productivity and cost estimators for conventional ground-based skidding on steep terrain using preplanned skid roads

Treesearch

Michael D. Erickson; Curt C. Hassler; Chris B. LeDoux

1991-01-01

Continuous time and motion study techniques were used to develop productivity and cost estimators for the skidding component of ground-based logging systems, operating on steep terrain using preplanned skid roads. Comparisons of productivity and costs were analyzed for an overland random access skidding method, verses a skidding method utilizing a network of preplanned...

Emg Amplitude Estimators Based on Probability Distribution for Muscle-Computer Interface

NASA Astrophysics Data System (ADS)

Phinyomark, Angkoon; Quaine, Franck; Laurillau, Yann; Thongpanja, Sirinee; Limsakul, Chusak; Phukpattaranont, Pornchai

To develop an advanced muscle-computer interface (MCI) based on surface electromyography (EMG) signal, the amplitude estimations of muscle activities, i.e., root mean square (RMS) and mean absolute value (MAV) are widely used as a convenient and accurate input for a recognition system. Their classification performance is comparable to advanced and high computational time-scale methods, i.e., the wavelet transform. However, the signal-to-noise-ratio (SNR) performance of RMS and MAV depends on a probability density function (PDF) of EMG signals, i.e., Gaussian or Laplacian. The PDF of upper-limb motions associated with EMG signals is still not clear, especially for dynamic muscle contraction. In this paper, the EMG PDF is investigated based on surface EMG recorded during finger, hand, wrist and forearm motions. The results show that on average the experimental EMG PDF is closer to a Laplacian density, particularly for male subject and flexor muscle. For the amplitude estimation, MAV has a higher SNR, defined as the mean feature divided by its fluctuation, than RMS. Due to a same discrimination of RMS and MAV in feature space, MAV is recommended to be used as a suitable EMG amplitude estimator for EMG-based MCIs.

Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation

PubMed Central

Sabatini, Angelo Maria

2011-01-01

In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical. PMID:22163689

A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring

PubMed Central

Yang, Che-Chang; Hsu, Yeh-Liang

2010-01-01

Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies. PMID:22163626

2-D Versus 3-D Cross-Correlation-Based Radial and Circumferential Strain Estimation Using Multiplane 2-D Ultrafast Ultrasound in a 3-D Atherosclerotic Carotid Artery Model.

PubMed

Fekkes, Stein; Swillens, Abigail E S; Hansen, Hendrik H G; Saris, Anne E C M; Nillesen, Maartje M; Iannaccone, Francesco; Segers, Patrick; de Korte, Chris L

2016-10-01

Three-dimensional (3-D) strain estimation might improve the detection and localization of high strain regions in the carotid artery (CA) for identification of vulnerable plaques. This paper compares 2-D versus 3-D displacement estimation in terms of radial and circumferential strain using simulated ultrasound (US) images of a patient-specific 3-D atherosclerotic CA model at the bifurcation embedded in surrounding tissue generated with ABAQUS software. Global longitudinal motion was superimposed to the model based on the literature data. A Philips L11-3 linear array transducer was simulated, which transmitted plane waves at three alternating angles at a pulse repetition rate of 10 kHz. Interframe (IF) radio-frequency US data were simulated in Field II for 191 equally spaced longitudinal positions of the internal CA. Accumulated radial and circumferential displacements were estimated using tracking of the IF displacements estimated by a two-step normalized cross-correlation method and displacement compounding. Least-squares strain estimation was performed to determine accumulated radial and circumferential strain. The performance of the 2-D and 3-D methods was compared by calculating the root-mean-squared error of the estimated strains with respect to the reference strains obtained from the model. More accurate strain images were obtained using the 3-D displacement estimation for the entire cardiac cycle. The 3-D technique clearly outperformed the 2-D technique in phases with high IF longitudinal motion. In fact, the large IF longitudinal motion rendered it impossible to accurately track the tissue and cumulate strains over the entire cardiac cycle with the 2-D technique.

Functionally interpretable local coordinate systems for the upper extremity using inertial & magnetic measurement systems.

PubMed

de Vries, W H K; Veeger, H E J; Cutti, A G; Baten, C; van der Helm, F C T

2010-07-20

Inertial Magnetic Measurement Systems (IMMS) are becoming increasingly popular by allowing for measurements outside the motion laboratory. The latest models enable long term, accurate measurement of segment motion in terms of joint angles, if initial segment orientations can accurately be determined. The standard procedure for definition of segmental orientation is based on the measurement of positions of bony landmarks (BLM). However, IMMS do not deliver position information, so an alternative method to establish IMMS based, anatomically understandable segment orientations is proposed. For five subjects, IMMS recordings were collected in a standard anatomical position for definition of static axes, and during a series of standardized motions for the estimation of kinematic axes of rotation. For all axes, the intra- and inter-individual dispersion was estimated. Subsequently, local coordinate systems (LCS) were constructed on the basis of the combination of IMMS axes with the lowest dispersion and compared with BLM based LCS. The repeatability of the method appeared to be high; for every segment at least two axes could be determined with a dispersion of at most 3.8 degrees. Comparison of IMMS based with BLM based LCS yielded compatible results for the thorax, but less compatible results for the humerus, forearm and hand, where differences in orientation rose to 17.2 degrees. Although different from the 'gold standard' BLM based LCS, IMMS based LCS can be constructed repeatable, enabling the estimation of segment orientations outside the laboratory. A procedure for the definition of local reference frames using IMMS is proposed. 2010 Elsevier Ltd. All rights reserved.

Helicopter flight simulation motion platform requirements

NASA Astrophysics Data System (ADS)

Schroeder, Jeffery Allyn

Flight simulators attempt to reproduce in-flight pilot-vehicle behavior on the ground. This reproduction is challenging for helicopter simulators, as the pilot is often inextricably dependent on external cues for pilot-vehicle stabilization. One important simulator cue is platform motion; however, its required fidelity is unknown. To determine the required motion fidelity, several unique experiments were performed. A large displacement motion platform was used that allowed pilots to fly tasks with matched motion and visual cues. Then, the platform motion was modified to give cues varying from full motion to no motion. Several key results were found. First, lateral and vertical translational platform cues had significant effects on fidelity. Their presence improved performance and reduced pilot workload. Second, yaw and roll rotational platform cues were not as important as the translational platform cues. In particular, the yaw rotational motion platform cue did not appear at all useful in improving performance or reducing workload. Third, when the lateral translational platform cue was combined with visual yaw rotational cues, pilots believed the platform was rotating when it was not. Thus, simulator systems can be made more efficient by proper combination of platform and visual cues. Fourth, motion fidelity specifications were revised that now provide simulator users with a better prediction of motion fidelity based upon the frequency responses of their motion control laws. Fifth, vertical platform motion affected pilot estimates of steady-state altitude during altitude repositionings. This refutes the view that pilots estimate altitude and altitude rate in simulation solely from visual cues. Finally, the combined results led to a general method for configuring helicopter motion systems and for developing simulator tasks that more likely represent actual flight. The overall results can serve as a guide to future simulator designers and to today's operators.

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

Vertical land motion controls regional sea level rise patterns on the United States east coast since 1900

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Hay, C.; Mitrovica, J. X.; Little, C. M.; Ponte, R. M.; Tingley, M.

2017-12-01

Understanding observed spatial variations in centennial relative sea level trends on the United States east coast has important scientific and societal applications. Past studies based on models and proxies variously suggest roles for crustal displacement, ocean dynamics, and melting of the Greenland ice sheet. Here we perform joint Bayesian inference on regional relative sea level, vertical land motion, and absolute sea level fields based on tide gauge records and GPS data. Posterior solutions show that regional vertical land motion explains most (80% median estimate) of the spatial variance in the large-scale relative sea level trend field on the east coast over 1900-2016. The posterior estimate for coastal absolute sea level rise is remarkably spatially uniform compared to previous studies, with a spatial average of 1.4-2.3 mm/yr (95% credible interval). Results corroborate glacial isostatic adjustment models and reveal that meaningful long-period, large-scale vertical velocity signals can be extracted from short GPS records.

Microseismicity of Blawan hydrothermal complex, Bondowoso, East Java, Indonesia

NASA Astrophysics Data System (ADS)

Maryanto, S.

2018-03-01

Peak Ground Acceleration (PGA), hypocentre, and epicentre of Blawan hydrothermal complex have been analysed in order to investigate its seismicity. PGA has been determined based on Fukushima-Tanaka method and the source location of microseismic estimated using particle motion method. PGA ranged between 0.095-0.323 g and tends to be higher in the formation that containing not compacted rocks. The seismic vulnerability index region indicated that the zone with high PGA also has a high seismic vulnerability index. This was because the rocks making up these zones were inclined soft and low-density rocks. For seismic sources around the area, epicentre and hypocentre, have estimated base on seismic particle motion method of single station. The stations used in this study were mobile stations identified as BL01, BL02, BL03, BL05, BL06, BL07 and BL08. The results of the analysis particle motion obtained 44 points epicentre and the depth of the sources about 15 – 110 meters below ground surface.

The statistics of local motion signals in naturalistic movies

PubMed Central

Nitzany, Eyal I.; Victor, Jonathan D.

2014-01-01

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics. PMID:24732243

The statistics of local motion signals in naturalistic movies.

PubMed

Nitzany, Eyal I; Victor, Jonathan D

2014-04-14

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics.

Optimal estimation of diffusion coefficients from single-particle trajectories

NASA Astrophysics Data System (ADS)

Vestergaard, Christian L.; Blainey, Paul C.; Flyvbjerg, Henrik

2014-02-01

How does one optimally determine the diffusion coefficient of a diffusing particle from a single-time-lapse recorded trajectory of the particle? We answer this question with an explicit, unbiased, and practically optimal covariance-based estimator (CVE). This estimator is regression-free and is far superior to commonly used methods based on measured mean squared displacements. In experimentally relevant parameter ranges, it also outperforms the analytically intractable and computationally more demanding maximum likelihood estimator (MLE). For the case of diffusion on a flexible and fluctuating substrate, the CVE is biased by substrate motion. However, given some long time series and a substrate under some tension, an extended MLE can separate particle diffusion on the substrate from substrate motion in the laboratory frame. This provides benchmarks that allow removal of bias caused by substrate fluctuations in CVE. The resulting unbiased CVE is optimal also for short time series on a fluctuating substrate. We have applied our estimators to human 8-oxoguanine DNA glycolase proteins diffusing on flow-stretched DNA, a fluctuating substrate, and found that diffusion coefficients are severely overestimated if substrate fluctuations are not accounted for.

Ultrasound thermography: A new temperature reconstruction model and in vivo results

NASA Astrophysics Data System (ADS)

Bayat, Mahdi; Ballard, John R.; Ebbini, Emad S.

2017-03-01

The recursive echo strain filter (RESF) model is presented as a new echo shift-based ultrasound temperature estimation model. The model is shown to have an infinite impulse response (IIR) filter realization of a differentitor-integrator operator. This model is then used for tracking sub-therapeutic temperature changes due to high intensity focused ultrasound (HIFU) shots in the hind limb of the Copenhagen rats in vivo. In addition to the reconstruction filter, a motion compensation method is presented which takes advantage of the deformation field outside the region of interest to correct the motion errors during temperature tracking. The combination of the RESF model and motion compensation algorithm is shown to greatly enhance the accuracy of the in vivo temperature estimation using ultrasound echo shifts.

Space-variant restoration of images degraded by camera motion blur.

PubMed

Sorel, Michal; Flusser, Jan

2008-02-01

We examine the problem of restoration from multiple images degraded by camera motion blur. We consider scenes with significant depth variations resulting in space-variant blur. The proposed algorithm can be applied if the camera moves along an arbitrary curve parallel to the image plane, without any rotations. The knowledge of camera trajectory and camera parameters is not necessary. At the input, the user selects a region where depth variations are negligible. The algorithm belongs to the group of variational methods that estimate simultaneously a sharp image and a depth map, based on the minimization of a cost functional. To initialize the minimization, it uses an auxiliary window-based depth estimation algorithm. Feasibility of the algorithm is demonstrated by three experiments with real images.

Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.

PubMed

Chen, Haibin; Zhong, Zichun; Yang, Yiwei; Chen, Jiawei; Zhou, Linghong; Zhen, Xin; Gu, Xuejun

2018-02-27

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.

A revised ground-motion and intensity interpolation scheme for shakemap

USGS Publications Warehouse

Worden, C.B.; Wald, D.J.; Allen, T.I.; Lin, K.; Garcia, D.; Cua, G.

2010-01-01

We describe a weighted-average approach for incorporating various types of data (observed peak ground motions and intensities and estimates from groundmotion prediction equations) into the ShakeMap ground motion and intensity mapping framework. This approach represents a fundamental revision of our existing ShakeMap methodology. In addition, the increased availability of near-real-time macroseismic intensity data, the development of newrelationships between intensity and peak ground motions, and new relationships to directly predict intensity from earthquake source information have facilitated the inclusion of intensity measurements directly into ShakeMap computations. Our approach allows for the combination of (1) direct observations (ground-motion measurements or reported intensities), (2) observations converted from intensity to ground motion (or vice versa), and (3) estimated ground motions and intensities from prediction equations or numerical models. Critically, each of the aforementioned data types must include an estimate of its uncertainties, including those caused by scaling the influence of observations to surrounding grid points and those associated with estimates given an unknown fault geometry. The ShakeMap ground-motion and intensity estimates are an uncertainty-weighted combination of these various data and estimates. A natural by-product of this interpolation process is an estimate of total uncertainty at each point on the map, which can be vital for comprehensive inventory loss calculations. We perform a number of tests to validate this new methodology and find that it produces a substantial improvement in the accuracy of ground-motion predictions over empirical prediction equations alone.

An All-Sky Search for Wide Binaries in the SUPERBLINK Proper Motion Catalog

NASA Astrophysics Data System (ADS)

Hartman, Zachary; Lepine, Sebastien

2017-01-01

We present initial results from an all-sky search for Common Proper Motion (CPM) binaries in the SUPERBLINK all-sky proper motion catalog of 2.8 million stars with proper motions greater than 40 mas/yr, which has been recently enhanced with data from the GAIA mission. We initially search the SUPERBLINK catalog for pairs of stars with angular separations up to 1 degree and proper motion difference less than 40 mas/yr. In order to determine which of these pairs are real binaries, we develop a Bayesian analysis to calculate probabilities of true companionship based on a combination of proper motion magnitude, angular separation, and proper motion differences. The analysis reveals that the SUPERBLINK catalog most likely contains ~40,000 genuine common proper motion binaries. We provide initial estimates of the distances and projected physical separations of these wide binaries.

Speed Biases With Real-Life Video Clips

PubMed Central

Rossi, Federica; Montanaro, Elisa; de’Sperati, Claudio

2018-01-01

We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli (short clips of human motion, mixed human-physical motion, physical motion and ego-motion), speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion) to 32% (physical motion). Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual tempo may integrate traditional methods that assess time perception: speed biases may be exploited to develop a simple, objective test of reality flow, to be used for example in clinical and developmental contexts. From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate “natural” video compression techniques based on sub-threshold temporal squeezing. PMID:29615875

Speed Biases With Real-Life Video Clips.

PubMed

Rossi, Federica; Montanaro, Elisa; de'Sperati, Claudio

2018-01-01

We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli (short clips of human motion, mixed human-physical motion, physical motion and ego-motion), speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion) to 32% (physical motion). Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual tempo may integrate traditional methods that assess time perception: speed biases may be exploited to develop a simple, objective test of reality flow, to be used for example in clinical and developmental contexts. From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate "natural" video compression techniques based on sub-threshold temporal squeezing.

Processing of angular motion and gravity information through an internal model.

PubMed

Laurens, Jean; Straumann, Dominik; Hess, Bernhard J M

2010-09-01

The vestibular organs in the base of the skull provide important information about head orientation and motion in space. Previous studies have suggested that both angular velocity information from the semicircular canals and information about head orientation and translation from the otolith organs are centrally processed in an internal model of head motion, using the principles of optimal estimation. This concept has been successfully applied to model behavioral responses to classical vestibular motion paradigms. This study measured the dynamic of the vestibuloocular reflex during postrotatory tilt, tilt during the optokinetic afternystagmus, and off-vertical axis rotation. The influence of otolith signal on the VOR was systematically varied by using a series of tilt angles. We found that the time constants of responses varied almost identically as a function of gravity in these paradigms. We show that Bayesian modeling could predict the experimental results in an accurate and consistent manner. In contrast to other approaches, the Bayesian model also provides a plausible explanation of why these vestibulooculo motor responses occur as a consequence of an internal process of optimal motion estimation.

Revised motion estimation algorithm for PROPELLER MRI.

PubMed

Pipe, James G; Gibbs, Wende N; Li, Zhiqiang; Karis, John P; Schar, Michael; Zwart, Nicholas R

2014-08-01

To introduce a new algorithm for estimating data shifts (used for both rotation and translation estimates) for motion-corrected PROPELLER MRI. The method estimates shifts for all blades jointly, emphasizing blade-pair correlations that are both strong and more robust to noise. The heads of three volunteers were scanned using a PROPELLER acquisition while they exhibited various amounts of motion. All data were reconstructed twice, using motion estimates from the original and new algorithm. Two radiologists independently and blindly compared 216 image pairs from these scans, ranking the left image as substantially better or worse than, slightly better or worse than, or equivalent to the right image. In the aggregate of 432 scores, the new method was judged substantially better than the old method 11 times, and was never judged substantially worse. The new algorithm compared favorably with the old in its ability to estimate bulk motion in a limited study of volunteer motion. A larger study of patients is planned for future work. Copyright © 2013 Wiley Periodicals, Inc.

The effect of concurrent hand movement on estimated time to contact in a prediction motion task.

PubMed

Zheng, Ran; Maraj, Brian K V

2018-04-27

In many activities, we need to predict the arrival of an occluded object. This action is called prediction motion or motion extrapolation. Previous researchers have found that both eye tracking and the internal clocking model are involved in the prediction motion task. Additionally, it is reported that concurrent hand movement facilitates the eye tracking of an externally generated target in a tracking task, even if the target is occluded. The present study examined the effect of concurrent hand movement on the estimated time to contact in a prediction motion task. We found different (accurate/inaccurate) concurrent hand movements had the opposite effect on the eye tracking accuracy and estimated TTC in the prediction motion task. That is, the accurate concurrent hand tracking enhanced eye tracking accuracy and had the trend to increase the precision of estimated TTC, but the inaccurate concurrent hand tracking decreased eye tracking accuracy and disrupted estimated TTC. However, eye tracking accuracy does not determine the precision of estimated TTC.

Discrimination of Human Forearm Motions on the Basis of Myoelectric Signals by Using Adaptive Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Seki, Hirokazu

This paper describes a method for discriminating of the human forearm motions based on the myoelectric signals using an adaptive fuzzy inference system. In conventional studies, the neural network is often used to estimate motion intention by the myoelectric signals and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signals. This study designs the membership function and the fuzzy rules using the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. In addition, the characteristics of the myoelectric potential gradually change as a result of the muscle fatigue. Therefore, the motion discrimination should be performed by taking muscle fatigue into consideration. This study proposes a method to redesign the fuzzy inference system such that dynamic change of the myoelectric potential because of the muscle fatigue will be taken into account. Some experiments carried out using a myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

Fast image interpolation for motion estimation using graphics hardware

NASA Astrophysics Data System (ADS)

Kelly, Francis; Kokaram, Anil

2004-05-01

Motion estimation and compensation is the key to high quality video coding. Block matching motion estimation is used in most video codecs, including MPEG-2, MPEG-4, H.263 and H.26L. Motion estimation is also a key component in the digital restoration of archived video and for post-production and special effects in the movie industry. Sub-pixel accurate motion vectors can improve the quality of the vector field and lead to more efficient video coding. However sub-pixel accuracy requires interpolation of the image data. Image interpolation is a key requirement of many image processing algorithms. Often interpolation can be a bottleneck in these applications, especially in motion estimation due to the large number pixels involved. In this paper we propose using commodity computer graphics hardware for fast image interpolation. We use the full search block matching algorithm to illustrate the problems and limitations of using graphics hardware in this way.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

DOE PAGES

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

2017-11-27

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

Estimation of regression laws for ground motion parameters using as case of study the Amatrice earthquake

NASA Astrophysics Data System (ADS)

Tiberi, Lara; Costa, Giovanni

2017-04-01

The possibility to directly associate the damages to the ground motion parameters is always a great challenge, in particular for civil protections. Indeed a ground motion parameter, estimated in near real time that can express the damages occurred after an earthquake, is fundamental to arrange the first assistance after an event. The aim of this work is to contribute to the estimation of the ground motion parameter that better describes the observed intensity, immediately after an event. This can be done calculating for each ground motion parameter estimated in a near real time mode a regression law which correlates the above-mentioned parameter to the observed macro-seismic intensity. This estimation is done collecting high quality accelerometric data in near field, filtering them at different frequency steps. The regression laws are calculated using two different techniques: the non linear least-squares (NLLS) Marquardt-Levenberg algorithm and the orthogonal distance methodology (ODR). The limits of the first methodology are the needed of initial values for the parameters a and b (set 1.0 in this study), and the constraint that the independent variable must be known with greater accuracy than the dependent variable. While the second algorithm is based on the estimation of the errors perpendicular to the line, rather than just vertically. The vertical errors are just the errors in the 'y' direction, so only for the dependent variable whereas the perpendicular errors take into account errors for both the variables, the dependent and the independent. This makes possible also to directly invert the relation, so the a and b values can be used also to express the gmps as function of I. For each law the standard deviation and R2 value are estimated in order to test the quality and the reliability of the found relation. The Amatrice earthquake of 24th August of 2016 is used as case of study to test the goodness of the calculated regression laws.

Vision-based control for flight relative to dynamic environments

NASA Astrophysics Data System (ADS)

Causey, Ryan Scott

The concept of autonomous systems has been considered an enabling technology for a diverse group of military and civilian applications. The current direction for autonomous systems is increased capabilities through more advanced systems that are useful for missions that require autonomous avoidance, navigation, tracking, and docking. To facilitate this level of mission capability, passive sensors, such as cameras, and complex software are added to the vehicle. By incorporating an on-board camera, visual information can be processed to interpret the surroundings. This information allows decision making with increased situational awareness without the cost of a sensor signature, which is critical in military applications. The concepts presented in this dissertation facilitate the issues inherent to vision-based state estimation of moving objects for a monocular camera configuration. The process consists of several stages involving image processing such as detection, estimation, and modeling. The detection algorithm segments the motion field through a least-squares approach and classifies motions not obeying the dominant trend as independently moving objects. An approach to state estimation of moving targets is derived using a homography approach. The algorithm requires knowledge of the camera motion, a reference motion, and additional feature point geometry for both the target and reference objects. The target state estimates are then observed over time to model the dynamics using a probabilistic technique. The effects of uncertainty on state estimation due to camera calibration are considered through a bounded deterministic approach. The system framework focuses on an aircraft platform of which the system dynamics are derived to relate vehicle states to image plane quantities. Control designs using standard guidance and navigation schemes are then applied to the tracking and homing problems using the derived state estimation. Four simulations are implemented in MATLAB that build on the image concepts present in this dissertation. The first two simulations deal with feature point computations and the effects of uncertainty. The third simulation demonstrates the open-loop estimation of a target ground vehicle in pursuit whereas the four implements a homing control design for the Autonomous Aerial Refueling (AAR) using target estimates as feedback.

Motion Correction in PROPELLER and Turboprop-MRI

PubMed Central

Tamhane, Ashish A.; Arfanakis, Konstantinos

2009-01-01

PROPELLER and Turboprop-MRI are characterized by greatly reduced sensitivity to motion, compared to their predecessors, fast spin-echo and gradient and spin-echo, respectively. This is due to the inherent self-navigation and motion correction of PROPELLER-based techniques. However, it is unknown how various acquisition parameters that determine k-space sampling affect the accuracy of motion correction in PROPELLER and Turboprop-MRI. The goal of this work was to evaluate the accuracy of motion correction in both techniques, to identify an optimal rotation correction approach, and determine acquisition strategies for optimal motion correction. It was demonstrated that, blades with multiple lines allow more accurate estimation of motion than blades with fewer lines. Also, it was shown that Turboprop-MRI is less sensitive to motion than PROPELLER. Furthermore, it was demonstrated that the number of blades does not significantly affect motion correction. Finally, clinically appropriate acquisition strategies that optimize motion correction were discussed for PROPELLER and Turboprop-MRI. PMID:19365858

On-Line Use of Three-Dimensional Marker Trajectory Estimation From Cone-Beam Computed Tomography Projections for Precise Setup in Radiotherapy for Targets With Respiratory Motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Worm, Esben S., E-mail: esbeworm@rm.dk; Department of Medical Physics, Aarhus University Hospital, Aarhus; Hoyer, Morten

2012-05-01

Purpose: To develop and evaluate accurate and objective on-line patient setup based on a novel semiautomatic technique in which three-dimensional marker trajectories were estimated from two-dimensional cone-beam computed tomography (CBCT) projections. Methods and Materials: Seven treatment courses of stereotactic body radiotherapy for liver tumors were delivered in 21 fractions in total to 6 patients by a linear accelerator. Each patient had two to three gold markers implanted close to the tumors. Before treatment, a CBCT scan with approximately 675 two-dimensional projections was acquired during a full gantry rotation. The marker positions were segmented in each projection. From this, the three-dimensionalmore » marker trajectories were estimated using a probability based method. The required couch shifts for patient setup were calculated from the mean marker positions along the trajectories. A motion phantom moving with known tumor trajectories was used to examine the accuracy of the method. Trajectory-based setup was retrospectively used off-line for the first five treatment courses (15 fractions) and on-line for the last two treatment courses (6 fractions). Automatic marker segmentation was compared with manual segmentation. The trajectory-based setup was compared with setup based on conventional CBCT guidance on the markers (first 15 fractions). Results: Phantom measurements showed that trajectory-based estimation of the mean marker position was accurate within 0.3 mm. The on-line trajectory-based patient setup was performed within approximately 5 minutes. The automatic marker segmentation agreed with manual segmentation within 0.36 {+-} 0.50 pixels (mean {+-} SD; pixel size, 0.26 mm in isocenter). The accuracy of conventional volumetric CBCT guidance was compromised by motion smearing ({<=}21 mm) that induced an absolute three-dimensional setup error of 1.6 {+-} 0.9 mm (maximum, 3.2) relative to trajectory-based setup. Conclusions: The first on-line clinical use of trajectory estimation from CBCT projections for precise setup in stereotactic body radiotherapy was demonstrated. Uncertainty in the conventional CBCT-based setup procedure was eliminated with the new method.« less

Developing the Second Generation CMORPH: A Prototype

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert

2014-05-01

A prototype system of the second generation CMORPH is being developed at NOAA Climate Prediction Center (CPC) to produce global analyses of 30-min precipitation on a 0.05deg lat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. First, precipitation estimation / retrievals from various sources are mapped onto a global grid of 0.05deg lat/lon and calibrated against a common reference field to ensure consistency in their precipitation rate PDF structures. The motion vectors for the precipitating cloud systems are then defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed from CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors with an objective analysis technique. Fine resolution mapped PMW precipitation retrievals are then separately propagated along the motion vectors from their respective observation times to the target analysis time from both forward and backward directions. The CMORPH high resolution precipitation analyses are finally constructed through the combination of propagated PMW retrievals with the IR based estimates for the target analysis time. This Kalman Filter based CMORPH processing is performed for rainfall and snowfall fields separately with the same motion vectors. Experiments have been conducted for two periods of two months each, July - August 2009, and January - February 2010, to explore the development of an optimal algorithm that generates global precipitation for summer and winter situations. Preliminary results demonstrated technical feasibility to construct global rainfall and snowfall analyses through the integration of information from multiple sources. More work is underway to refine various technical components of the system for operational applications of the system. Detailed results will be reported at the EGU meeting.

Video-Based Method of Quantifying Performance and Instrument Motion During Simulated Phonosurgery

PubMed Central

Conroy, Ellen; Surender, Ketan; Geng, Zhixian; Chen, Ting; Dailey, Seth; Jiang, Jack

2015-01-01

Objectives/Hypothesis To investigate the use of the Video-Based Phonomicrosurgery Instrument Tracking System to collect instrument position data during simulated phonomicrosurgery and calculate motion metrics using these data. We used this system to determine if novice subject motion metrics improved over 1 week of training. Study Design Prospective cohort study. Methods Ten subjects performed simulated surgical tasks once per day for 5 days. Instrument position data were collected and used to compute motion metrics (path length, depth perception, and motion smoothness). Data were analyzed to determine if motion metrics improved with practice time. Task outcome was also determined each day, and relationships between task outcome and motion metrics were used to evaluate the validity of motion metrics as indicators of surgical performance. Results Significant decreases over time were observed for path length (P <.001), depth perception (P <.001), and task outcome (P <.001). No significant change was observed for motion smoothness. Significant relationships were observed between task outcome and path length (P <.001), depth perception (P <.001), and motion smoothness (P <.001). Conclusions Our system can estimate instrument trajectory and provide quantitative descriptions of surgical performance. It may be useful for evaluating phonomicrosurgery performance. Path length and depth perception may be particularly useful indicators. PMID:24737286

Joint Center Estimation Using Single-Frame Optimization: Part 1: Numerical Simulation.

PubMed

Frick, Eric; Rahmatalla, Salam

2018-04-04

The biomechanical models used to refine and stabilize motion capture processes are almost invariably driven by joint center estimates, and any errors in joint center calculation carry over and can be compounded when calculating joint kinematics. Unfortunately, accurate determination of joint centers is a complex task, primarily due to measurements being contaminated by soft-tissue artifact (STA). This paper proposes a novel approach to joint center estimation implemented via sequential application of single-frame optimization (SFO). First, the method minimizes the variance of individual time frames’ joint center estimations via the developed variance minimization method to obtain accurate overall initial conditions. These initial conditions are used to stabilize an optimization-based linearization of human motion that determines a time-varying joint center estimation. In this manner, the complex and nonlinear behavior of human motion contaminated by STA can be captured as a continuous series of unique rigid-body realizations without requiring a complex analytical model to describe the behavior of STA. This article intends to offer proof of concept, and the presented method must be further developed before it can be reasonably applied to human motion. Numerical simulations were introduced to verify and substantiate the efficacy of the proposed methodology. When directly compared with a state-of-the-art inertial method, SFO reduced the error due to soft-tissue artifact in all cases by more than 45%. Instead of producing a single vector value to describe the joint center location during a motion capture trial as existing methods often do, the proposed method produced time-varying solutions that were highly correlated ( r > 0.82) with the true, time-varying joint center solution.

Wall shear stress estimation in the aorta: Impact of wall motion, spatiotemporal resolution, and phase noise.

PubMed

Zimmermann, Judith; Demedts, Daniel; Mirzaee, Hanieh; Ewert, Peter; Stern, Heiko; Meierhofer, Christian; Menze, Bjoern; Hennemuth, Anja

2018-04-01

Wall shear stress (WSS) presents an important parameter for assessing blood flow characteristics and evaluating flow-mediated lesions in the aorta. To investigate the robustness of WSS and oscillatory shear index (OSI) estimation based on 4D flow MRI against vessel wall motion, spatiotemporal resolution, and velocity encoding (VENC). Simulated and prospective. Synthetic 4D flow MRI data of the aorta, simulated using the Lattice-Boltzmann method; in vivo 4D flow MRI data of the aorta from healthy volunteers (n = 11) and patients with congenital heart defects (n = 17). 1.5T; 4D flow MRI with PEAK-GRAPPA acceleration and prospective electrocardiogram triggering. Predicated upon 3D cubic B-splines interpolation of the image velocity field, WSS was estimated in mid-systole, early-diastole, and late-diastole and OSI was derived. We assessed the impact of spatiotemporal resolution and phase noise, and compared results based on tracked-using deformable registration-and static vessel wall location. Bland-Altman analysis to assess WSS/OSI differences; Hausdorff distance (HD) to assess wall motion; and Pearson's correlation coefficient (PCC) to assess correlation of HD with WSS. Synthetic data results show systematic over-/underestimation of WSS when different spatial resolution (mean ± 1.96 SD up to -0.24 ± 0.40 N/m 2 and 0.5 ± 1.38 N/m 2 for 8-fold and 27-fold voxel size, respectively) and VENC-depending phase noise (mean ± 1.96 SD up to 0.31 ± 0.12 N/m 2 and 0.94 ± 0.28 N/m 2 for 2-fold and 4-fold VENC increase, respectively) are given. Neglecting wall motion when defining the vessel wall perturbs WSS estimates to a considerable extent (1.96 SD up to 1.21 N/m 2 ) without systematic over-/underestimation (Bland-Altman mean range -0.06 to 0.05). In addition to sufficient spatial resolution and velocity to noise ratio, accurate tracking of the vessel wall is essential for reliable image-based WSS estimation and should not be neglected if wall motion is present. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Computation of fluid and particle motion from a time-sequenced image pair: a global outlier identification approach.

PubMed

Ray, Nilanjan

2011-10-01

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its application is widespread in experimental fluidics research and many related areas like biomedical engineering and atmospheric sciences. In this paper, we present a novel flow computation framework to estimate the flow velocity vectors from two consecutive image frames. In an energy minimization-based flow computation, we propose a novel data fidelity term, which: 1) can accommodate various measures, such as cross-correlation or sum of absolute or squared differences of pixel intensities between image patches; 2) has a global mechanism to control the adverse effect of outliers arising out of motion discontinuities, proximity of image borders; and 3) can go hand-in-hand with various spatial smoothness terms. Further, the proposed data term and related regularization schemes are both applicable to dense and sparse flow vector estimations. We validate these claims by numerical experiments on benchmark flow data sets. © 2011 IEEE

Algorithm architecture co-design for ultra low-power image sensor

NASA Astrophysics Data System (ADS)

Laforest, T.; Dupret, A.; Verdant, A.; Lattard, D.; Villard, P.

2012-03-01

In a context of embedded video surveillance, stand alone leftbehind image sensors are used to detect events with high level of confidence, but also with a very low power consumption. Using a steady camera, motion detection algorithms based on background estimation to find regions in movement are simple to implement and computationally efficient. To reduce power consumption, the background is estimated using a down sampled image formed of macropixels. In order to extend the class of moving objects to be detected, we propose an original mixed mode architecture developed thanks to an algorithm architecture co-design methodology. This programmable architecture is composed of a vector of SIMD processors. A basic RISC architecture was optimized in order to implement motion detection algorithms with a dedicated set of 42 instructions. Definition of delta modulation as a calculation primitive has allowed to implement algorithms in a very compact way. Thereby, a 1920x1080@25fps CMOS image sensor performing integrated motion detection is proposed with a power estimation of 1.8 mW.

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

Motion estimation in the frequency domain using fuzzy c-planes clustering.

PubMed

Erdem, C E; Karabulut, G Z; Yanmaz, E; Anarim, E

2001-01-01

A recent work explicitly models the discontinuous motion estimation problem in the frequency domain where the motion parameters are estimated using a harmonic retrieval approach. The vertical and horizontal components of the motion are independently estimated from the locations of the peaks of respective periodogram analyses and they are paired to obtain the motion vectors using a procedure proposed. In this paper, we present a more efficient method that replaces the motion component pairing task and hence eliminates the problems of the pairing method described. The method described in this paper uses the fuzzy c-planes (FCP) clustering approach to fit planes to three-dimensional (3-D) frequency domain data obtained from the peaks of the periodograms. Experimental results are provided to demonstrate the effectiveness of the proposed method.

WE-AB-303-11: Verification of a Deformable 4DCT Motion Model for Lung Tumor Tracking Using Different Driving Surrogates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woelfelschneider, J; Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, DE; Seregni, M

2015-06-15

Purpose: Tumor tracking is an advanced technique to treat intra-fractionally moving tumors. The aim of this study is to validate a surrogate-driven model based on four-dimensional computed tomography (4DCT) that is able to predict CT volumes corresponding to arbitrary respiratory states. Further, the comparison of three different driving surrogates is evaluated. Methods: This study is based on multiple 4DCTs of two patients treated for bronchial carcinoma and metastasis. Analyses for 18 additional patients are currently ongoing. The motion model was estimated from the planning 4DCT through deformable image registration. To predict a certain phase of a follow-up 4DCT, the modelmore » considers for inter-fractional variations (baseline correction) and intra-fractional respiratory parameters (amplitude and phase) derived from surrogates. In this evaluation, three different approaches were used to extract the motion surrogate: for each 4DCT phase, the 3D thoraco-abdominal surface motion, the body volume and the anterior-posterior motion of a virtual single external marker defined on the sternum were investigated. The estimated volumes resulting from the model were compared to the ground-truth clinical 4DCTs using absolute HU differences in the lung volume and landmarks localized using the Scale Invariant Feature Transform (SIFT). Results: The results show absolute HU differences between estimated and ground-truth images with median values limited to 55 HU and inter-quartile ranges (IQR) lower than 100 HU. Median 3D distances between about 1500 matching landmarks are below 2 mm for 3D surface motion and body volume methods. The single marker surrogates Result in increased median distances up to 0.6 mm. Analyses for the extended database incl. 20 patients are currently in progress. Conclusion: The results depend mainly on the image quality of the initial 4DCTs and the deformable image registration. All investigated surrogates can be used to estimate follow-up 4DCT phases, however uncertainties decrease for three-dimensional approaches. This work was funded in parts by the German Research Council (DFG) - KFO 214/2.« less

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound.

PubMed

Seo, Joohyun; Pietrangelo, Sabino J; Sodini, Charles G; Lee, Hae-Seung

2018-05-01

This paper details unfocused imaging using single-element ultrasound transducers for motion tolerant arterial blood pressure (ABP) waveform estimation. The ABP waveform is estimated based on pulse wave velocity and arterial pulsation through Doppler and M-mode ultrasound. This paper discusses approaches to mitigate the effect of increased clutter due to unfocused imaging on blood flow and diameter waveform estimation. An intensity reduction model (IRM) estimator is described to track the change of diameter, which outperforms a complex cross-correlation model (C3M) estimator in low contrast environments. An adaptive clutter filtering approach is also presented, which reduces the increased Doppler angle estimation error due to unfocused imaging. Experimental results in a flow phantom demonstrate that flow velocity and diameter waveforms can be reliably measured with wide lateral offsets of the transducer position. The distension waveform estimated from human carotid M-mode imaging using the IRM estimator shows physiological baseline fluctuations and 0.6-mm pulsatile diameter change on average, which is within the expected physiological range. These results show the feasibility of this low cost and portable ABP waveform estimation device.

Spacecraft Formation Control and Estimation Via Improved Relative Motion Dynamics

DTIC Science & Technology

2017-03-30

statistical (e.g. batch least-squares or Extended Kalman Filter ) estimator. In addition, the IROD approach can be applied to classical (ground-based...covariance  Test the viability of IROD solutions by injecting them into precise orbit determination schemes (e.g. various strains of Kalman filters

Incremental Dynamic Analysis of Koyna Dam under Repeated Ground Motions

NASA Astrophysics Data System (ADS)

Zainab Nik Azizan, Nik; Majid, Taksiah A.; Nazri, Fadzli Mohamed; Maity, Damodar; Abdullah, Junaidah

2018-03-01

This paper discovers the incremental dynamic analysis (IDA) of concrete gravity dam under single and repeated earthquake loadings to identify the limit state of the dam. Seven ground motions with horizontal and vertical direction as seismic input considered in the nonlinear dynamic analysis based on the real repeated earthquake in the worldwide. All the ground motions convert to respond spectrum and scaled according to the developed elastic respond spectrum in order to match the characteristic of the ground motion to the soil type. The scaled was depends on the fundamental period, T1 of the dam. The Koyna dam has been selected as a case study for the purpose of the analysis by assuming that no sliding and rigid foundation, has been estimated. IDA curves for Koyna dam developed for single and repeated ground motions and the performance level of the dam identifies. The IDA curve of repeated ground motion shown stiffer rather than single ground motion. The ultimate state displacement for a single event is 45.59mm and decreased to 39.33mm under repeated events which are decreased about 14%. This showed that the performance level of the dam based on seismic loadings depend on ground motion pattern.

A switched systems approach to image-based estimation

NASA Astrophysics Data System (ADS)

Parikh, Anup

With the advent of technological improvements in imaging systems and computational resources, as well as the development of image-based reconstruction techniques, it is necessary to understand algorithm performance when subject to real world conditions. Specifically, this dissertation focuses on the stability and performance of a class of image-based observers in the presence of intermittent measurements, caused by e.g., occlusions, limited FOV, feature tracking losses, communication losses, or finite frame rates. Observers or filters that are exponentially stable under persistent observability may have unbounded error growth during intermittent sensing, even while providing seemingly accurate state estimates. In Chapter 3, dwell time conditions are developed to guarantee state estimation error convergence to an ultimate bound for a class of observers while undergoing measurement loss. Bounds are developed on the unstable growth of the estimation errors during the periods when the object being tracked is not visible. A Lyapunov-based analysis for the switched system is performed to develop an inequality in terms of the duration of time the observer can view the moving object and the duration of time the object is out of the field of view. In Chapter 4, a motion model is used to predict the evolution of the states of the system while the object is not visible. This reduces the growth rate of the bounding function to an exponential and enables the use of traditional switched systems Lyapunov analysis techniques. The stability analysis results in an average dwell time condition to guarantee state error convergence with a known decay rate. In comparison with the results in Chapter 3, the estimation errors converge to zero rather than a ball, with relaxed switching conditions, at the cost of requiring additional information about the motion of the feature. In some applications, a motion model of the object may not be available. Numerous adaptive techniques have been developed to compensate for unknown parameters or functions in system dynamics; however, persistent excitation (PE) conditions are typically required to ensure parameter convergence, i.e., learning. Since the motion model is needed in the predictor, model learning is desired; however, PE is difficult to insure a priori and infeasible to check online for nonlinear systems. Concurrent learning (CL) techniques have been developed to use recorded data and a relaxed excitation condition to ensure convergence. In CL, excitation is only required for a finite period of time, and the recorded data can be checked to determine if it is sufficiently rich. However, traditional CL requires knowledge of state derivatives, which are typically not measured and require extensive filter design and tuning to develop satisfactory estimates. In Chapter 5 of this dissertation, a novel formulation of CL is developed in terms of an integral (ICL), removing the need to estimate state derivatives while preserving parameter convergence properties. Using ICL, an estimator is developed in Chapter 6 for simultaneously estimating the pose of an object as well as learning a model of its motion for use in a predictor when the object is not visible. A switched systems analysis is provided to demonstrate the stability of the estimation and prediction with learning scheme. Dwell time conditions as well as excitation conditions are developed to ensure estimation errors converge to an arbitrarily small bound. Experimental results are provided to illustrate the performance of each of the developed estimation schemes. The dissertation concludes with a discussion of the contributions and limitations of the developed techniques, as well as avenues for future extensions.

Magnitude Estimation for Large Earthquakes from Borehole Recordings

NASA Astrophysics Data System (ADS)

Eshaghi, A.; Tiampo, K. F.; Ghofrani, H.; Atkinson, G.

2012-12-01

We present a simple and fast method for magnitude determination technique for earthquake and tsunami early warning systems based on strong ground motion prediction equations (GMPEs) in Japan. This method incorporates borehole strong motion records provided by the Kiban Kyoshin network (KiK-net) stations. We analyzed strong ground motion data from large magnitude earthquakes (5.0 ≤ M ≤ 8.1) with focal depths < 50 km and epicentral distances of up to 400 km from 1996 to 2010. Using both peak ground acceleration (PGA) and peak ground velocity (PGV) we derived GMPEs in Japan. These GMPEs are used as the basis for regional magnitude determination. Predicted magnitudes from PGA values (Mpga) and predicted magnitudes from PGV values (Mpgv) were defined. Mpga and Mpgv strongly correlate with the moment magnitude of the event, provided sufficient records for each event are available. The results show that Mpgv has a smaller standard deviation in comparison to Mpga when compared with the estimated magnitudes and provides a more accurate early assessment of earthquake magnitude. We test this new method to estimate the magnitude of the 2011 Tohoku earthquake and we present the results of this estimation. PGA and PGV from borehole recordings allow us to estimate the magnitude of this event 156 s and 105 s after the earthquake onset, respectively. We demonstrate that the incorporation of borehole strong ground-motion records immediately available after the occurrence of large earthquakes significantly increases the accuracy of earthquake magnitude estimation and the associated improvement in earthquake and tsunami early warning systems performance. Moment magnitude versus predicted magnitude (Mpga and Mpgv).

Modeling of earthquake ground motion in the frequency domain

NASA Astrophysics Data System (ADS)

Thrainsson, Hjortur

In recent years, the utilization of time histories of earthquake ground motion has grown considerably in the design and analysis of civil structures. It is very unlikely, however, that recordings of earthquake ground motion will be available for all sites and conditions of interest. Hence, there is a need for efficient methods for the simulation and spatial interpolation of earthquake ground motion. In addition to providing estimates of the ground motion at a site using data from adjacent recording stations, spatially interpolated ground motions can also be used in design and analysis of long-span structures, such as bridges and pipelines, where differential movement is important. The objective of this research is to develop a methodology for rapid generation of horizontal earthquake ground motion at any site for a given region, based on readily available source, path and site characteristics, or (sparse) recordings. The research includes two main topics: (i) the simulation of earthquake ground motion at a given site, and (ii) the spatial interpolation of earthquake ground motion. In topic (i), models are developed to simulate acceleration time histories using the inverse discrete Fourier transform. The Fourier phase differences, defined as the difference in phase angle between adjacent frequency components, are simulated conditional on the Fourier amplitude. Uniformly processed recordings from recent California earthquakes are used to validate the simulation models, as well as to develop prediction formulas for the model parameters. The models developed in this research provide rapid simulation of earthquake ground motion over a wide range of magnitudes and distances, but they are not intended to replace more robust geophysical models. In topic (ii), a model is developed in which Fourier amplitudes and Fourier phase angles are interpolated separately. A simple dispersion relationship is included in the phase angle interpolation. The accuracy of the interpolation model is assessed using data from the SMART-1 array in Taiwan. The interpolation model provides an effective method to estimate ground motion at a site using recordings from stations located up to several kilometers away. Reliable estimates of differential ground motion are restricted to relatively limited ranges of frequencies and inter-station spacings.

Method and system for non-linear motion estimation

NASA Technical Reports Server (NTRS)

Lu, Ligang (Inventor)

2011-01-01

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Regional Earthquake Shaking and Loss Estimation

NASA Astrophysics Data System (ADS)

Sesetyan, K.; Demircioglu, M. B.; Zulfikar, C.; Durukal, E.; Erdik, M.

2009-04-01

This study, conducted under the JRA-3 component of the EU NERIES Project, develops a methodology and software (ELER) for the rapid estimation of earthquake shaking and losses in the Euro-Mediterranean region. This multi-level methodology developed together with researchers from Imperial College, NORSAR and ETH-Zurich is capable of incorporating regional variability and sources of uncertainty stemming from ground motion predictions, fault finiteness, site modifications, inventory of physical and social elements subjected to earthquake hazard and the associated vulnerability relationships. GRM Risk Management, Inc. of Istanbul serves as sub-contractor tor the coding of the ELER software. The methodology encompasses the following general steps: 1. Finding of the most likely location of the source of the earthquake using regional seismotectonic data base and basic source parameters, and if and when possible, by the estimation of fault rupture parameters from rapid inversion of data from on-line stations. 2. Estimation of the spatial distribution of selected ground motion parameters through region specific ground motion attenuation relationships and using shear wave velocity distributions.(Shake Mapping) 4. Incorporation of strong ground motion and other empirical macroseismic data for the improvement of Shake Map 5. Estimation of the losses (damage, casualty and economic) at different levels of sophistication (0, 1 and 2) that commensurate with the availability of inventory of human built environment (Loss Mapping) Both Level 0 (similar to PAGER system of USGS) and Level 1 analyses of the ELER routine are based on obtaining intensity distributions analytically and estimating total number of casualties and their geographic distribution either using regionally adjusted intensity-casualty or magnitude-casualty correlations (Level 0) of using regional building inventory data bases (Level 1). Level 0 analysis is similar to the PAGER system being developed by USGS. For given basis source parameters the intensity distributions can be computed using: a)Regional intensity attenuation relationships, b)Intensity correlations with attenuation relationship based PGV, PGA, and Spectral Amplitudes and, c)Intensity correlations with synthetic Fourier Amplitude Spectrum. In Level 1 analysis EMS98 based building vulnerability relationships are used for regional estimates of building damage and the casualty distributions. Results obtained from pilot applications of the Level 0 and Level 1 analysis modes of the ELER software to the 1999 M 7.4 Kocaeli, 1995 M 6.1 Dinar, and 2007 M 5.4 Bingol earthquakes in terms of ground shaking and losses are presented and comparisons with the observed losses are made. The regional earthquake shaking and loss information is intented for dissemination in a timely manner to related agencies for the planning and coordination of the post-earthquake emergency response. However the same software can also be used for scenario earthquake loss estimation and related Monte-Carlo type simulations.

SU-G-JeP3-04: Estimating 4D CBCT from Prior Information and Extremely Limited Angle Projections Using Structural PCA and Weighted Free-Form Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, W; Yin, F; Zhang, Y

Purpose: To investigate the feasibility of using structure-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and a free-form deformation (GMM-FD) technique, using data fidelity constraint and the deformation energy minimization. In thismore » study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Results: Among 6 different XCAT scenarios corresponding to respirational and anatomical changes from planning CT to on-board using single 30° on-board projections, the VPD/COMS for SMM-WFD was reduced to 10.64±3.04%/1.20±0.45mm from 21.72±9.24%/1.80±0.53mm for GMM-FD. Using 15° orthogonal projections, the VPD/COMS was further reduced to 1.91±0.86%/0.31±0.42mm based on SMM-WFD. Conclusion: Compared to GMM-FD technique, the SMM-WFD technique can substantially improve the 4D-CBCT estimation accuracy using extremely small scan angles to provide ultra-fast 4D verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.« less

Proper-motion Study of the Magellanic Clouds Using SPM Material

NASA Astrophysics Data System (ADS)

Vieira, Katherine; Girard, Terrence M.; van Altena, William F.; Zacharias, Norbert; Casetti-Dinescu, Dana I.; Korchagin, Vladimir I.; Platais, Imants; Monet, David G.; López, Carlos E.; Herrera, David; Castillo, Danilo J.

2010-12-01

Absolute proper motions are determined for stars and galaxies to V = 17.5 over a 450 deg2 area that encloses both Magellanic Clouds. The proper motions are based on photographic and CCD observations of the Yale/San Juan Southern Proper Motion program, which span a baseline of 40 years. Multiple, local relative proper-motion measures are combined in an overlap solution using photometrically selected Galactic disk stars to define a global relative system that is then transformed to absolute using external galaxies and Hipparcos stars to tie into the ICRS. The resulting catalog of 1.4 million objects is used to derive the mean absolute proper motions of the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC); (μαcos δ, μδ)LMC = (1.89, + 0.39) ± (0.27, 0.27) masyr-1 and (μαcos δ, μδ)SMC = (0.98, - 1.01) ± (0.30, 0.29) masyr-1. These mean motions are based on best-measured samples of 3822 LMC stars and 964 SMC stars. A dominant portion (0.25 mas yr-1) of the formal errors is due to the estimated uncertainty in the inertial system of the Hipparcos Catalog stars used to anchor the bright end of our proper motion measures. A more precise determination can be made for the proper motion of the SMC relative to the LMC; (μαcos δ, μδ)SMC-LMC = (-0.91, - 1.49) ± (0.16, 0.15) masyr-1. This differential value is combined with measurements of the proper motion of the LMC taken from the literature to produce new absolute proper-motion determinations for the SMC, as well as an estimate of the total velocity difference of the two clouds to within ±54 km s-1. The absolute proper-motion results are consistent with the Clouds' orbits being marginally bound to the Milky Way, albeit on an elongated orbit. The inferred relative velocity between the Clouds places them near their binding energy limit and, thus, no definitive conclusion can be made as to whether or not the Clouds are bound to one another.

Optical Flow in a Smart Sensor Based on Hybrid Analog-Digital Architecture

PubMed Central

Guzmán, Pablo; Díaz, Javier; Agís, Rodrigo; Ros, Eduardo

2010-01-01

The purpose of this study is to develop a motion sensor (delivering optical flow estimations) using a platform that includes the sensor itself, focal plane processing resources, and co-processing resources on a general purpose embedded processor. All this is implemented on a single device as a SoC (System-on-a-Chip). Optical flow is the 2-D projection into the camera plane of the 3-D motion information presented at the world scenario. This motion representation is widespread well-known and applied in the science community to solve a wide variety of problems. Most applications based on motion estimation require work in real-time; hence, this restriction must be taken into account. In this paper, we show an efficient approach to estimate the motion velocity vectors with an architecture based on a focal plane processor combined on-chip with a 32 bits NIOS II processor. Our approach relies on the simplification of the original optical flow model and its efficient implementation in a platform that combines an analog (focal-plane) and digital (NIOS II) processor. The system is fully functional and is organized in different stages where the early processing (focal plane) stage is mainly focus to pre-process the input image stream to reduce the computational cost in the post-processing (NIOS II) stage. We present the employed co-design techniques and analyze this novel architecture. We evaluate the system’s performance and accuracy with respect to the different proposed approaches described in the literature. We also discuss the advantages of the proposed approach as well as the degree of efficiency which can be obtained from the focal plane processing capabilities of the system. The final outcome is a low cost smart sensor for optical flow computation with real-time performance and reduced power consumption that can be used for very diverse application domains. PMID:22319283

Optimization of yttrium-90 PET for simultaneous PET/MR imaging: A phantom study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eldib, Mootaz

2016-08-15

Purpose: Positron emission tomography (PET) imaging of yttrium-90 in the liver post radioembolization has been shown useful for personalized dosimetry calculations and evaluation of extrahepatic deposition. The purpose of this study was to quantify the benefits of several MR-based data correction approaches offered by using a combined PET/MR system to improve Y-90 PET imaging. In particular, the feasibility of motion and partial volume corrections were investigated in a controlled phantom study. Methods: The ACR phantom was filled with an initial concentration of 8 GBq of Y-90 solution resulting in a contrast of 10:1 between the hot cylinders and the background.more » Y-90 PET motion correction through motion estimates from MR navigators was evaluated by using a custom-built motion stage that simulated realistic amplitudes of respiration-induced liver motion. Finally, the feasibility of an MR-based partial volume correction method was evaluated using a wavelet decomposition approach. Results: Motion resulted in a large (∼40%) loss of contrast recovery for the 8 mm cylinder in the phantom, but was corrected for after MR-based motion correction was applied. Partial volume correction improved contrast recovery by 13% for the 8 mm cylinder. Conclusions: MR-based data correction improves Y-90 PET imaging on simultaneous PET/MR systems. Assessment of these methods must be studied further in the clinical setting.« less

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Ionospheric Correction of InSAR for Accurate Ice Motion Mapping at High Latitudes

NASA Astrophysics Data System (ADS)

Liao, H.; Meyer, F. J.

2016-12-01

Monitoring the motion of the large ice sheets is of great importance for determining ice mass balance and its contribution to sea level rise. Recently the first comprehensive ice motion of the Greenland and the Antarctica have been generated with InSAR. However, these studies have indicated that the performance of InSAR-based ice motion mapping is limited by the presence of the ionosphere. This is particularly true at high latitudes and for low-frequency SAR data. Filter-based and empirical methods (e.g., removing polynomials), which have often been used to mitigate ionospheric effects, are often ineffective in these areas due to the typically strong spatial variability of ionospheric phase delay in high latitudes and due to the risk of removing true deformation signals from the observations. In this study, we will first present an outline of our split-spectrum InSAR-based ionospheric correction approach and particularly highlight how our method improves upon published techniques, such as the multiple sub-band approach to boost estimation accuracy as well as advanced error correction and filtering algorithms. We applied our work flow to a large number of ionosphere-affected dataset over the large ice sheets to estimate the benefit of ionospheric correction on ice motion mapping accuracy. Appropriate test sites over Greenland and the Antarctic have been chosen through cooperation with authors (UW, Ian Joughin) of previous ice motion studies. To demonstrate the magnitude of ionospheric noise and to showcase the performance of ionospheric correction, we will show examples of ionospheric-affected InSAR data and our ionosphere corrected result for comparison in visual. We also compared the corrected phase data to known ice velocity fields quantitatively for the analyzed areas from experts in ice velocity mapping. From our studies we found that ionospheric correction significantly reduces biases in ice velocity estimates and boosts accuracy by a factor that depends on a set of system (range bandwidth, temporal and spatial baseline) and processing parameters (e.g., filtering strength and sub-band configuration). A case study in Greenland is attached below.

Ground Motion in Central Mexico: A Comprehensive Analysis

NASA Astrophysics Data System (ADS)

Ramirez-Guzman, L.; Juarez, A.; Rábade, S.; Aguirre, J.; Bielak, J.

2015-12-01

This study presents a detailed analysis of the ground motion in Central Mexico based on numerical simulations, as well as broadband and strong ground motion records. We describe and evaluate a velocity model for Central Mexico derived from noise and regional earthquake cross-correlations, which is used throughout this research to estimate the ground motion in the region. The 3D crustal model includes a geotechnical structure of the Valley of Mexico (VM), subduction zone geometry, and 3D velocity distributions. The latter are based on more than 200 low magnitude (Mw < 4.5) earthquakes and two years of noise recordings. We emphasize the analysis on the ground motion in the Valley of Mexico originating from intra-slab deep events and temblors located along the Pacific coast. Also, we quantify the effects Trans-Mexican Volcanic Belt (TMVB) and the low-velocity deposits on the ground motion. The 3D octree-based finite element wave propagation computations, valid up to 1 Hz, reveal that the inclusion of a basin with a structure as complex as the Valley of Mexico dramatically enhances the regional effects induced by the TMVB. Moreover, the basin not only produces ground motion amplification and anomalous duration, but it also favors the energy focusing into zones of Mexico City where structures typically undergo high levels of damage.

Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Suorsa, Raymond; Sridhar, Banavar

1991-01-01

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

Annualized earthquake loss estimates for California and their sensitivity to site amplification

USGS Publications Warehouse

Chen, Rui; Jaiswal, Kishor; Bausch, D; Seligson, H; Wills, C.J.

2016-01-01

Input datasets for annualized earthquake loss (AEL) estimation for California were updated recently by the scientific community, and include the National Seismic Hazard Model (NSHM), site‐response model, and estimates of shear‐wave velocity. Additionally, the Federal Emergency Management Agency’s loss estimation tool, Hazus, was updated to include the most recent census and economic exposure data. These enhancements necessitated a revisit to our previous AEL estimates and a study of the sensitivity of AEL estimates subjected to alternate inputs for site amplification. The NSHM ground motions for a uniform site condition are modified to account for the effect of local near‐surface geology. The site conditions are approximated in three ways: (1) by VS30 (time‐averaged shear‐wave velocity in the upper 30 m) value obtained from a geology‐ and topography‐based map consisting of 15 VS30 groups, (2) by site classes categorized according to National Earthquake Hazards Reduction Program (NEHRP) site classification, and (3) by a uniform NEHRP site class D. In case 1, ground motions are amplified using the Seyhan and Stewart (2014) semiempirical nonlinear amplification model. In cases 2 and 3, ground motions are amplified using the 2014 version of the NEHRP site amplification factors, which are also based on the Seyhan and Stewart model but are approximated to facilitate their use for building code applications. Estimated AELs are presented at multiple resolutions, starting with the state level assessment and followed by detailed assessments for counties, metropolitan statistical areas (MSAs), and cities. AEL estimate at the state level is ∼$3.7  billion, 70% of which is contributed from Los Angeles–Long Beach–Santa Ana, San Francisco–Oakland–Fremont, and Riverside–San Bernardino–Ontario MSAs. The statewide AEL estimate is insensitive to alternate assumptions of site amplification. However, we note significant differences in AEL estimates among the three sensitivity cases for smaller geographic units.

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters.

PubMed

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-09-07

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers.

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

Visual perception and interception of falling objects: a review of evidence for an internal model of gravity.

PubMed

Zago, Myrka; Lacquaniti, Francesco

2005-09-01

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. However, there are limitations in the visual system that raise questions about the general validity of these theories. Most notably, vision is poorly sensitive to arbitrary accelerations. How then does the brain deal with the motion of objects accelerated by Earth's gravity? Here we review evidence in favor of the view that the brain makes the best estimate about target motion based on visually measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from the expected kinetics in the Earth's gravitational field.

On modeling animal movements using Brownian motion with measurement error.

PubMed

Pozdnyakov, Vladimir; Meyer, Thomas; Wang, Yu-Bo; Yan, Jun

2014-02-01

Modeling animal movements with Brownian motion (or more generally by a Gaussian process) has a long tradition in ecological studies. The recent Brownian bridge movement model (BBMM), which incorporates measurement errors, has been quickly adopted by ecologists because of its simplicity and tractability. We discuss some nontrivial properties of the discrete-time stochastic process that results from observing a Brownian motion with added normal noise at discrete times. In particular, we demonstrate that the observed sequence of random variables is not Markov. Consequently the expected occupation time between two successively observed locations does not depend on just those two observations; the whole path must be taken into account. Nonetheless, the exact likelihood function of the observed time series remains tractable; it requires only sparse matrix computations. The likelihood-based estimation procedure is described in detail and compared to the BBMM estimation.

Side-information-dependent correlation channel estimation in hash-based distributed video coding.

PubMed

Deligiannis, Nikos; Barbarien, Joeri; Jacobs, Marc; Munteanu, Adrian; Skodras, Athanassios; Schelkens, Peter

2012-04-01

In the context of low-cost video encoding, distributed video coding (DVC) has recently emerged as a potential candidate for uplink-oriented applications. This paper builds on a concept of correlation channel (CC) modeling, which expresses the correlation noise as being statistically dependent on the side information (SI). Compared with classical side-information-independent (SII) noise modeling adopted in current DVC solutions, it is theoretically proven that side-information-dependent (SID) modeling improves the Wyner-Ziv coding performance. Anchored in this finding, this paper proposes a novel algorithm for online estimation of the SID CC parameters based on already decoded information. The proposed algorithm enables bit-plane-by-bit-plane successive refinement of the channel estimation leading to progressively improved accuracy. Additionally, the proposed algorithm is included in a novel DVC architecture that employs a competitive hash-based motion estimation technique to generate high-quality SI at the decoder. Experimental results corroborate our theoretical gains and validate the accuracy of the channel estimation algorithm. The performance assessment of the proposed architecture shows remarkable and consistent coding gains over a germane group of state-of-the-art distributed and standard video codecs, even under strenuous conditions, i.e., large groups of pictures and highly irregular motion content.

Applicability of source scaling relations for crustal earthquakes to estimation of the ground motions of the 2016 Kumamoto earthquake

NASA Astrophysics Data System (ADS)

Irikura, Kojiro; Miyakoshi, Ken; Kamae, Katsuhiro; Yoshida, Kunikazu; Somei, Kazuhiro; Kurahashi, Susumu; Miyake, Hiroe

2017-01-01

A two-stage scaling relationship of the source parameters for crustal earthquakes in Japan has previously been constructed, in which source parameters obtained from the results of waveform inversion of strong motion data are combined with parameters estimated based on geological and geomorphological surveys. A three-stage scaling relationship was subsequently developed to extend scaling to crustal earthquakes with magnitudes greater than M w 7.4. The effectiveness of these scaling relationships was then examined based on the results of waveform inversion of 18 recent crustal earthquakes ( M w 5.4-6.9) that occurred in Japan since the 1995 Hyogo-ken Nanbu earthquake. The 2016 Kumamoto earthquake, with M w 7.0, was one of the largest earthquakes to occur since dense and accurate strong motion observation networks, such as K-NET and KiK-net, were deployed after the 1995 Hyogo-ken Nanbu earthquake. We examined the applicability of the scaling relationships of the source parameters of crustal earthquakes in Japan to the 2016 Kumamoto earthquake. The rupture area and asperity area were determined based on slip distributions obtained from waveform inversion of the 2016 Kumamoto earthquake observations. We found that the relationship between the rupture area and the seismic moment for the 2016 Kumamoto earthquake follows the second-stage scaling within one standard deviation ( σ = 0.14). The ratio of the asperity area to the rupture area for the 2016 Kumamoto earthquake is nearly the same as ratios previously obtained for crustal earthquakes. Furthermore, we simulated the ground motions of this earthquake using a characterized source model consisting of strong motion generation areas (SMGAs) based on the empirical Green's function (EGF) method. The locations and areas of the SMGAs were determined through comparison between the synthetic ground motions and observed motions. The sizes of the SMGAs were nearly coincident with the asperities with large slip. The synthetic ground motions obtained using the EGF method agree well with the observed motions in terms of acceleration, velocity, and displacement within the frequency range of 0.3-10 Hz. These findings indicate that the 2016 Kumamoto earthquake is a standard event that follows the scaling relationship of crustal earthquakes in Japan.

Terrain Measurement with SAR/InSAR

NASA Astrophysics Data System (ADS)

Li, Deren; Liao, Mingsheng; Balz, Timo; Zhang, Lu; Yang, Tianliang

2016-08-01

Terrain measurement and surface motion estimation are the most important applications for commercial and scientific SAR missions. In Dragon-3, we worked on these applications, especially regarding DEM generation, surface motion estimation with SAR time- series for urban subsidence monitoring and landslide motion estimation, as well as developing tomographic SAR processing methods in urban areas.

New evidence for the Hawaiian hotspot plume motion since the Eocene

NASA Astrophysics Data System (ADS)

Parés, Josep M.; Moore, Ted C.

2005-09-01

A thick mound of fossiliferous sediments, reflecting high biogenic productivity at the Equator can be used to determine latitudinal motion of the Pacific lithospheric plate. Plate motion estimates based on the latitudinal movement of Equatorial facies are independent of paleomagnetic data and hotspot tracks and thus permit further testing of kinematic models. We have determined the northward motion of the Pacific Plate for the last 53 Myr based on the position of the paleoequator as shown by Equatorial sediment facies. Between 26 and 69 DSDP and ODP Sites sample the past 53 Myr in the tropical Pacific. Based on the mapped patterns of accumulation rates in these sites, we were able not only to determine the position of the paleoequator but also to estimate the Equatorial great circle and hence the relative position of the spin axis since the early Eocene. The northward motion of the Pacific Plate inferred from the change in latitude of dated Hawaiian Chain seamounts relative to the Hawaiian hotspot is consistently higher than that deduced from the analyses of Equatorial sediment facies. Such a difference results from a latitudinal shift of the Hawaiian hotspot during the last 53 Myr. All together, our observations and recent paleomagnetic results from the Detroit, Nintoku and Koko seamounts [J.A. Tarduno, R.A. Duncan, D.W. Scholl, R.D. Cottrell, B., Steinberger, T. Thordarson, B.C. Kerr, C.R. Neal, F.A. Frey, M. Torii, M., C. Carvallo. The Emperor Seamounts: Southward motion of the Hawaiian hotspot plume in Earth's mantle. Science 301 (2003) 1064-1069.] [1] are consistent with a progressive southward motion of the Hawaiian mantle plume since the Late Cretaceous. Our results suggest that the Hawaiian hotspot moved at ˜32 mm/yr to the SE during the past 43 million years and that the Pacific Plate moved ˜12° northward since 53 Ma at an average rate of 25 mm/yr.

Global Plate Motions Relative to the Hotspots since 48 Ma B.P. from Simultaneous Inversion of Hotspot Tracks in the Pacific, Indian, and Atlantic Oceans Constrained to Consistency with Known Relative Plate Motions

NASA Astrophysics Data System (ADS)

Gordon, R. G.; Koivisto, E. A. L.

2016-12-01

A fundamental problem of global tectonics and paleomagnetism is determining what part of apparent polar wander is due to plate motion and what part is due to true polar wander. One approach for separating these is available if global hotspots can be used as a reference frame approximately fixed with respect to the deep mantle. Some other workers have used a hotspot reference based only on tracks in the Atlantic and Indian Oceans, and some have used reference frames with moving hotspots and many adjustable parameters. In sharp contrast to the assumptions made in these other works, our recent results demonstrate that there is no significant motion between the Pacific and Indo-Atlantic hotspots since 48 Ma B.P. (lower bound of zero and upper bound of 8-13 mm/yr [Koivisto et al., 2014]). Corrected methodologies combined with cumulative improvements in the age progression along the hotspot tracks, the geomagnetic reversal time scale, and relative plate reconstructions lead to significantly lower rates of motion between hotspots than found in prior studies. Building on our prior results, here we present a globally self-consistent estimate of plate motions relative to the hotspots for the past 48 million years from inversions to fit simultaneously the tracks of the Hawaiian, Louisville, Tristan da Cunha, Réunion, and Iceland hotspots constrained to consistency with known relative plate motions. Each finite rotation is estimated for an age corresponding to a key magnetic anomaly used in plate reconstructions. The new set of plate reconstructions presented here provides a firm basis for estimating absolute plate motions for the past 48 million years and, in particular, can be used to separate paleomagnetically determined apparent polar wander into the part due to plate motion and the part due to true polar wander. Implications for true polar wander since the age of the Hawaiian-Emperor Bend will be discussed.

SU-F-J-138: An Extension of PCA-Based Respiratory Deformation Modeling Via Multi-Linear Decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Pitsianis, N

Purpose: To address and lift the limited degree of freedom (DoF) of globally bilinear motion components such as those based on principal components analysis (PCA), for encoding and modeling volumetric deformation motion. Methods: We provide a systematic approach to obtaining a multi-linear decomposition (MLD) and associated motion model from deformation vector field (DVF) data. We had previously introduced MLD for capturing multi-way relationships between DVF variables, without being restricted by the bilinear component format of PCA-based models. PCA-based modeling is commonly used for encoding patient-specific deformation as per planning 4D-CT images, and aiding on-board motion estimation during radiotherapy. However, themore » bilinear space-time decomposition inherently limits the DoF of such models by the small number of respiratory phases. While this limit is not reached in model studies using analytical or digital phantoms with low-rank motion, it compromises modeling power in the presence of relative motion, asymmetries and hysteresis, etc, which are often observed in patient data. Specifically, a low-DoF model will spuriously couple incoherent motion components, compromising its adaptability to on-board deformation changes. By the multi-linear format of extracted motion components, MLD-based models can encode higher-DoF deformation structure. Results: We conduct mathematical and experimental comparisons between PCA- and MLD-based models. A set of temporally-sampled analytical trajectories provides a synthetic, high-rank DVF; trajectories correspond to respiratory and cardiac motion factors, including different relative frequencies and spatial variations. Additionally, a digital XCAT phantom is used to simulate a lung lesion deforming incoherently with respect to the body, which adheres to a simple respiratory trend. In both cases, coupling of incoherent motion components due to a low model DoF is clearly demonstrated. Conclusion: Multi-linear decomposition can enable decoupling of distinct motion factors in high-rank DVF measurements. This may improve motion model expressiveness and adaptability to on-board deformation, aiding model-based image reconstruction for target verification. NIH Grant No. R01-184173.« less

A comparative study of ground motion hybrid simulations and the modified NGA ground motion predictive equations for directivity and its application to the the Marmara Sea region (Turkey)

NASA Astrophysics Data System (ADS)

Pischiutta, M.; Akinci, A.; Spagnuolo, E.; Taroni, M.; Herrero, A.; Aochi, H.

2016-12-01

We have simulated strong ground motions for two Mw>7.0 rupture scenarios on the North Anatolian Fault, in the Marmara Sea within 10-20 km from Istanbul. This city is characterized by one of the highest levels of seismic risk in Europe and the Mediterranean region. The increased risk in Istanbul is due to eight destructive earthquakes that ruptured the fault system and left a seismic gap at the western portion of the 1000km-long North Anatolian Fault Zone. To estimate the ground motion characteristics and its variability in the region we have simulated physics-based rupture scenarios, producing hybrid broadband time histories. We have merged two simulation techniques: a full 3D wave propagation method to generate low-frequency seismograms (Aochi and Ulrich, 2015) and the stochastic finite-fault model approach based on a dynamic corner frequency (Motazedian and Atkinson, 2005) to simulate high-frequency seismograms (Akinci et al., 2016, submitted to BSSA, 2016). They are merged to compute realistic broadband hybrid time histories. The comparison of ground motion intensity measures (PGA, PGV, SA) resulting from our simulations with those predicted by the recent Ground Motion Prediction Equations (GMPEs) in the region (Boore & Atkinson, 2008; Chiou & Young, 2008; Akkar & Bommer, 2010; Akkar & Cagnan, 2010) seems to indicate that rupture directivity and super-shear rupture effects affect the ground motion in the Marmara Sea region. In order to account for the rupture directivity we improve the comparison using the directivity predictor proposed by Spudich & Chiu (2008). This study highlights the importance of the rupture directivity for the hazard estimation in the Marmara Sea region, especially for the city of Istanbul.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henderson, C. B.; Gould, A.; Gaudi, B. S.

The mass of the lenses giving rise to Galactic microlensing events can be constrained by measuring the relative lens-source proper motion and lens flux. The flux of the lens can be separated from that of the source, companions to the source, and unrelated nearby stars with high-resolution images taken when the lens and source are spatially resolved. For typical ground-based adaptive optics (AO) or space-based observations, this requires either inordinately long time baselines or high relative proper motions. We provide a list of microlensing events toward the Galactic bulge with high relative lens-source proper motion that are therefore good candidatesmore » for constraining the lens mass with future high-resolution imaging. We investigate all events from 2004 to 2013 that display detectable finite-source effects, a feature that allows us to measure the proper motion. In total, we present 20 events with μ ≳ 8 mas yr{sup –1}. Of these, 14 were culled from previous analyses while 6 are new, including OGLE-2004-BLG-368, MOA-2005-BLG-36, OGLE-2012-BLG-0211, OGLE-2012-BLG-0456, MOA-2012-BLG-532, and MOA-2013-BLG-029. In ≲12 yr from the time of each event the lens and source of each event will be sufficiently separated for ground-based telescopes with AO systems or space telescopes to resolve each component and further characterize the lens system. Furthermore, for the most recent events, comparison of the lens flux estimates from images taken immediately to those estimated from images taken when the lens and source are resolved can be used to empirically check the robustness of the single-epoch method currently being used to estimate lens masses for many events.« less

Comparison of hydrological and GRACE-based excitation functions of polar motion in the seasonal spectral band

NASA Astrophysics Data System (ADS)

Nastula, J.; Kolaczek, B.; Salstein, D. A.

2008-04-01

Understanding changes in the global balance of the Earths angular momentum due to the mass redistribution of geophysical fluids is needed to explain the observed polar motion. The impact of continental hydrologic signals, from land water, snow, and ice, on polar motion excitation (hydrological angular momentum-HAM), is still inadequately known. Although estimates of HAM have been made from several models of global hydrology based upon the observed distribution of surface water, snow, and soil moisture, the relatively sparse observation network and the presence of errors in the data and the geophysical fluid models preclude a full understanding of the HAM influence on polar motion variations. Recently the GRACE mission monitoring Earths time variable gravity field has allowed us to determine the mass term of polar motion excitation functions and compare them with the mass term derivable as a residual from the geodetic excitation functions and geophysical fluid motion terms on seasonal time scales. Differences between these mass terms in the years 2004 - 2005.5 are still on the order of 20 mas. Besides the overall mass excitation of polar motion comparisons with GRACE (RL04-release), we also intercompare the non-atmospheric, non-oceanic signals in the mass term of geodetic polar motion excitation with hydrological excitation of polar motion.

Extended state observer-based motion synchronisation control for hybrid actuation system of large civil aircraft

NASA Astrophysics Data System (ADS)

Wang, Xingjian; Shi, Cun; Wang, Shaoping

2017-07-01

Hybrid actuation system with dissimilar redundant actuators, which is composed of a hydraulic actuator (HA) and an electro-hydrostatic actuator (EHA), has been applied on modern civil aircraft to improve the reliability. However, the force fighting problem arises due to different dynamic performances between HA and EHA. This paper proposes an extended state observer (ESO)-based motion synchronisation control method. To cope with the problem of unavailability of the state signals, the well-designed ESO is utilised to observe the HA and EHA state variables which are unmeasured. In particular, the extended state of ESO can estimate the lumped effect of the unknown external disturbances acting on the control surface, the nonlinear dynamics, uncertainties, and the coupling term between HA and EHA. Based on the observed states of ESO, motion synchronisation controllers are presented to make HA and EHA to simultaneously track the desired motion trajectories, which are generated by a trajectory generator. Additionally, the unknown disturbances and the coupling terms can be compensated by using the extended state of the proposed ESO. Finally, comparative simulation results indicate that the proposed ESO-based motion synchronisation controller can achieve great force fighting reduction between HA and EHA.

Event-by-Event Continuous Respiratory Motion Correction for Dynamic PET Imaging.

PubMed

Yu, Yunhan; Chan, Chung; Ma, Tianyu; Liu, Yaqiang; Gallezot, Jean-Dominique; Naganawa, Mika; Kelada, Olivia J; Germino, Mary; Sinusas, Albert J; Carson, Richard E; Liu, Chi

2016-07-01

Existing respiratory motion-correction methods are applied only to static PET imaging. We have previously developed an event-by-event respiratory motion-correction method with correlations between internal organ motion and external respiratory signals (INTEX). This method is uniquely appropriate for dynamic imaging because it corrects motion for each time point. In this study, we applied INTEX to human dynamic PET studies with various tracers and investigated the impact on kinetic parameter estimation. The use of 3 tracers-a myocardial perfusion tracer, (82)Rb (n = 7); a pancreatic β-cell tracer, (18)F-FP(+)DTBZ (n = 4); and a tumor hypoxia tracer, (18)F-fluoromisonidazole ((18)F-FMISO) (n = 1)-was investigated in a study of 12 human subjects. Both rest and stress studies were performed for (82)Rb. The Anzai belt system was used to record respiratory motion. Three-dimensional internal organ motion in high temporal resolution was calculated by INTEX to guide event-by-event respiratory motion correction of target organs in each dynamic frame. Time-activity curves of regions of interest drawn based on end-expiration PET images were obtained. For (82)Rb studies, K1 was obtained with a 1-tissue model using a left-ventricle input function. Rest-stress myocardial blood flow (MBF) and coronary flow reserve (CFR) were determined. For (18)F-FP(+)DTBZ studies, the total volume of distribution was estimated with arterial input functions using the multilinear analysis 1 method. For the (18)F-FMISO study, the net uptake rate Ki was obtained with a 2-tissue irreversible model using a left-ventricle input function. All parameters were compared with the values derived without motion correction. With INTEX, K1 and MBF increased by 10% ± 12% and 15% ± 19%, respectively, for (82)Rb stress studies. CFR increased by 19% ± 21%. For studies with motion amplitudes greater than 8 mm (n = 3), K1, MBF, and CFR increased by 20% ± 12%, 30% ± 20%, and 34% ± 23%, respectively. For (82)Rb rest studies, INTEX had minimal effect on parameter estimation. The total volume of distribution of (18)F-FP(+)DTBZ and Ki of (18)F-FMISO increased by 17% ± 6% and 20%, respectively. Respiratory motion can have a substantial impact on dynamic PET in the thorax and abdomen. The INTEX method using continuous external motion data substantially changed parameters in kinetic modeling. More accurate estimation is expected with INTEX. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.

PubMed

Joukov, Vladimir; Bonnet, Vincent; Karg, Michelle; Venture, Gentiane; Kulic, Dana

2018-02-01

This paper proposes a method to enable the use of non-intrusive, small, wearable, and wireless sensors to estimate the pose of the lower body during gait and other periodic motions and to extract objective performance measures useful for physiotherapy. The Rhythmic Extended Kalman Filter (Rhythmic-EKF) algorithm is developed to estimate the pose, learn an individualized model of periodic movement over time, and use the learned model to improve pose estimation. The proposed approach learns a canonical dynamical system model of the movement during online observation, which is used to accurately model the acceleration during pose estimation. The canonical dynamical system models the motion as a periodic signal. The estimated phase and frequency of the motion also allow the proposed approach to segment the motion into repetitions and extract useful features, such as gait symmetry, step length, and mean joint movement and variance. The algorithm is shown to outperform the extended Kalman filter in simulation, on healthy participant data, and stroke patient data. For the healthy participant marching dataset, the Rhythmic-EKF improves joint acceleration and velocity estimates over regular EKF by 40% and 37%, respectively, estimates joint angles with 2.4° root mean squared error, and segments the motion into repetitions with 96% accuracy.

Image and Video Quality Assessment Using LCD: Comparisons with CRT Conditions

NASA Astrophysics Data System (ADS)

Tourancheau, Sylvain; Callet, Patrick Le; Barba, Dominique

In this paper, the impact of display on quality assessment is addressed. Subjective quality assessment experiments have been performed on both LCD and CRT displays. Two sets of still images and two sets of moving pictures have been assessed using either an ACR or a SAMVIQ protocol. Altogether, eight experiments have been led. Results are presented and discussed, some differences are pointed out. Concerning moving pictures, these differences seem to be mainly due to LCD moving artefacts such as motion blur. LCD motion blur has been measured objectively and with psycho-physics experiments. A motion-blur metric based on the temporal characteristics of LCD can be defined. A prediction model have been then designed which predict the differences of perceived quality between CRT and LCD. This motion-blur-based model enables the estimation of perceived quality on LCD with respect to the perceived quality on CRT. Technical solutions to LCD motion blur can thus be evaluated on natural contents by this mean.

Automatic online and real-time tumour motion monitoring during stereotactic liver treatments on a conventional linac by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK)

NASA Astrophysics Data System (ADS)

Bertholet, Jenny; Toftegaard, Jakob; Hansen, Rune; Worm, Esben S.; Wan, Hanlin; Parikh, Parag J.; Weber, Britta; Høyer, Morten; Poulsen, Per R.

2018-03-01

The purpose of this study was to develop, validate and clinically demonstrate fully automatic tumour motion monitoring on a conventional linear accelerator by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK). COSMIK combines auto-segmentation of implanted fiducial markers in cone-beam computed tomography (CBCT) projections and intra-treatment kV images with simultaneous streaming of an external motion signal. A pre-treatment CBCT is acquired with simultaneous recording of the motion of an external marker block on the abdomen. The 3-dimensional (3D) marker motion during the CBCT is estimated from the auto-segmented positions in the projections and used to optimize an external correlation model (ECM) of internal motion as a function of external motion. During treatment, the ECM estimates the internal motion from the external motion at 20 Hz. KV images are acquired every 3 s, auto-segmented, and used to update the ECM for baseline shifts between internal and external motion. The COSMIK method was validated using Calypso-recorded internal tumour motion with simultaneous camera-recorded external motion for 15 liver stereotactic body radiotherapy (SBRT) patients. The validation included phantom experiments and simulations hereof for 12 fractions and further simulations for 42 fractions. The simulations compared the accuracy of COSMIK with ECM-based monitoring without model updates and with model updates based on stereoscopic imaging as well as continuous kilovoltage intrafraction monitoring (KIM) at 10 Hz without an external signal. Clinical real-time tumour motion monitoring with COSMIK was performed offline for 14 liver SBRT patients (41 fractions) and online for one patient (two fractions). The mean 3D root-mean-square error for the four monitoring methods was 1.61 mm (COSMIK), 2.31 mm (ECM without updates), 1.49 mm (ECM with stereoscopic updates) and 0.75 mm (KIM). COSMIK is the first combined kV/optical real-time motion monitoring method used clinically online on a conventional accelerator. COSMIK gives less imaging dose than KIM and is in addition applicable when the kV imager cannot be deployed such as during non-coplanar fields.

Wind estimates from cloud motions: Preliminary results from phases 1, 2, and 3 of an in situ aircraft verification experiment

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Shenk, W. E.; Skillman, W. C.

1975-01-01

Low level aircraft equipped with Inertial Navigation Systems (INS) were used to define the vertical extent and horizontal motion of a cloud and to measure the ambient wind field. A high level aircraft, also equipped with an INS, took photographs to describe the horizontal extent of the cloud field and to measure cloud motion. The aerial photographs were also used to make a positive identification in a satellite picture of the cloud observed by the low level aircraft. The experiment was conducted over the tropical oceans in the vicinity of Florida, Puerto Rico, Panama and in the Western Gulf of Mexico. Results for tropical cumulus clouds indicate excellent agreement between the cloud motion and the wind at the cloud base. The magnitude of the vector difference between the cloud motion and the cloud base wind is less than 1.3 m/sec for 67% of the cases with track lengths of 1 hour or longer. The cirrus cloud motions agreed best with the mean wind in the cloud layer with a vector difference of about 1.6 m/sec.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Short term evaluation of harvesting systems for ecosystem management

Treesearch

Michael D. Erickson; Penn Peters; Curt Hassler

1995-01-01

Continuous time/motion studies have traditionally been the basis for productivity estimates of timber harvesting systems. The detailed data from such studies permits the researcher or analyst to develop mathematical relationships based on stand, system, and stem attributes for describing machine cycle times. The resulting equation(s) allow the analyst to estimate...

SU-E-CAMPUS-T-02: Can Pre-Treatment 4DCT-Based Motion Margins Estimates Be Trusted for Proton Radiotherapy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seco, J; Koybasi, O; Mishra, P

2014-06-15

Purpose: Radiotherapy motion margins are generated using pre-treatment 4DCT data. The purpose of this study is to assess if pre-treatment 4DCT is sufficient in proton therapy to provide accurate estimate of motion margins. A dosimetric assessment is performed comparing pre-treatment margins with daily-customized margins. Methods: Gold fiducial markers implanted in lung tumors of patients were used to track the tumor. A spherical tumor of diameter 20 mm is inserted into a realistic digital respiratory phantom, where the tumor motion is based on real patient lung tumor trajectories recorded over multiple days. Using “Day 1” patient data, 100 ITVs were generatedmore » with 1 s interval between consecutive scan start times. Each ITV was made up by the union of 10 tumor positions obtained from 6 s scan time. Two ITV volumes were chosen for treatment planning: ITVmean-σ and ITVmean+σ. The delivered dose was computed on i) 10 phases forming the planning ITV (“10-phase” - simulating dose calculation based on 4DCT) and ii) 50 phantoms produced from 100 s of data from any other day with tumor positions sampled every 2 s (“dynamic” - simulating the dose that would actually be delivered). Results: For similar breathing patterns between “Day 1” and any other “Day N(>1)”, the 95% volume coverage (D95) for “dynamic” case was 8.13% lower than the “10-phase” case for ITVmean+σ. For breathing patterns that were very different between “Day 1” and any other “Day N(>1)”, this difference was as high as 24.5% for ITVmean-σ. Conclusion: Proton treatment planning based on pre-treatment 4DCT can lead to under-dosage of the tumor and over-dosage of the surrounding tissues, because of inadequate estimate of the range of motion of the tumor. This is due to the shift of the Bragg peak compared to photon therapy in which the tumor is surrounded by an electron bath.« less

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

A kind of graded sub-pixel motion estimation algorithm combining time-domain characteristics with frequency-domain phase correlation

NASA Astrophysics Data System (ADS)

Xie, Bing; Duan, Zhemin; Chen, Yu

2017-11-01

The mode of navigation based on scene match can assist UAV to achieve autonomous navigation and other missions. However, aerial multi-frame images of the UAV in the complex flight environment easily be affected by the jitter, noise and exposure, which will lead to image blur, deformation and other issues, and result in the decline of detection rate of the interested regional target. Aiming at this problem, we proposed a kind of Graded sub-pixel motion estimation algorithm combining time-domain characteristics with frequency-domain phase correlation. Experimental results prove the validity and accuracy of the proposed algorithm.

Ubiquitous human upper-limb motion estimation using wearable sensors.

PubMed

Zhang, Zhi-Qiang; Wong, Wai-Choong; Wu, Jian-Kang

2011-07-01

Human motion capture technologies have been widely used in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health care, navigation, and so on. The existing human motion capture techniques, which use structured multiple high-resolution cameras in a dedicated studio, are complicated and expensive. With the rapid development of microsensors-on-chip, human motion capture using wearable microsensors has become an active research topic. Because of the agility in movement, upper-limb motion estimation has been regarded as the most difficult problem in human motion capture. In this paper, we take the upper limb as our research subject and propose a novel ubiquitous upper-limb motion estimation algorithm, which concentrates on modeling the relationship between upper-arm movement and forearm movement. A link structure with 5 degrees of freedom (DOF) is proposed to model the human upper-limb skeleton structure. Parameters are defined according to Denavit-Hartenberg convention, forward kinematics equations are derived, and an unscented Kalman filter is deployed to estimate the defined parameters. The experimental results have shown that the proposed upper-limb motion capture and analysis algorithm outperforms other fusion methods and provides accurate results in comparison to the BTS optical motion tracker.

Seismic response evaluation of base-isolated reinforced concrete buildings under bidirectional excitation

NASA Astrophysics Data System (ADS)

Bhagat, Satish; Wijeyewickrema, Anil C.

2017-04-01

This paper reports on an investigation of the seismic response of base-isolated reinforced concrete buildings, which considers various isolation system parameters under bidirectional near-fault and far-fault motions. Three-dimensional models of 4-, 8-, and 12-story base-isolated buildings with nonlinear effects in the isolation system and the superstructure are investigated, and nonlinear response history analysis is carried out. The bounding values of isolation system properties that incorporate the aging effect of isolators are also taken into account, as is the current state of practice in the design and analysis of base-isolated buildings. The response indicators of the buildings are studied for near-fault and far-fault motions weight-scaled to represent the design earthquake (DE) level and the risk-targeted maximum considered earthquake (MCER) level. Results of the nonlinear response history analyses indicate no structural damage under DE-level motions for near-fault and far-fault motions and for MCER-level far-fault motions, whereas minor structural damage is observed under MCER-level near-fault motions. Results of the base-isolated buildings are compared with their fixed-base counterparts. Significant reduction of the superstructure response of the 12-story base-isolated building compared to the fixed-base condition indicates that base isolation can be effectively used in taller buildings to enhance performance. Additionally, the applicability of a rigid superstructure to predict the isolator displacement demand is also investigated. It is found that the isolator displacements can be estimated accurately using a rigid body model for the superstructure for the buildings considered.

The Solar Neighborhood. XXV. Discovery of New Proper Motion Stars with 0.40 sec/yr > mu > or = 0.18 sec/yr Between Declinations -47 deg and 00 deg

NASA Technical Reports Server (NTRS)

Boyd, Mark R.; Winters, Jennifer G.; Henry, Todd J.; Jao, Wei-Chun; Finch, Charlie T.; Subasavage, John P.; Hambly, Nigel C.

2011-01-01

We present 2817 new southern proper motion systems with 0.40 sec/yr > mu > or = 0.18 sec/yr and declination between 47 deg and 00 deg. This is a continuation of the SuperCOSMOS-RECONS (SCR) proper motion searches of the southern sky. We use the same photometric relations as previous searches to provide distance estimates based on the assumption that the objects are single main-sequence stars. We find 79 new red dwarf systems predicted to be within 25 pc, including a few new components of previously known systems. Two systems--SCR 1731-2452 at 9.5 pc and SCR 1746-3214 at 9.9 pc--are anticipated to be within 10 pc. We also find 23 new white dwarf (WD) candidates with distance estimates of 15-66 pc, as well as 360 new red subdwarf candidates. With this search, we complete the SCR sweep of the southern sky for stars with mu > or = 0.18 sec/yr and R(sub 59F) < or = 16.5, resulting in a total of 5042 objects in 4724 previously unreported proper motion systems. Here we provide selected comprehensive lists from our SCR proper motion search to date, including 152 red dwarf systems estimated to be within 25 pc (9 within 10 pc), 46 WDs (10 within 25 pc), and 598 subdwarf candidates. The results of this search suggest that there are more nearby systems to be found at fainter magnitudes and lower proper motion limits than those probed so far.

Flies and humans share a motion estimation strategy that exploits natural scene statistics

PubMed Central

Clark, Damon A.; Fitzgerald, James E.; Ales, Justin M.; Gohl, Daryl M.; Silies, Marion A.; Norcia, Anthony M.; Clandinin, Thomas R.

2014-01-01

Sighted animals extract motion information from visual scenes by processing spatiotemporal patterns of light falling on the retina. The dominant models for motion estimation exploit intensity correlations only between pairs of points in space and time. Moving natural scenes, however, contain more complex correlations. Here we show that fly and human visual systems encode the combined direction and contrast polarity of moving edges using triple correlations that enhance motion estimation in natural environments. Both species extract triple correlations with neural substrates tuned for light or dark edges, and sensitivity to specific triple correlations is retained even as light and dark edge motion signals are combined. Thus, both species separately process light and dark image contrasts to capture motion signatures that can improve estimation accuracy. This striking convergence argues that statistical structures in natural scenes have profoundly affected visual processing, driving a common computational strategy over 500 million years of evolution. PMID:24390225

Stock price prediction using geometric Brownian motion

NASA Astrophysics Data System (ADS)

Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

2018-03-01

Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

The Estimation of a Rigid Body Motion in the Presence of Noise.

DTIC Science & Technology

1987-07-31

Rigid Body Motion in the Presence of Noise 12. PERSONAL AUTHOR(S) 1S. AYOFDREPRTy 13b.e ad COVRE C4. 10AOUTE OF FUNPING NUBERSlAE...8217, .,_, .,,.. .\\ ..: ., : ’ *-: ,:,.,,. .’ 4 /. .’.’ ’, ’ ,. 9) 7 TRACT The problem of estimating a rigid body motion from two noisy images of an...SI ... ... Cs . I ,-’ ’".’ 1 -, ED 1, D:;.;i,1q L HARVARD UNIVERSITY DzPAILTMNT OP STATIMCS THE ESTIMATION OF A RIGID BODY MOTION IN THE

A Fourier approach to cloud motion estimation

NASA Technical Reports Server (NTRS)

Arking, A.; Lo, R. C.; Rosenfield, A.

1977-01-01

A Fourier technique is described for estimating cloud motion from pairs of pictures using the phase of the cross spectral density. The method allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. Results obtained are presented and compared with the results of a Fourier domain cross correlation scheme. Using both artificial and real cloud data show that the technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects.

Investigation of the Observability of a Satellite Cluster in a Near Circular Orbit

DTIC Science & Technology

1989-12-01

investigation involved the use of dynamics based on the Clohessy - Wiltshire equa- tions and an on-board estimator based on the U-D covariance factorization...vectors were determined from the Clohessy - Wiltshire equations (10:80). These equations have the following * form: I I4 I I I sat i , ref pointI S iA lll ri... Clohessy - Wiltshire equations of motion, with 77 representing the mean motion (10:80). These equations are: 1 11I ;i - 2 )- 3 T12 X = 0 (27) +21 =0 (28

Efficient flapping flight of pterosaurs

NASA Astrophysics Data System (ADS)

Strang, Karl Axel

In the late eighteenth century, humans discovered the first pterosaur fossil remains and have been fascinated by their existence ever since. Pterosaurs exploited their membrane wings in a sophisticated manner for flight control and propulsion, and were likely the most efficient and effective flyers ever to inhabit our planet. The flapping gait is a complex combination of motions that sustains and propels an animal in the air. Because pterosaurs were so large with wingspans up to eleven meters, if they could have sustained flapping flight, they would have had to achieve high propulsive efficiencies. Identifying the wing motions that contribute the most to propulsive efficiency is key to understanding pterosaur flight, and therefore to shedding light on flapping flight in general and the design of efficient ornithopters. This study is based on published results for a very well-preserved specimen of Coloborhynchus robustus, for which the joints are well-known and thoroughly described in the literature. Simplifying assumptions are made to estimate the characteristics that can not be inferred directly from the fossil remains. For a given animal, maximizing efficiency is equivalent to minimizing power at a given thrust and speed. We therefore aim at finding the flapping gait, that is the joint motions, that minimize the required flapping power. The power is computed from the aerodynamic forces created during a given wing motion. We develop an unsteady three-dimensional code based on the vortex-lattice method, which correlates well with published results for unsteady motions of rectangular wings. In the aerodynamic model, the rigid pterosaur wing is defined by the position of the bones. In the aeroelastic model, we add the flexibility of the bones and of the wing membrane. The nonlinear structural behavior of the membrane is reduced to a linear modal decomposition, assuming small deflections about the reference wing geometry. The reference wing geometry is computed for the membrane subject to glide loads and pretension from the wing joint positions. The flapping gait is optimized in a two-stage procedure. First the design space is explored using a binary genetic algorithm. The best design points are then used as starting points in a sequential quadratic programming optimization algorithm. This algorithm is used to refine the solutions by precisely satisfying the constraints. The refined solutions are found in generally less than twenty major iterations and constraints are violated generally by less than 0.1%. We find that the optimal motions are in agreement with previous results for simple wing motions. By adding joint motions, the required flapping power is reduced by 7% to 17%. Because of the large uncertainties for some estimates, we investigate the sensitivity of the optimized flapping gait. We find that the optimal motions are sensitive mainly to flight speed, body accelerations, and to the material properties of the wing membrane. The optimal flight speed found correlates well with other studies of pterosaur flapping flight, and is 31% to 37% faster than previous estimates based on glide performance. Accounting for the body accelerations yields an increase of 10% to 16% in required flapping power. When including the aeroelastic effects, the optimal flapping gait is only slightly modified to accommodate for the deflections of stiff membranes. For a flexible membrane, the motion is significantly modified and the power increased by up to 57%. Finally, the flapping gait and required power compare well with published results for similar wing motions. Some published estimates of required power assumed a propulsive efficiency of 100%, whereas the propulsive efficiency computed for Coloborhynchus robustus ranges between 54% and 87%.

Tsunami simulation using submarine displacement calculated from simulation of ground motion due to seismic source model

NASA Astrophysics Data System (ADS)

Akiyama, S.; Kawaji, K.; Fujihara, S.

2013-12-01

Since fault fracturing due to an earthquake can simultaneously cause ground motion and tsunami, it is appropriate to evaluate the ground motion and the tsunami by single fault model. However, several source models are used independently in the ground motion simulation or the tsunami simulation, because of difficulty in evaluating both phenomena simultaneously. Many source models for the 2011 off the Pacific coast of Tohoku Earthquake are proposed from the inversion analyses of seismic observations or from those of tsunami observations. Most of these models show the similar features, which large amount of slip is located at the shallower part of fault area near the Japan Trench. This indicates that the ground motion and the tsunami can be evaluated by the single source model. Therefore, we examine the possibility of the tsunami prediction, using the fault model estimated from seismic observation records. In this study, we try to carry out the tsunami simulation using the displacement field of oceanic crustal movements, which is calculated from the ground motion simulation of the 2011 off the Pacific coast of Tohoku Earthquake. We use two fault models by Yoshida et al. (2011), which are based on both the teleseismic body wave and on the strong ground motion records. Although there is the common feature in those fault models, the amount of slip near the Japan trench is lager in the fault model from the strong ground motion records than in that from the teleseismic body wave. First, the large-scale ground motion simulations applying those fault models used by the voxel type finite element method are performed for the whole eastern Japan. The synthetic waveforms computed from the simulations are generally consistent with the observation records of K-NET (Kinoshita (1998)) and KiK-net stations (Aoi et al. (2000)), deployed by the National Research Institute for Earth Science and Disaster Prevention (NIED). Next, the tsunami simulations are performed by the finite difference calculation based on the shallow water theory. The initial wave height for tsunami generation is estimated from the vertical displacement of ocean bottom due to the crustal movements, which is obtained from the ground motion simulation mentioned above. The results of tsunami simulations are compared with the observations of the GPS wave gauges to evaluate the validity for the tsunami prediction using the fault model based on the seismic observation records.

Total Motion Across the East African Rift Viewed From the Southwest Indian Ridge

NASA Astrophysics Data System (ADS)

Royer, J.; Gordon, R. G.

2005-05-01

The Nubian plate is known to have been separating from the Somalian plate along the East African Rift since Oligocene time. Recent works have shown that the spreading rates and spreading directions since 11 Ma along the Southwest Indian Ridge (SWIR) record Nubia-Antarctica motion west of the Andrew Bain Fracture Zone complex (ABFZ; between 25E and 35E) and Somalia-Antarctica motion east of it. Nubia-Somalia motion can be determined by differencing Nubia-Antarctica and Somalia-Antarctica motion. To estimate the total motion across the East African Rift, we estimated and differenced Nubia-Antarctica motion and Somalia-Antarctica motion for times that preceded the initiation of Nubia-Somalia motion. We analyze anomalies 24n.3o (53 Ma), 21o (48 Ma), 18o (40 Ma) and 13o (34 Ma). Preliminary results show that the poles of the finite rotations that describe the Nubia-Somalia motions cluster near 30E, 42S. Angles of rotation range from 2.7 to 4.0 degrees. The uncertainty regions are large. The lower estimate predicts a total extension of 245 km at the latitude of the Ethiopian rift (41E, 9N) in a direction N104, perpendicular to the mean trend of the rift. Assuming an age of 34 Ma for the initiation of rifting, the average rate of motion would be 7 mm/a, near the 9 mm/a deduced from present-day geodetic measurements [e.g. synthesis of Fernandes et al., 2004]. Although these results require further analysis, particularly on the causes of the large uncertainties, they represent the first independent estimate of the total extension across the rift. Among other remaining questions are the following: How significant are the differences between these estimates and those for younger chrons (5 or 6 ; respectively 11 and 20 Ma), i.e. is the start of extension datable? Is the region east of the ABFZ part of the Somalian plate or does it form a distinct component plate of Somalia, as postulated by Hartnady (2004)? How has motion between two or more component plates within the African composite plate affected estimates of India-Eurasia motion and of Pacific-North America motion?

Ground Motion Prediction Models for Caucasus Region

NASA Astrophysics Data System (ADS)

Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

2016-04-01

Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

Variance change point detection for fractional Brownian motion based on the likelihood ratio test

NASA Astrophysics Data System (ADS)

Kucharczyk, Daniel; Wyłomańska, Agnieszka; Sikora, Grzegorz

2018-01-01

Fractional Brownian motion is one of the main stochastic processes used for describing the long-range dependence phenomenon for self-similar processes. It appears that for many real time series, characteristics of the data change significantly over time. Such behaviour one can observe in many applications, including physical and biological experiments. In this paper, we present a new technique for the critical change point detection for cases where the data under consideration are driven by fractional Brownian motion with a time-changed diffusion coefficient. The proposed methodology is based on the likelihood ratio approach and represents an extension of a similar methodology used for Brownian motion, the process with independent increments. Here, we also propose a statistical test for testing the significance of the estimated critical point. In addition to that, an extensive simulation study is provided to test the performance of the proposed method.

Incorporating structure from motion uncertainty into image-based pose estimation

NASA Astrophysics Data System (ADS)

Ludington, Ben T.; Brown, Andrew P.; Sheffler, Michael J.; Taylor, Clark N.; Berardi, Stephen

2015-05-01

A method for generating and utilizing structure from motion (SfM) uncertainty estimates within image-based pose estimation is presented. The method is applied to a class of problems in which SfM algorithms are utilized to form a geo-registered reference model of a particular ground area using imagery gathered during flight by a small unmanned aircraft. The model is then used to form camera pose estimates in near real-time from imagery gathered later. The resulting pose estimates can be utilized by any of the other onboard systems (e.g. as a replacement for GPS data) or downstream exploitation systems, e.g., image-based object trackers. However, many of the consumers of pose estimates require an assessment of the pose accuracy. The method for generating the accuracy assessment is presented. First, the uncertainty in the reference model is estimated. Bundle Adjustment (BA) is utilized for model generation. While the high-level approach for generating a covariance matrix of the BA parameters is straightforward, typical computing hardware is not able to support the required operations due to the scale of the optimization problem within BA. Therefore, a series of sparse matrix operations is utilized to form an exact covariance matrix for only the parameters that are needed at a particular moment. Once the uncertainty in the model has been determined, it is used to augment Perspective-n-Point pose estimation algorithms to improve the pose accuracy and to estimate the resulting pose uncertainty. The implementation of the described method is presented along with results including results gathered from flight test data.

Application and evaluation of a rapid response earthquake-triggered landslide model to the 25 April 2015 Mw 7.8 Gorkha earthquake, Nepal

USGS Publications Warehouse

Gallen, Sean F.; Clark, Marin K.; Godt, Jonathan W.; Roback, Kevin; Niemi, Nathan A

2017-01-01

The 25 April 2015 Mw 7.8 Gorkha earthquake produced strong ground motions across an approximately 250 km by 100 km swath in central Nepal. To assist disaster response activities, we modified an existing earthquake-triggered landslide model based on a Newmark sliding block analysis to estimate the extent and intensity of landsliding and landslide dam hazard. Landslide hazard maps were produced using Shuttle Radar Topography Mission (SRTM) digital topography, peak ground acceleration (PGA) information from the U.S. Geological Survey (USGS) ShakeMap program, and assumptions about the regional rock strength based on end-member values from previous studies. The instrumental record of seismicity in Nepal is poor, so PGA estimates were based on empirical Ground Motion Prediction Equations (GMPEs) constrained by teleseismic data and felt reports. We demonstrate a non-linear dependence of modeled landsliding on aggregate rock strength, where the number of landslides decreases exponentially with increasing rock strength. Model estimates are less sensitive to PGA at steep slopes (> 60°) compared to moderate slopes (30–60°). We compare forward model results to an inventory of landslides triggered by the Gorkha earthquake. We show that moderate rock strength inputs over estimate landsliding in regions beyond the main slip patch, which may in part be related to poorly constrained PGA estimates for this event at far distances from the source area. Directly above the main slip patch, however, the moderate strength model accurately estimates the total number of landslides within the resolution of the model (landslides ≥ 0.0162 km2; observed n = 2214, modeled n = 2987), but the pattern of landsliding differs from observations. This discrepancy is likely due to the unaccounted for effects of variable material strength and local topographic amplification of strong ground motion, as well as other simplifying assumptions about source characteristics and their relationship to landsliding.

Mobile robot motion estimation using Hough transform

NASA Astrophysics Data System (ADS)

Aldoshkin, D. N.; Yamskikh, T. N.; Tsarev, R. Yu

2018-05-01

This paper proposes an algorithm for estimation of mobile robot motion. The geometry of surrounding space is described with range scans (samples of distance measurements) taken by the mobile robot’s range sensors. A similar sample of space geometry in any arbitrary preceding moment of time or the environment map can be used as a reference. The suggested algorithm is invariant to isotropic scaling of samples or map that allows using samples measured in different units and maps made at different scales. The algorithm is based on Hough transform: it maps from measurement space to a straight-line parameters space. In the straight-line parameters, space the problems of estimating rotation, scaling and translation are solved separately breaking down a problem of estimating mobile robot localization into three smaller independent problems. The specific feature of the algorithm presented is its robustness to noise and outliers inherited from Hough transform. The prototype of the system of mobile robot orientation is described.

Towards Photoplethysmography-Based Estimation of Instantaneous Heart Rate During Physical Activity.

PubMed

Jarchi, Delaram; Casson, Alexander J

2017-09-01

Recently numerous methods have been proposed for estimating average heart rate using photoplethysmography (PPG) during physical activity, overcoming the significant interference that motion causes in PPG traces. We propose a new algorithm framework for extracting instantaneous heart rate from wearable PPG and Electrocardiogram (ECG) signals to provide an estimate of heart rate variability during exercise. For ECG signals, we propose a new spectral masking approach which modifies a particle filter tracking algorithm, and for PPG signals constrains the instantaneous frequency obtained from the Hilbert transform to a region of interest around a candidate heart rate measure. Performance is verified using accelerometry and wearable ECG and PPG data from subjects while biking and running on a treadmill. Instantaneous heart rate provides more information than average heart rate alone. The instantaneous heart rate can be extracted during motion to an accuracy of 1.75 beats per min (bpm) from PPG signals and 0.27 bpm from ECG signals. Estimates of instantaneous heart rate can now be generated from PPG signals during motion. These estimates can provide more information on the human body during exercise. Instantaneous heart rate provides a direct measure of vagal nerve and sympathetic nervous system activity and is of substantial use in a number of analyzes and applications. Previously it has not been possible to estimate instantaneous heart rate from wrist wearable PPG signals.

Smartphone-Based Cardiac Rehabilitation Program: Feasibility Study.

PubMed

Chung, Heewon; Ko, Hoon; Thap, Tharoeun; Jeong, Changwon; Noh, Se-Eung; Yoon, Kwon-Ha; Lee, Jinseok

2016-01-01

We introduce a cardiac rehabilitation program (CRP) that utilizes only a smartphone, with no external devices. As an efficient guide for cardiac rehabilitation exercise, we developed an application to automatically indicate the exercise intensity by comparing the estimated heart rate (HR) with the target heart rate zone (THZ). The HR is estimated using video images of a fingertip taken by the smartphone's built-in camera. The introduced CRP app includes pre-exercise, exercise with intensity guidance, and post-exercise. In the pre-exercise period, information such as THZ, exercise type, exercise stage order, and duration of each stage are set up. In the exercise with intensity guidance, the app estimates HR from the pulse obtained using the smartphone's built-in camera and compares the estimated HR with the THZ. Based on this comparison, the app adjusts the exercise intensity to shift the patient's HR to the THZ during exercise. In the post-exercise period, the app manages the ratio of the estimated HR to the THZ and provides a questionnaire on factors such as chest pain, shortness of breath, and leg pain during exercise, as objective and subjective evaluation indicators. As a key issue, HR estimation upon signal corruption due to motion artifacts is also considered. Through the smartphone-based CRP, we estimated the HR accuracy as mean absolute error and root mean squared error of 6.16 and 4.30bpm, respectively, with signal corruption due to motion artifacts being detected by combining the turning point ratio and kurtosis.

Smartphone-Based Cardiac Rehabilitation Program: Feasibility Study

PubMed Central

Chung, Heewon; Yoon, Kwon-Ha; Lee, Jinseok

2016-01-01

We introduce a cardiac rehabilitation program (CRP) that utilizes only a smartphone, with no external devices. As an efficient guide for cardiac rehabilitation exercise, we developed an application to automatically indicate the exercise intensity by comparing the estimated heart rate (HR) with the target heart rate zone (THZ). The HR is estimated using video images of a fingertip taken by the smartphone’s built-in camera. The introduced CRP app includes pre-exercise, exercise with intensity guidance, and post-exercise. In the pre-exercise period, information such as THZ, exercise type, exercise stage order, and duration of each stage are set up. In the exercise with intensity guidance, the app estimates HR from the pulse obtained using the smartphone’s built-in camera and compares the estimated HR with the THZ. Based on this comparison, the app adjusts the exercise intensity to shift the patient’s HR to the THZ during exercise. In the post-exercise period, the app manages the ratio of the estimated HR to the THZ and provides a questionnaire on factors such as chest pain, shortness of breath, and leg pain during exercise, as objective and subjective evaluation indicators. As a key issue, HR estimation upon signal corruption due to motion artifacts is also considered. Through the smartphone-based CRP, we estimated the HR accuracy as mean absolute error and root mean squared error of 6.16 and 4.30bpm, respectively, with signal corruption due to motion artifacts being detected by combining the turning point ratio and kurtosis. PMID:27551969

Motion correction in periodically-rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) and turboprop MRI.

PubMed

Tamhane, Ashish A; Arfanakis, Konstantinos

2009-07-01

Periodically-rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) and Turboprop MRI are characterized by greatly reduced sensitivity to motion, compared to their predecessors, fast spin-echo (FSE) and gradient and spin-echo (GRASE), respectively. This is due to the inherent self-navigation and motion correction of PROPELLER-based techniques. However, it is unknown how various acquisition parameters that determine k-space sampling affect the accuracy of motion correction in PROPELLER and Turboprop MRI. The goal of this work was to evaluate the accuracy of motion correction in both techniques, to identify an optimal rotation correction approach, and determine acquisition strategies for optimal motion correction. It was demonstrated that blades with multiple lines allow more accurate estimation of motion than blades with fewer lines. Also, it was shown that Turboprop MRI is less sensitive to motion than PROPELLER. Furthermore, it was demonstrated that the number of blades does not significantly affect motion correction. Finally, clinically appropriate acquisition strategies that optimize motion correction are discussed for PROPELLER and Turboprop MRI. (c) 2009 Wiley-Liss, Inc.

3D delivered dose assessment using a 4DCT-based motion model

PubMed Central

Cai, Weixing; Hurwitz, Martina H.; Williams, Christopher L.; Dhou, Salam; Berbeco, Ross I.; Seco, Joao; Mishra, Pankaj; Lewis, John H.

2015-01-01

Purpose: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). Methods: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying “fluoroscopic” 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using “ground truth” XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. Results: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images reconstructed from kV and MV projections compared to the ground truth, which is clinically comparable to 4DCT (0.093%). For the second XCAT phantom that has an irregular breathing pattern, the errors are 0.81% and 1.75% for kV and MV reconstructions, both of which are better than that of 4DCT (4.01%). In the case of real patient, although it is impossible to obtain the actual delivered dose, the dose estimation is clinically reasonable and demonstrates differences between 4DCT and MV reconstruction-based dose estimates. Conclusions: With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed 3D fluoroscopic images was as good as 4DCT for regular respiratory pattern and was a better dose estimation for the irregular respiratory pattern. PMID:26127043

3D delivered dose assessment using a 4DCT-based motion model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Weixing; Hurwitz, Martina H.; Williams, Christopher L.

Purpose: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). Methods: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basismore » DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying “fluoroscopic” 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using “ground truth” XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. Results: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images reconstructed from kV and MV projections compared to the ground truth, which is clinically comparable to 4DCT (0.093%). For the second XCAT phantom that has an irregular breathing pattern, the errors are 0.81% and 1.75% for kV and MV reconstructions, both of which are better than that of 4DCT (4.01%). In the case of real patient, although it is impossible to obtain the actual delivered dose, the dose estimation is clinically reasonable and demonstrates differences between 4DCT and MV reconstruction-based dose estimates. Conclusions: With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed 3D fluoroscopic images was as good as 4DCT for regular respiratory pattern and was a better dose estimation for the irregular respiratory pattern.« less

Preliminary SPE Phase II Far Field Ground Motion Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steedman, David W.

2014-03-06

Phase II of the Source Physics Experiment (SPE) program will be conducted in alluvium. Several candidate sites were identified. These include existing large diameter borehole U1e. One criterion for acceptance is expected far field ground motion. In June 2013 we were requested to estimate peak response 2 km from the borehole due to the largest planned SPE Phase II experiment: a contained 50- Ton event. The cube-root scaled range for this event is 5423 m/KT 1/3. The generally accepted first order estimate of ground motions from an explosive event is to refer to the standard data base for explosive eventsmore » (Perrett and Bass, 1975). This reference is a compilation and analysis of ground motion data from numerous nuclear and chemical explosive events from Nevada National Security Site (formerly the Nevada Test Site, or NTS) and other locations. The data were compiled and analyzed for various geologic settings including dry alluvium, which we believe is an accurate descriptor for the SPE Phase II setting. The Perrett and Bass plots of peak velocity and peak yield-scaled displacement, both vs. yield-scaled range, are provided here. Their analysis of both variables resulted in bi-linear fits: a close-in non-linear regime and a more distant linear regime.« less

Representation of deformable motion for compression of dynamic cardiac image data

NASA Astrophysics Data System (ADS)

Weinlich, Andreas; Amon, Peter; Hutter, Andreas; Kaup, André

2012-02-01

We present a new approach for efficient estimation and storage of tissue deformation in dynamic medical image data like 3-D+t computed tomography reconstructions of human heart acquisitions. Tissue deformation between two points in time can be described by means of a displacement vector field indicating for each voxel of a slice, from which position in the previous slice at a fixed position in the third dimension it has moved to this position. Our deformation model represents the motion in a compact manner using a down-sampled potential function of the displacement vector field. This function is obtained by a Gauss-Newton minimization of the estimation error image, i. e., the difference between the current and the deformed previous slice. For lossless or lossy compression of volume slices, the potential function and the error image can afterwards be coded separately. By assuming deformations instead of translational motion, a subsequent coding algorithm using this method will achieve better compression ratios for medical volume data than with conventional block-based motion compensation known from video coding. Due to the smooth prediction without block artifacts, particularly whole-image transforms like wavelet decomposition as well as intra-slice prediction methods can benefit from this approach. We show that with discrete cosine as well as with Karhunen-Lo`eve transform the method can achieve a better energy compaction of the error image than block-based motion compensation while reaching approximately the same prediction error energy.

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Wide-Range Motion Estimation Architecture with Dual Search Windows for High Resolution Video Coding

NASA Astrophysics Data System (ADS)

Dung, Lan-Rong; Lin, Meng-Chun

This paper presents a memory-efficient motion estimation (ME) technique for high-resolution video compression. The main objective is to reduce the external memory access, especially for limited local memory resource. The reduction of memory access can successfully save the notorious power consumption. The key to reduce the memory accesses is based on center-biased algorithm in that the center-biased algorithm performs the motion vector (MV) searching with the minimum search data. While considering the data reusability, the proposed dual-search-windowing (DSW) approaches use the secondary windowing as an option per searching necessity. By doing so, the loading of search windows can be alleviated and hence reduce the required external memory bandwidth. The proposed techniques can save up to 81% of external memory bandwidth and require only 135 MBytes/sec, while the quality degradation is less than 0.2dB for 720p HDTV clips coded at 8Mbits/sec.

Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice

USGS Publications Warehouse

Kaklamanos, James; Baise, Laurie G.; Boore, David M.

2011-01-01

The ground-motion prediction equations (GMPEs) developed as part of the Next Generation Attenuation of Ground Motions (NGA-West) project in 2008 are becoming widely used in seismic hazard analyses. However, these new models are considerably more complicated than previous GMPEs, and they require several more input parameters. When employing the NGA models, users routinely face situations in which some of the required input parameters are unknown. In this paper, we present a framework for estimating the unknown source, path, and site parameters when implementing the NGA models in engineering practice, and we derive geometrically-based equations relating the three distance measures found in the NGA models. Our intent is for the content of this paper not only to make the NGA models more accessible, but also to help with the implementation of other present or future GMPEs.

A comparison of two computer-automated semen analysis instruments for the evaluation of sperm motion characteristics in the stallion.

PubMed

Jasko, D J; Lein, D H; Foote, R H

1990-01-01

Two commercially available computer-automate semen analysis instruments (CellSoft Automated Semen Analyzer and HTM-2000 Motion Analyzer) were compared for their ability to report similar results based on the analysis of pre-recorded video tapes of extended, motile stallion semen. The determinations of the percentage of motile cells by these instruments were more similar than the comparisons between subjective estimates and either instrument. However, mean values obtained from the same sample may still differ by as much as 30 percentage units between instruments. Instruments varied with regard to the determinations of mean sperm curvilinear velocity and sperm concentration, but mean sperm linearity determinations were similar between the instruments. We concluded that the determinations of sperm motion characteristics by subjective estimation, CellSoft Automated Semen Analyzer, and HTM-2000 Motility Analyzer are often dissimilar, making direct comparisons of results difficult.

Application of the integral manifold method to the analysis of the spatial motion of a rigid body fixed to a cable

NASA Astrophysics Data System (ADS)

Zabolotnov, Yu. M.

2016-07-01

We analyze the spatial motion of a rigid body fixed to a cable about its center of mass when the orbital cable system is unrolling. The analysis is based on the integral manifold method, which permits separating the rigid body motion into the slow and fast components. The motion of the rigid body is studied in the case of slow variations in the cable tension force and under the action of various disturbances.We estimate the influence of the static and dynamic asymmetry of the rigid body on its spatial motion about the cable fixation point. An example of the analysis of the rigid body motion when the orbital cable system is unrolling is given for a special program of variations in the cable tension force. The conditions of applicability of the integral manifold method are analyzed.

In vivo validation of patellofemoral kinematics during overground gait and stair ascent.

PubMed

Pitcairn, Samuel; Lesniak, Bryson; Anderst, William

2018-06-18

The patellofemoral (PF) joint is a common site for non-specific anterior knee pain. The pathophysiology of patellofemoral pain may be related to abnormal motion of the patella relative to the femur, leading to increased stress at the patellofemoral joint. Patellofemoral motion cannot be accurately measured using conventional motion capture. The aim of this study was to determine the accuracy of a biplane radiography system for measuring in vivo PF motion during walking and stair ascent. Four subjects had three 1.0 mm diameter tantalum beads implanted into the patella. Participants performed three trials each of over ground walking and stair ascent while biplane radiographs were collected at 100 Hz. Patella motion was tracked using radiostereophotogrammetric analysis (RSA) as a "gold standard", and compared to a volumetric CT model-based tracking algorithm that matched digitally reconstructed radiographs to the original biplane radiographs. The average RMS difference between the RSA and model-based tracking was 0.41 mm and 1.97° when there was no obstruction from the contralateral leg. These differences increased by 34% and 40%, respectively, when the patella was at least partially obstructed by the contralateral leg. The average RMS difference in patellofemoral joint space between tracking methods was 0.9 mm or less. Previous validations of biplane radiographic systems have estimated tracking accuracy by moving cadaveric knees through simulated motions. These validations were unable to replicate in vivo kinematics, including patella motion due to muscle activation, and failed to assess the imaging and tracking challenges related to contralateral limb obstruction. By replicating the muscle contraction, movement velocity, joint range of motion, and obstruction of the patella by the contralateral limb, the present study provides a realistic estimate of patellofemoral tracking accuracy for future in vivo studies. Copyright © 2018 Elsevier B.V. All rights reserved.

MO-G-18C-05: Real-Time Prediction in Free-Breathing Perfusion MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, H; Liu, W; Ruan, D

Purpose: The aim is to minimize frame-wise difference errors caused by respiratory motion and eliminate the need for breath-holds in magnetic resonance imaging (MRI) sequences with long acquisitions and repeat times (TRs). The technique is being applied to perfusion MRI using arterial spin labeling (ASL). Methods: Respiratory motion prediction (RMP) using navigator echoes was implemented in ASL. A least-square method was used to extract the respiratory motion information from the 1D navigator. A generalized artificial neutral network (ANN) with three layers was developed to simultaneously predict 10 time points forward in time and correct for respiratory motion during MRI acquisition.more » During the training phase, the parameters of the ANN were optimized to minimize the aggregated prediction error based on acquired navigator data. During realtime prediction, the trained ANN was applied to the most recent estimated displacement trajectory to determine in real-time the amount of spatial Results: The respiratory motion information extracted from the least-square method can accurately represent the navigator profiles, with a normalized chi-square value of 0.037±0.015 across the training phase. During the 60-second training phase, the ANN successfully learned the respiratory motion pattern from the navigator training data. During real-time prediction, the ANN received displacement estimates and predicted the motion in the continuum of a 1.0 s prediction window. The ANN prediction was able to provide corrections for different respiratory states (i.e., inhalation/exhalation) during real-time scanning with a mean absolute error of < 1.8 mm. Conclusion: A new technique enabling free-breathing acquisition during MRI is being developed. A generalized ANN development has demonstrated its efficacy in predicting a continuum of motion profile for volumetric imaging based on navigator inputs. Future work will enhance the robustness of ANN and verify its effectiveness with human subjects. Research supported by National Institutes of Health National Cancer Institute Grant R01 CA159471-01.« less

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

NASA Astrophysics Data System (ADS)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Study of the Navigation Method for a Snake Robot Based on the Kinematics Model with MEMS IMU.

PubMed

Zhao, Xu; Dou, Lihua; Su, Zhong; Liu, Ning

2018-03-16

A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot's motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot's motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot's navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots.

Optimal integer resolution for attitude determination using global positioning system signals

NASA Technical Reports Server (NTRS)

Crassidis, John L.; Markley, F. Landis; Lightsey, E. Glenn

1998-01-01

In this paper, a new motion-based algorithm for GPS integer ambiguity resolution is derived. The first step of this algorithm converts the reference sightline vectors into body frame vectors. This is accomplished by an optimal vectorized transformation of the phase difference measurements. The result of this transformation leads to the conversion of the integer ambiguities to vectorized biases. This essentially converts the problem to the familiar magnetometer-bias determination problem, for which an optimal and efficient solution exists. Also, the formulation in this paper is re-derived to provide a sequential estimate, so that a suitable stopping condition can be found during the vehicle motion. The advantages of the new algorithm include: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can sequentially estimate the ambiguities during the vehicle motion. The only disadvantage of the new algorithm is that it requires at least three non-coplanar baselines. The performance of the new algorithm is tested on a dynamic hardware simulator.

Relative effects of posture and activity on human height estimation from surveillance footage.

PubMed

Ramstrand, Nerrolyn; Ramstrand, Simon; Brolund, Per; Norell, Kristin; Bergström, Peter

2011-10-10

Height estimations based on security camera footage are often requested by law enforcement authorities. While valid and reliable techniques have been established to determine vertical distances from video frames, there is a discrepancy between a person's true static height and their height as measured when assuming different postures or when in motion (e.g., walking). The aim of the research presented in this report was to accurately record the height of subjects as they performed a variety of activities typically observed in security camera footage and compare results to height recorded using a standard height measuring device. Forty-six able bodied adults participated in this study and were recorded using a 3D motion analysis system while performing eight different tasks. Height measurements captured using the 3D motion analysis system were compared to static height measurements in order to determine relative differences. It is anticipated that results presented in this report can be used by forensic image analysis experts as a basis for correcting height estimations of people captured on surveillance footage. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Influence of ultrasound speckle tracking strategies for motion and strain estimation.

PubMed

Curiale, Ariel H; Vegas-Sánchez-Ferrero, Gonzalo; Aja-Fernández, Santiago

2016-08-01

Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system. Copyright © 2016 Elsevier B.V. All rights reserved.

Source motion detection, estimation, and compensation for underwater acoustics inversion by wideband ambiguity lag-Doppler filtering.

PubMed

Josso, Nicolas F; Ioana, Cornel; Mars, Jérôme I; Gervaise, Cédric

2010-12-01

Acoustic channel properties in a shallow water environment with moving source and receiver are difficult to investigate. In fact, when the source-receiver relative position changes, the underwater environment causes multipath and Doppler scale changes on the transmitted signal over low-to-medium frequencies (300 Hz-20 kHz). This is the result of a combination of multiple paths propagation, source and receiver motions, as well as sea surface motion or water column fast changes. This paper investigates underwater acoustic channel properties in a shallow water (up to 150 m depth) and moving source-receiver conditions using extracted time-scale features of the propagation channel model for low-to-medium frequencies. An average impulse response of one transmission is estimated using the physical characteristics of propagation and the wideband ambiguity plane. Since a different Doppler scale should be considered for each propagating signal, a time-warping filtering method is proposed to estimate the channel time delay and Doppler scale attributes for each propagating path. The proposed method enables the estimation of motion-compensated impulse responses, where different Doppler scaling factors are considered for the different time delays. It was validated for channel profiles using real data from the BASE'07 experiment conducted by the North Atlantic Treaty Organization Undersea Research Center in the shallow water environment of the Malta Plateau, South Sicily. This paper provides a contribution to many field applications including passive ocean tomography with unknown natural sources position and movement. Another example is active ocean tomography where sources motion enables to rapidly cover one operational area for rapid environmental assessment and hydrophones may be drifting in order to avoid additional flow noise.

Preliminary evaluation of the dosimetric accuracy of cone-beam computed tomography for cases with respiratory motion

NASA Astrophysics Data System (ADS)

Kim, Dong Wook; Bae, Sunhyun; Chung, Weon Kuu; Lee, Yoonhee

2014-04-01

Cone-beam computed tomography (CBCT) images are currently used for patient positioning and adaptive dose calculation; however, the degree of CBCT uncertainty in cases of respiratory motion remains an interesting issue. This study evaluated the uncertainty of CBCT-based dose calculations for a moving target. Using a phantom, we estimated differences in the geometries and the Hounsfield units (HU) between CT and CBCT. The calculated dose distributions based on CT and CBCT images were also compared using a radiation treatment planning system, and the comparison included cases with respiratory motion. The geometrical uncertainties of the CT and the CBCT images were less than 0.15 cm. The HU differences between CT and CBCT images for standard-dose-head, high-quality-head, normal-pelvis, and low-dose-thorax modes were 31, 36, 23, and 33 HU, respectively. The gamma (3%, 0.3 cm)-dose distribution between CT and CBCT was greater than 1 in 99% of the area. The gamma-dose distribution between CT and CBCT during respiratory motion was also greater than 1 in 99% of the area. The uncertainty of the CBCT-based dose calculation was evaluated for cases with respiratory motion. In conclusion, image distortion due to motion did not significantly influence dosimetric parameters.

Novel true-motion estimation algorithm and its application to motion-compensated temporal frame interpolation.

PubMed

Dikbas, Salih; Altunbasak, Yucel

2013-08-01

In this paper, a new low-complexity true-motion estimation (TME) algorithm is proposed for video processing applications, such as motion-compensated temporal frame interpolation (MCTFI) or motion-compensated frame rate up-conversion (MCFRUC). Regular motion estimation, which is often used in video coding, aims to find the motion vectors (MVs) to reduce the temporal redundancy, whereas TME aims to track the projected object motion as closely as possible. TME is obtained by imposing implicit and/or explicit smoothness constraints on the block-matching algorithm. To produce better quality-interpolated frames, the dense motion field at interpolation time is obtained for both forward and backward MVs; then, bidirectional motion compensation using forward and backward MVs is applied by mixing both elegantly. Finally, the performance of the proposed algorithm for MCTFI is demonstrated against recently proposed methods and smoothness constraint optical flow employed by a professional video production suite. Experimental results show that the quality of the interpolated frames using the proposed method is better when compared with the MCFRUC techniques.

Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates

NASA Astrophysics Data System (ADS)

Garcin, Matthieu

2017-10-01

Hurst exponents depict the long memory of a time series. For human-dependent phenomena, as in finance, this feature may vary in the time. It justifies modelling dynamics by multifractional Brownian motions, which are consistent with time-dependent Hurst exponents. We improve the existing literature on estimating time-dependent Hurst exponents by proposing a smooth estimate obtained by variational calculus. This method is very general and not restricted to the sole Hurst framework. It is globally more accurate and easier than other existing non-parametric estimation techniques. Besides, in the field of Hurst exponents, it makes it possible to make forecasts based on the estimated multifractional Brownian motion. The application to high-frequency foreign exchange markets (GBP, CHF, SEK, USD, CAD, AUD, JPY, CNY and SGD, all against EUR) shows significantly good forecasts. When the Hurst exponent is higher than 0.5, what depicts a long-memory feature, the accuracy is higher.

SU-D-210-05: The Accuracy of Raw and B-Mode Image Data for Ultrasound Speckle Tracking in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, T; Bamber, J; Harris, E

Purpose: For ultrasound speckle tracking there is some evidence that the envelope-detected signal (the main step in B-mode image formation) may be more accurate than raw ultrasound data for tracking larger inter-frame tissue motion. This study investigates the accuracy of raw radio-frequency (RF) versus non-logarithmic compressed envelope-detected (B-mode) data for ultrasound speckle tracking in the context of image-guided radiation therapy. Methods: Transperineal ultrasound RF data was acquired (with a 7.5 MHz linear transducer operating at a 12 Hz frame rate) from a speckle phantom moving with realistic intra-fraction prostate motion derived from a commercial tracking system. A normalised cross-correlation templatemore » matching algorithm was used to track speckle motion at the focus using (i) the RF signal and (ii) the B-mode signal. A range of imaging rates (0.5 to 12 Hz) were simulated by decimating the imaging sequences, therefore simulating larger to smaller inter-frame displacements. Motion estimation accuracy was quantified by comparison with known phantom motion. Results: The differences between RF and B-mode motion estimation accuracy (2D mean and 95% errors relative to ground truth displacements) were less than 0.01 mm for stable and persistent motion types and 0.2 mm for transient motion for imaging rates of 0.5 to 12 Hz. The mean correlation for all motion types and imaging rates was 0.851 and 0.845 for RF and B-mode data, respectively. Data type is expected to have most impact on axial (Superior-Inferior) motion estimation. Axial differences were <0.004 mm for stable and persistent motion and <0.3 mm for transient motion (axial mean errors were lowest for B-mode in all cases). Conclusions: Using the RF or B-mode signal for speckle motion estimation is comparable for translational prostate motion. B-mode image formation may involve other signal-processing steps which also influence motion estimation accuracy. A similar study for respiratory-induced motion would also be prudent. This work is support by Cancer Research UK Programme Grant C33589/A19727.« less

A method of intentional movement estimation of oblique small-UAV videos stabilized based on homography model

NASA Astrophysics Data System (ADS)

Guo, Shiyi; Mai, Ying; Zhao, Hongying; Gao, Pengqi

2013-05-01

The airborne video streams of small-UAVs are commonly plagued with distractive jittery and shaking motions, disorienting rotations, noisy and distorted images and other unwanted movements. These problems collectively make it very difficult for observers to obtain useful information from the video. Due to the small payload of small-UAVs, it is a priority to improve the image quality by means of electronic image stabilization. But when small-UAV makes a turn, affected by the flight characteristics of it, the video is easy to become oblique. This brings a lot of difficulties to electronic image stabilization technology. Homography model performed well in the oblique image motion estimation, while bringing great challenges to intentional motion estimation. Therefore, in this paper, we focus on solve the problem of the video stabilized when small-UAVs banking and turning. We attend to the small-UAVs fly along with an arc of a fixed turning radius. For this reason, after a series of experimental analysis on the flight characteristics and the path how small-UAVs turned, we presented a new method to estimate the intentional motion in which the path of the frame center was used to fit the video moving track. Meanwhile, the image sequences dynamic mosaic was done to make up for the limited field of view. At last, the proposed algorithm was carried out and validated by actual airborne videos. The results show that the proposed method is effective to stabilize the oblique video of small-UAVs.

a Sensor Aided H.264/AVC Video Encoder for Aerial Video Sequences with in the Loop Metadata Correction

NASA Astrophysics Data System (ADS)

Cicala, L.; Angelino, C. V.; Ruatta, G.; Baccaglini, E.; Raimondo, N.

2015-08-01

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

BEM-based simulation of lung respiratory deformation for CT-guided biopsy.

PubMed

Chen, Dong; Chen, Weisheng; Huang, Lipeng; Feng, Xuegang; Peters, Terry; Gu, Lixu

2017-09-01

Accurate and real-time prediction of the lung and lung tumor deformation during respiration are important considerations when performing a peripheral biopsy procedure. However, most existing work focused on offline whole lung simulation using 4D image data, which is not applicable in real-time image-guided biopsy with limited image resources. In this paper, we propose a patient-specific biomechanical model based on the boundary element method (BEM) computed from CT images to estimate the respiration motion of local target lesion region, vessel tree and lung surface for the real-time biopsy guidance. This approach applies pre-computation of various BEM parameters to facilitate the requirement for real-time lung motion simulation. The resulting boundary condition at end inspiratory phase is obtained using a nonparametric discrete registration with convex optimization, and the simulation of the internal tissue is achieved by applying a tetrahedron-based interpolation method depend on expert-determined feature points on the vessel tree model. A reference needle is tracked to update the simulated lung motion during biopsy guidance. We evaluate the model by applying it for respiratory motion estimations of ten patients. The average symmetric surface distance (ASSD) and the mean target registration error (TRE) are employed to evaluate the proposed model. Results reveal that it is possible to predict the lung motion with ASSD of [Formula: see text] mm and a mean TRE of [Formula: see text] mm at largest over the entire respiratory cycle. In the CT-/electromagnetic-guided biopsy experiment, the whole process was assisted by our BEM model and final puncture errors in two studies were 3.1 and 2.0 mm, respectively. The experiment results reveal that both the accuracy of simulation and real-time performance meet the demands of clinical biopsy guidance.

Uncertainty Prediction in Passive Target Motion Analysis

DTIC Science & Technology

2016-05-12

fundamental property of bearings- only target motion analysis (TMA) is that bearing B to the Attorney Docket No. 300118 3 of 25 target 10 results...the measurements used to estimate them are often non-linear. This is true for the bearing observation: = tan −1 ( () () ) ( 3 ...Parameter Evaluation Plot ( PEP ) is one example of such a grid-based approach. U.S. Patent No. 7,020,046 discloses one version of this method and is

Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

PubMed Central

Abdul-Kreem, Luma Issa; Neumann, Heiko

2015-01-01

The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells. PMID:26554589

Combining multiple earthquake models in real time for earthquake early warning

USGS Publications Warehouse

Minson, Sarah E.; Wu, Stephen; Beck, James L; Heaton, Thomas H.

2017-01-01

The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real‐time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point source. Other EEW algorithms use finite rupture models or may directly estimate ground motion without first solving for an earthquake source. EEW performance could be improved if the information from these diverse and independent prediction models could be combined into one unified, ground‐motion prediction. In this article, we set the forecast shaking at each location as the common ground to combine all these predictions and introduce a Bayesian approach to creating better ground‐motion predictions. We also describe how this methodology could be used to build a new generation of EEW systems that provide optimal decisions customized for each user based on the user’s individual false‐alarm tolerance and the time necessary for that user to react.

Three-Dimensional Motion Estimation Using Shading Information in Multiple Frames

DTIC Science & Technology

1989-09-01

j. Threle-D.imensionai GO Motion Estimation U sing, Shadin g Ilnformation in Multiple Frames- IJean-Pierre Schotf MIT Artifi -cial intelligence...vision 3-D structure 3-D vision- shape from shading multiple frames 20. ABSTRACT (Cofrn11,00 an reysrf* OWd Of Rssss00n7 Ad 4111111& F~ block f)nseq See...motion and shading have been treated as two disjoint problems. On the one hand, researchers studying motion or structure from motion often assume

Temporally diffeomorphic cardiac motion estimation from three-dimensional echocardiography by minimization of intensity consistency error.

PubMed

Zhang, Zhijun; Ashraf, Muhammad; Sahn, David J; Song, Xubo

2014-05-01

Quantitative analysis of cardiac motion is important for evaluation of heart function. Three dimensional (3D) echocardiography is among the most frequently used imaging modalities for motion estimation because it is convenient, real-time, low-cost, and nonionizing. However, motion estimation from 3D echocardiographic sequences is still a challenging problem due to low image quality and image corruption by noise and artifacts. The authors have developed a temporally diffeomorphic motion estimation approach in which the velocity field instead of the displacement field was optimized. The optimal velocity field optimizes a novel similarity function, which we call the intensity consistency error, defined as multiple consecutive frames evolving to each time point. The optimization problem is solved by using the steepest descent method. Experiments with simulated datasets, images of anex vivo rabbit phantom, images of in vivo open-chest pig hearts, and healthy human images were used to validate the authors' method. Simulated and real cardiac sequences tests showed that results in the authors' method are more accurate than other competing temporal diffeomorphic methods. Tests with sonomicrometry showed that the tracked crystal positions have good agreement with ground truth and the authors' method has higher accuracy than the temporal diffeomorphic free-form deformation (TDFFD) method. Validation with an open-access human cardiac dataset showed that the authors' method has smaller feature tracking errors than both TDFFD and frame-to-frame methods. The authors proposed a diffeomorphic motion estimation method with temporal smoothness by constraining the velocity field to have maximum local intensity consistency within multiple consecutive frames. The estimated motion using the authors' method has good temporal consistency and is more accurate than other temporally diffeomorphic motion estimation methods.

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters

PubMed Central

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-01-01

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers. PMID:27618046

Effect of pressure and padding on motion artifact of textile electrodes.

PubMed

Cömert, Alper; Honkala, Markku; Hyttinen, Jari

2013-04-08

With the aging population and rising healthcare costs, wearable monitoring is gaining importance. The motion artifact affecting dry electrodes is one of the main challenges preventing the widespread use of wearable monitoring systems. In this paper we investigate the motion artifact and ways of making a textile electrode more resilient against motion artifact. Our aim is to study the effects of the pressure exerted onto the electrode, and the effects of inserting padding between the applied pressure and the electrode. We measure real time electrode-skin interface impedance, ECG from two channels, the motion artifact related surface potential, and exerted pressure during controlled motion by a measurement setup designed to estimate the relation of motion artifact to the signals. We use different foam padding materials with various mechanical properties and apply electrode pressures between 5 and 25 mmHg to understand their effect. A QRS and noise detection algorithm based on a modified Pan-Tompkins QRS detection algorithm estimates the electrode behaviour in respect to the motion artifact from two channels; one dominated by the motion artifact and one containing both the motion artifact and the ECG. This procedure enables us to quantify a given setup's susceptibility to the motion artifact. Pressure is found to strongly affect signal quality as is the use of padding. In general, the paddings reduce the motion artifact. However the shape and frequency components of the motion artifact vary for different paddings, and their material and physical properties. Electrode impedance at 100 kHz correlates in some cases with the motion artifact but it is not a good predictor of the motion artifact. From the results of this study, guidelines for improving electrode design regarding padding and pressure can be formulated as paddings are a necessary part of the system for reducing the motion artifact, and further, their effect maximises between 15 mmHg and 20 mmHg of exerted pressure. In addition, we present new methods for evaluating electrode sensitivity to motion, utilizing the detection of noise peaks that fall into the same frequency band as R-peaks.

Modeling the vestibulo-ocular reflex of the squirrel monkey during eccentric rotation and roll tilt

NASA Technical Reports Server (NTRS)

Merfeld, D. M.; Paloski, W. H. (Principal Investigator)

1995-01-01

Model simulations of the squirrel monkey vestibulo-ocular reflex (VOR) are presented for two motion paradigms: constant velocity eccentric rotation and roll tilt about a naso-occipital axis. The model represents the implementation of three hypotheses: the "internal model" hypothesis, the "gravito-inertial force (GIF) resolution" hypothesis, and the "compensatory VOR" hypothesis. The internal model hypothesis is based on the idea that the nervous system knows the dynamics of the sensory systems and implements this knowledge as an internal dynamic model. The GIF resolution hypothesis is based on the idea that the nervous system knows that gravity minus linear acceleration equals GIF and implements this knowledge by resolving the otolith measurement of GIF into central estimates of gravity and linear acceleration, such that the central estimate of gravity minus the central estimate of acceleration equals the otolith measurement of GIF. The compensatory VOR hypothesis is based on the idea that the VOR compensates for the central estimates of angular velocity and linear velocity, which sum in a near-linear manner. During constant velocity eccentric rotation, the model correctly predicts that: (1) the peak horizontal response is greater while "facing-motion" than with "back-to-motion"; (2) the axis of eye rotation shifts toward alignment with GIF; and (3) a continuous vertical response, slow phase downward, exists prior to deceleration. The model also correctly predicts that a torsional response during the roll rotation is the only velocity response observed during roll rotations about a naso-occipital axis. The success of this model in predicting the observed experimental responses suggests that the model captures the essence of the complex sensory interactions engendered by eccentric rotation and roll tilt.

Tilts in strong ground motion

USGS Publications Warehouse

Graizer, V.

2006-01-01

Most instruments used in seismological practice to record ground motion are pendulum seismographs, velocigraphs, or accelerographs. In most cases it is assumed that seismic instruments are only sensitive to the translational motion of the instrument's base. In this study the full equation of pendulum motion, including the inputs of rotations and tilts, is considered. It is shown that tilting the accelerograph's base can severely impact its response to the ground motion. The method of tilt evaluation using uncorrected strong-motion accelerograms was first suggested by Graizer (1989), and later tested in several laboratory experiments with different strong-motion instruments. The method is based on the difference in the tilt sensitivity of the horizontal and vertical pendulums. The method was applied to many of the strongest records of the Mw 6.7 Northridge earthquake of 1994. Examples are shown when relatively large tilts of up to a few degrees occurred during strong earthquake ground motion. Residual tilt extracted from the strong-motion record at the Pacoima Dam-Upper Left Abutment reached 3.1?? in N45??E direction, and was a result of local earthquake-induced tilting due to high-amplitude shaking. This value is in agreement with the residual tilt measured by using electronic level a few days after the earthquake. The method was applied to the building records from the Northridge earthquake. According to the estimates, residual tilt reached 2.6?? on the ground floor of the 12-story Hotel in Ventura. Processing of most of the strongest records of the Northridge earthquake shows that tilts, if happened, were within the error of the method, or less than about 0.5??.

Dense motion estimation using regularization constraints on local parametric models.

PubMed

Patras, Ioannis; Worring, Marcel; van den Boomgaard, Rein

2004-11-01

This paper presents a method for dense optical flow estimation in which the motion field within patches that result from an initial intensity segmentation is parametrized with models of different order. We propose a novel formulation which introduces regularization constraints between the model parameters of neighboring patches. In this way, we provide the additional constraints for very small patches and for patches whose intensity variation cannot sufficiently constrain the estimation of their motion parameters. In order to preserve motion discontinuities, we use robust functions as a regularization mean. We adopt a three-frame approach and control the balance between the backward and forward constraints by a real-valued direction field on which regularization constraints are applied. An iterative deterministic relaxation method is employed in order to solve the corresponding optimization problem. Experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities, and produces accurate piecewise-smooth motion fields.

Stochastic Earthquake Rupture Modeling Using Nonparametric Co-Regionalization

NASA Astrophysics Data System (ADS)

Lee, Kyungbook; Song, Seok Goo

2017-09-01

Accurate predictions of the intensity and variability of ground motions are essential in simulation-based seismic hazard assessment. Advanced simulation-based ground motion prediction methods have been proposed to complement the empirical approach, which suffers from the lack of observed ground motion data, especially in the near-source region for large events. It is important to quantify the variability of the earthquake rupture process for future events and to produce a number of rupture scenario models to capture the variability in simulation-based ground motion predictions. In this study, we improved the previously developed stochastic earthquake rupture modeling method by applying the nonparametric co-regionalization, which was proposed in geostatistics, to the correlation models estimated from dynamically derived earthquake rupture models. The nonparametric approach adopted in this study is computationally efficient and, therefore, enables us to simulate numerous rupture scenarios, including large events ( M > 7.0). It also gives us an opportunity to check the shape of true input correlation models in stochastic modeling after being deformed for permissibility. We expect that this type of modeling will improve our ability to simulate a wide range of rupture scenario models and thereby predict ground motions and perform seismic hazard assessment more accurately.

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei

2012-08-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

Motion-based prediction explains the role of tracking in motion extrapolation.

PubMed

Khoei, Mina A; Masson, Guillaume S; Perrinet, Laurent U

2013-11-01

During normal viewing, the continuous stream of visual input is regularly interrupted, for instance by blinks of the eye. Despite these frequents blanks (that is the transient absence of a raw sensory source), the visual system is most often able to maintain a continuous representation of motion. For instance, it maintains the movement of the eye such as to stabilize the image of an object. This ability suggests the existence of a generic neural mechanism of motion extrapolation to deal with fragmented inputs. In this paper, we have modeled how the visual system may extrapolate the trajectory of an object during a blank using motion-based prediction. This implies that using a prior on the coherency of motion, the system may integrate previous motion information even in the absence of a stimulus. In order to compare with experimental results, we simulated tracking velocity responses. We found that the response of the motion integration process to a blanked trajectory pauses at the onset of the blank, but that it quickly recovers the information on the trajectory after reappearance. This is compatible with behavioral and neural observations on motion extrapolation. To understand these mechanisms, we have recorded the response of the model to a noisy stimulus. Crucially, we found that motion-based prediction acted at the global level as a gain control mechanism and that we could switch from a smooth regime to a binary tracking behavior where the dot is tracked or lost. Our results imply that a local prior implementing motion-based prediction is sufficient to explain a large range of neural and behavioral results at a more global level. We show that the tracking behavior deteriorates for sensory noise levels higher than a certain value, where motion coherency and predictability fail to hold longer. In particular, we found that motion-based prediction leads to the emergence of a tracking behavior only when enough information from the trajectory has been accumulated. Then, during tracking, trajectory estimation is robust to blanks even in the presence of relatively high levels of noise. Moreover, we found that tracking is necessary for motion extrapolation, this calls for further experimental work exploring the role of noise in motion extrapolation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Accelerated acquisition of tagged MRI for cardiac motion correction in simultaneous PET-MR: Phantom and patient studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Chuan, E-mail: chuan.huang@stonybrookmedicine.edu; Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115; Departments of Radiology, Psychiatry, Stony Brook Medicine, Stony Brook, New York 11794

2015-02-15

Purpose: Degradation of image quality caused by cardiac and respiratory motions hampers the diagnostic quality of cardiac PET. It has been shown that improved diagnostic accuracy of myocardial defect can be achieved by tagged MR (tMR) based PET motion correction using simultaneous PET-MR. However, one major hurdle for the adoption of tMR-based PET motion correction in the PET-MR routine is the long acquisition time needed for the collection of fully sampled tMR data. In this work, the authors propose an accelerated tMR acquisition strategy using parallel imaging and/or compressed sensing and assess the impact on the tMR-based motion corrected PETmore » using phantom and patient data. Methods: Fully sampled tMR data were acquired simultaneously with PET list-mode data on two simultaneous PET-MR scanners for a cardiac phantom and a patient. Parallel imaging and compressed sensing were retrospectively performed by GRAPPA and kt-FOCUSS algorithms with various acceleration factors. Motion fields were estimated using nonrigid B-spline image registration from both the accelerated and fully sampled tMR images. The motion fields were incorporated into a motion corrected ordered subset expectation maximization reconstruction algorithm with motion-dependent attenuation correction. Results: Although tMR acceleration introduced image artifacts into the tMR images for both phantom and patient data, motion corrected PET images yielded similar image quality as those obtained using the fully sampled tMR images for low to moderate acceleration factors (<4). Quantitative analysis of myocardial defect contrast over ten independent noise realizations showed similar results. It was further observed that although the image quality of the motion corrected PET images deteriorates for high acceleration factors, the images were still superior to the images reconstructed without motion correction. Conclusions: Accelerated tMR images obtained with more than 4 times acceleration can still provide relatively accurate motion fields and yield tMR-based motion corrected PET images with similar image quality as those reconstructed using fully sampled tMR data. The reduction of tMR acquisition time makes it more compatible with routine clinical cardiac PET-MR studies.« less

Visual Target Tracking in the Presence of Unknown Observer Motion

NASA Technical Reports Server (NTRS)

Williams, Stephen; Lu, Thomas

2009-01-01

Much attention has been given to the visual tracking problem due to its obvious uses in military surveillance. However, visual tracking is complicated by the presence of motion of the observer in addition to the target motion, especially when the image changes caused by the observer motion are large compared to those caused by the target motion. Techniques for estimating the motion of the observer based on image registration techniques and Kalman filtering are presented and simulated. With the effects of the observer motion removed, an additional phase is implemented to track individual targets. This tracking method is demonstrated on an image stream from a buoy-mounted or periscope-mounted camera, where large inter-frame displacements are present due to the wave action on the camera. This system has been shown to be effective at tracking and predicting the global position of a planar vehicle (boat) being observed from a single, out-of-plane camera. Finally, the tracking system has been extended to a multi-target scenario.

Crab Pulsar Astrometry and Spin-Velocity Alignment

NASA Astrophysics Data System (ADS)

Romani, Roger W.; Ng, C.-Y.

2009-01-01

The proper motion of the Crab pulsar and its orientation with respect to the PWN symmetry axis is interesting for testing models of neutron star birth kicks. A number of authors have measured the Crab's motion using archival HST images. The most detailed study by Kaplan et al. (2008) compares a wide range of WFPC and ACS images to obtain an accurate proper motion measurement. However, they concluded that a kick comparison is fundamentally limited by the uncertainty in the progenitor's motion. Here we report on new HST images matched to 1994 and 1995 data frames, providing independent proper motion measurement with over 13 year time base and minimal systematic errors. The new observations also allow us to estimate the systematic errors due to CCD saturation. Our preliminary result indicates a proper motion consistent with Kaplan et al.'s finding. We discuss a model for the progenitor's motion, suggesting that the pulsar spin is much closer to alignment than previously suspected.

Transient tidal eddy motion in the western Gulf of Maine, part 1: Primary structure

NASA Astrophysics Data System (ADS)

Brown, W. S.; Marques, G. M.

2013-07-01

High frequency radar-derived surface current maps of the Great South Channel (GSC) in the western Gulf of Maine in 2005 revealed clockwise (CW) and anticlockwise (ACW) eddy motion associated with the strong regional tidal currents. To better elucidate the kinematics and dynamics of these transient tidal eddy motions, an observational and modeling study was conducted during the weakly stratified conditions of winter 2008-2009. Our moored bottom pressure and ADCP current measurements in 13m depth were augmented by historical current measurements in about 30m in documenting the dominance of highly polarized M2 semidiurnal currents in our nearshore study region. The high-resolution finite element coastal ocean model (QUODDY) - forced by the five principal tidal constituents - produced maps depicting the formation and evolution of the CW and ACW eddy motions that regularly follow maximum ebb and flood flows, respectively. Observation versus model current comparison required that the model bottom current drag coefficient be set to at an unusually high Cd=0.01 - suggesting the importance of form drag in the study region. The observations and model results were consistent in diagnosing CW or ACW eddy motions that (a) form nearshore in the coastal boundary layer (CBL) for about 3h after the respective tidal current maxima and then (b) translate southeastward across the GSC along curved 50m isobath at speeds of about 25m/s. Observation-based and model-based momentum budget estimates were consistent in showing a first order forced semidiurnal standing tidal wave dynamics (like the adjacent Gulf of Maine) which was modulated by adverse pressure gradient/bottom stress forcing to generate the eddy motions. Observation-based estimates of terms in the transport vorticity budget showed that in the shallower Inner Zone subregion (average depth=23m) that the diffusion of nearshore vorticity was dominant in feeding the growth of eddy motion vorticity; while in the somewhat deeper Outer Zone subregion (33m) bottom current lateral shear and water column stretching/squashing was significant in modulating the eddy motion. We conclude that the transient eddy motions in the GSC region are phase eddies that accompany the change of tide across the GSC and are (1) generated by bottom stress gradients in the shallower nearshore - an issue which needs to be better understood for improved future forecasting.

Stochastic ground-motion simulations for the 2016 Kumamoto, Japan, earthquake

NASA Astrophysics Data System (ADS)

Zhang, Long; Chen, Guangqi; Wu, Yanqiang; Jiang, Han

2016-11-01

On April 15, 2016, Kumamoto, Japan, was struck by a large earthquake sequence, leading to severe casualty and building damage. The stochastic finite-fault method based on a dynamic corner frequency has been applied to perform ground-motion simulations for the 2016 Kumamoto earthquake. There are 53 high-quality KiK-net stations available in the Kyushu region, and we employed records from all stations to determine region-specific source, path and site parameters. The calculated S-wave attenuation for the Kyushu region beneath the volcanic and non-volcanic areas can be expressed in the form of Q s = (85.5 ± 1.5) f 0.68±0.01 and Q s = (120 ± 5) f 0.64±0.05, respectively. The effects of lateral S-wave velocity and attenuation heterogeneities on the ground-motion simulations were investigated. Site amplifications were estimated using the corrected cross-spectral ratios technique. Zero-distance kappa filter was obtained to be the value of 0.0514 ± 0.0055 s, using the spectral decay method. The stress drop of the mainshock based on the USGS slip model was estimated optimally to have a value of 64 bars. Our finite-fault model with optimized parameters was validated through the good agreement of observations and simulations at all stations. The attenuation characteristics of the simulated peak ground accelerations were also successfully captured by the ground-motion prediction equations. Finally, the ground motions at two destructively damaged regions, Kumamoto Castle and Minami Aso village, were simulated. We conclude that the stochastic finite-fault method with well-determined parameters can reproduce the ground-motion characteristics of the 2016 Kumamoto earthquake in both the time and frequency domains. This work is necessary for seismic hazard assessment and mitigation.[Figure not available: see fulltext.

Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.

Estimating geocenter motion and barystatic sea-level variability from GRACE observations with explicit consideration of self-attraction and loading effects

NASA Astrophysics Data System (ADS)

Bergmann-Wolf, Inga; Dobslaw, Henryk

2016-04-01

Estimating global barystatic sea-level variations from monthly mean gravity fields delivered by the Gravity Recovery and Climate Experiment (GRACE) satellite mission requires additional information about geocenter motion. These variations are not available directly due to the mission implementation in the CM-frame and are represented by the degree-1 terms of the spherical harmonics expansion. Global degree-1 estimates can be determined with the method of Swenson et al. (2008) from ocean mass variability, the geometry of the global land-sea distribution, and GRACE data of higher degrees and orders. Consequently, a recursive relation between the derivation of ocean mass variations from GRACE data and the introduction of geocenter motion into GRACE data exists. In this contribution, we will present a recent improvement to the processing strategy described in Bergmann-Wolf et al. (2014) by introducing a non-homogeneous distribution of global ocean mass variations in the geocenter motion determination strategy, which is due to the effects of loading and self-attraction induced by mass redistributions at the surface. A comparison of different GRACE-based oceanographic products (barystatic signal for both the global oceans and individual basins; barotropic transport variations of major ocean currents) with degree-1 terms estimated with a homogeneous and non-homogeneous ocean mass representation will be discussed, and differences in noise levels in most recent GRACE solutions from GFZ (RL05a), CSR, and JPL (both RL05) and their consequences for the application of this method will be discussed. Swenson, S., D. Chambers and J. Wahr (2008), Estimating geocenter variations from a combination of GRACE and ocean model output, J. Geophys. Res., 113, B08410 Bergmann-Wolf, I., L. Zhang and H. Dobslaw (2014), Global Eustatic Sea-Level Variations for the Approximation of Geocenter Motion from GRACE, J. Geod. Sci., 4, 37-48

Comparison of the hydrological excitation functions HAM of polar motion for the period 1980.0-2007.0

NASA Astrophysics Data System (ADS)

Nastula, J.; Pasnicka, M.; Kolaczek, B.

2011-10-01

In this study we compared contributions of polar motion excitation determined from hydrological models and harmonic coefficients of the Earth gravity field obtained from Gravity Recovery and Climate Experiment (GRACE). Hydrological excitation function (hydrological angular momentum - HAM) has been estimated from models of global hydrology, based on the observed distribution of surface water, snow, ice and soil moisture. All of them were compared with observed Geodetic Angular Momentum (GAM), excitations of polar motion. The spectra of these excitation functions of polar motion and residual geodetic excitation function G-A-O obtained from GAM by elimination of atmospheric and oceanic excitation functions were computed too. Phasor diagrams of the seasonal components of the polar motion excitation functions of all HAM excitation functions as well as of two GRACE solutions: CSR, CNES were determined and discussed.

Stochastic point-source modeling of ground motions in the Cascadia region

USGS Publications Warehouse

Atkinson, G.M.; Boore, D.M.

1997-01-01

A stochastic model is used to develop preliminary ground motion relations for the Cascadia region for rock sites. The model parameters are derived from empirical analyses of seismographic data from the Cascadia region. The model is based on a Brune point-source characterized by a stress parameter of 50 bars. The model predictions are compared to ground-motion data from the Cascadia region and to data from large earthquakes in other subduction zones. The point-source simulations match the observations from moderate events (M 100 km). The discrepancy at large magnitudes suggests further work on modeling finite-fault effects and regional attenuation is warranted. In the meantime, the preliminary equations are satisfactory for predicting motions from events of M < 7 and provide conservative estimates of motions from larger events at distances less than 100 km.

Stress Drop and Its Relationship to Radiated Energy, Ground Motion and Uncertainty

NASA Astrophysics Data System (ADS)

Baltay, A.

2014-12-01

Despite the seemingly diverse circumstances under which crustal earthquakes occur, scale-invariant stress drop and apparent stress, the ratio of radiated seismic energy to moment, is observed. The magnitude-independence of these parameters is central to our understanding of both earthquake physics and strong ground motion genesis. Estimates of stress drop and radiated energy, however, display large amounts of scatter potentially masking any secondary trends in the data. We investigate sources of this uncertainty within the framework of constant stress drop and apparent stress. We first re-visit estimates of energy and stress drop from a variety of earthquake observations and methods, for events ranging from magnitude ~2 to ~9. Using an empirical Green's function (eGf) deconvolution method, which removes the path and site effects, radiated energy and Brune stress drop are estimated for both regional events in the western US and Eastern Honshu, Japan from the HiNet network, as well as teleseismically recorded global great earthquakes [Baltay et al., 2010, 2011, 2014]. In addition to eGf methods, ground-motion based metrics for stress drop are considered, using both KikNet data from Japan [Baltay et al., 2013] and the NGA-West2 data, a very well curated ground-motion database. Both the eGf-based stress drop estimates and those from the NGA-West2 database show a marked decrease in scatter, allowing us to identify deterministic secondary trends in stress drop. We find both an increasing stress drop with depth, as well as a larger stress drop of about 30% on average for mainshock events as compared to on-fault aftershocks. While both of these effects are already included in some ground-motion prediction equations (GMPE), many previous seismological studies have been unable to conclusively uncover these trends because of their considerable scatter. Elucidating these effects in the context of reduced and quantified epistemic uncertainty can help both seismologists and engineers to understand the true aleatory variability of the earthquake source, which may be due to the complex and diverse circumstances under which these earthquake occur and which we are yet unable to model.

Estimation of cardiac motion in cine-MRI sequences by correlation transform optical flow of monogenic features distance

NASA Astrophysics Data System (ADS)

Gao, Bin; Liu, Wanyu; Wang, Liang; Liu, Zhengjun; Croisille, Pierre; Delachartre, Philippe; Clarysse, Patrick

2016-12-01

Cine-MRI is widely used for the analysis of cardiac function in clinical routine, because of its high soft tissue contrast and relatively short acquisition time in comparison with other cardiac MRI techniques. The gray level distribution in cardiac cine-MRI is relatively homogenous within the myocardium, and can therefore make motion quantification difficult. To ensure that the motion estimation problem is well posed, more image features have to be considered. This work is inspired by a method previously developed for color image processing. The monogenic signal provides a framework to estimate the local phase, orientation, and amplitude, of an image, three features which locally characterize the 2D intensity profile. The independent monogenic features are combined into a 3D matrix for motion estimation. To improve motion estimation accuracy, we chose the zero-mean normalized cross-correlation as a matching measure, and implemented a bilateral filter for denoising and edge-preservation. The monogenic features distance is used in lieu of the color space distance in the bilateral filter. Results obtained from four realistic simulated sequences outperformed two other state of the art methods even in the presence of noise. The motion estimation errors (end point error) using our proposed method were reduced by about 20% in comparison with those obtained by the other tested methods. The new methodology was evaluated on four clinical sequences from patients presenting with cardiac motion dysfunctions and one healthy volunteer. The derived strain fields were analyzed favorably in their ability to identify myocardial regions with impaired motion.

The effect of heart motion on parameter bias in dynamic cardiac SPECT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, S.G.; Gullberg, G.T.; Huesman, R.H.

1996-12-31

Dynamic cardiac SPECT can be used to estimate kinetic rate parameters which describe the wash-in and wash-out of tracer activity between the blood and the myocardial tissue. These kinetic parameters can in turn be correlated to myocardial perfusion. There are, however, many physical aspects associated with dynamic SPECT which can introduce errors into the estimates. This paper describes a study which investigates the effect of heart motion on kinetic parameter estimates. Dynamic SPECT simulations are performed using a beating version of the MCAT phantom. The results demonstrate that cardiac motion has a significant effect on the blood, tissue, and backgroundmore » content of regions of interest. This in turn affects estimates of wash-in, while it has very little effect on estimates of wash-out. The effect of cardiac motion on parameter estimates appears not to be as great as effects introduced by photon noise and geometric collimator response. It is also shown that cardiac motion results in little extravascular contamination of the left ventricle blood region of interest.« less

EVA Robotic Assistant Project: Platform Attitude Prediction

NASA Technical Reports Server (NTRS)

Nickels, Kevin M.

2003-01-01

The Robotic Systems Technology Branch is currently working on the development of an EVA Robotic Assistant under the sponsorship of the Surface Systems Thrust of the NASA Cross Enterprise Technology Development Program (CETDP). This will be a mobile robot that can follow a field geologist during planetary surface exploration, carry his tools and the samples that he collects, and provide video coverage of his activity. Prior experiments have shown that for such a robot to be useful it must be able to follow the geologist at walking speed over any terrain of interest. Geologically interesting terrain tends to be rough rather than smooth. The commercial mobile robot that was recently purchased as an initial testbed for the EVA Robotic Assistant Project, an ATRV Jr., is capable of faster than walking speed outside but it has no suspension. Its wheels with inflated rubber tires are attached to axles that are connected directly to the robot body. Any angular motion of the robot produced by driving over rough terrain will directly affect the pointing of the on-board stereo cameras. The resulting image motion is expected to make tracking of the geologist more difficult. This will either require the tracker to search a larger part of the image to find the target from frame to frame or to search mechanically in pan and tilt whenever the image motion is large enough to put the target outside the image in the next frame. This project consists of the design and implementation of a Kalman filter that combines the output of the angular rate sensors and linear accelerometers on the robot to estimate the motion of the robot base. The motion of the stereo camera pair mounted on the robot that results from this motion as the robot drives over rough terrain is then straightforward to compute. The estimates may then be used, for example, to command the robot s on-board pan-tilt unit to compensate for the camera motion induced by the base movement. This has been accomplished in two ways: first, a standalone head stabilizer has been implemented and second, the estimates have been used to influence the search algorithm of the stereo tracking algorithm. Studies of the image motion of a tracked object indicate that the image motion of objects is suppressed while the robot crossing rough terrain. This work expands the range of speed and surface roughness over which the robot should be able to track and follow a field geologist and accept arm gesture commands from the geologist.

A learning scheme for reach to grasp movements: on EMG-based interfaces using task specific motion decoding models.

PubMed

Liarokapis, Minas V; Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J; Manolakos, Elias S

2013-09-01

A learning scheme based on random forests is used to discriminate between different reach to grasp movements in 3-D space, based on the myoelectric activity of human muscles of the upper-arm and the forearm. Task specificity for motion decoding is introduced in two different levels: Subspace to move toward and object to be grasped. The discrimination between the different reach to grasp strategies is accomplished with machine learning techniques for classification. The classification decision is then used in order to trigger an EMG-based task-specific motion decoding model. Task specific models manage to outperform "general" models providing better estimation accuracy. Thus, the proposed scheme takes advantage of a framework incorporating both a classifier and a regressor that cooperate advantageously in order to split the task space. The proposed learning scheme can be easily used to a series of EMG-based interfaces that must operate in real time, providing data-driven capabilities for multiclass problems, that occur in everyday life complex environments.

Evaluation of modal pushover-based scaling of one component of ground motion: Tall buildings

USGS Publications Warehouse

Kalkan, Erol; Chopra, Anil K.

2012-01-01

Nonlinear response history analysis (RHA) is now increasingly used for performance-based seismic design of tall buildings. Required for nonlinear RHAs is a set of ground motions selected and scaled appropriately so that analysis results would be accurate (unbiased) and efficient (having relatively small dispersion). This paper evaluates accuracy and efficiency of recently developed modal pushover–based scaling (MPS) method to scale ground motions for tall buildings. The procedure presented explicitly considers structural strength and is based on the standard intensity measure (IM) of spectral acceleration in a form convenient for evaluating existing structures or proposed designs for new structures. Based on results presented for two actual buildings (19 and 52 stories, respectively), it is demonstrated that the MPS procedure provided a highly accurate estimate of the engineering demand parameters (EDPs), accompanied by significantly reduced record-to-record variability of the responses. In addition, the MPS procedure is shown to be superior to the scaling procedure specified in the ASCE/SEI 7-05 document.

Evaluation of Rigid-Body Motion Compensation in Cardiac Perfusion SPECT Employing Polar-Map Quantification

PubMed Central

Pretorius, P. Hendrik; Johnson, Karen L.; King, Michael A.

2016-01-01

We have recently been successful in the development and testing of rigid-body motion tracking, estimation and compensation for cardiac perfusion SPECT based on a visual tracking system (VTS). The goal of this study was to evaluate in patients the effectiveness of our rigid-body motion compensation strategy. Sixty-four patient volunteers were asked to remain motionless or execute some predefined body motion during an additional second stress perfusion acquisition. Acquisitions were performed using the standard clinical protocol with 64 projections acquired through 180 degrees. All data were reconstructed with an ordered-subsets expectation-maximization (OSEM) algorithm using 4 projections per subset and 5 iterations. All physical degradation factors were addressed (attenuation, scatter, and distance dependent resolution), while a 3-dimensional Gaussian rotator was used during reconstruction to correct for six-degree-of-freedom (6-DOF) rigid-body motion estimated by the VTS. Polar map quantification was employed to evaluate compensation techniques. In 54.7% of the uncorrected second stress studies there was a statistically significant difference in the polar maps, and in 45.3% this made a difference in the interpretation of segmental perfusion. Motion correction reduced the impact of motion such that with it 32.8 % of the polar maps were statistically significantly different, and in 14.1% this difference changed the interpretation of segmental perfusion. The improvement shown in polar map quantitation translated to visually improved uniformity of the SPECT slices. PMID:28042170

THE SOLAR NEIGHBORHOOD. XXV. DISCOVERY OF NEW PROPER MOTION STARS WITH 0.''40 yr{sup -1} > {mu} {>=} 0.''18 yr{sup -1} BETWEEN DECLINATIONS -47{sup 0} AND 00{sup 0}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, Mark R.; Winters, Jennifer G.; Henry, Todd J.

2011-07-15

We present 2817 new southern proper motion systems with 0.''40 yr{sup -1} > {mu} {>=} 0.''18 yr{sup -1} and declination between -47{sup 0} and 00{sup 0}. This is a continuation of the SuperCOSMOS-RECONS (SCR) proper motion searches of the southern sky. We use the same photometric relations as previous searches to provide distance estimates based on the assumption that the objects are single main-sequence stars. We find 79 new red dwarf systems predicted to be within 25 pc, including a few new components of previously known systems. Two systems-SCR 1731-2452 at 9.5 pc and SCR 1746-3214 at 9.9 pc-are anticipatedmore » to be within 10 pc. We also find 23 new white dwarf (WD) candidates with distance estimates of 15-66 pc, as well as 360 new red subdwarf candidates. With this search, we complete the SCR sweep of the southern sky for stars with {mu} {>=} 0.''18 yr{sup -1} and R{sub 59F} {<=} 16.5, resulting in a total of 5042 objects in 4724 previously unreported proper motion systems. Here we provide selected comprehensive lists from our SCR proper motion search to date, including 152 red dwarf systems estimated to be within 25 pc (9 within 10 pc), 46 WDs (10 within 25 pc), and 598 subdwarf candidates. The results of this search suggest that there are more nearby systems to be found at fainter magnitudes and lower proper motion limits than those probed so far.« less

Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles.

PubMed

Atman, Jamal; Popp, Manuel; Ruppelt, Jan; Trommer, Gert F

2016-09-16

Micro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV's navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results.

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

Estimation of spatial-temporal gait parameters using a low-cost ultrasonic motion analysis system.

PubMed

Qi, Yongbin; Soh, Cheong Boon; Gunawan, Erry; Low, Kay-Soon; Thomas, Rijil

2014-08-20

In this paper, a low-cost motion analysis system using a wireless ultrasonic sensor network is proposed and investigated. A methodology has been developed to extract spatial-temporal gait parameters including stride length, stride duration, stride velocity, stride cadence, and stride symmetry from 3D foot displacements estimated by the combination of spherical positioning technique and unscented Kalman filter. The performance of this system is validated against a camera-based system in the laboratory with 10 healthy volunteers. Numerical results show the feasibility of the proposed system with average error of 2.7% for all the estimated gait parameters. The influence of walking speed on the measurement accuracy of proposed system is also evaluated. Statistical analysis demonstrates its capability of being used as a gait assessment tool for some medical applications.

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1989-01-01

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Spatial correlation of probabilistic earthquake ground motion and loss

USGS Publications Warehouse

Wesson, R.L.; Perkins, D.M.

2001-01-01

Spatial correlation of annual earthquake ground motions and losses can be used to estimate the variance of annual losses to a portfolio of properties exposed to earthquakes A direct method is described for the calculations of the spatial correlation of earthquake ground motions and losses. Calculations for the direct method can be carried out using either numerical quadrature or a discrete, matrix-based approach. Numerical results for this method are compared with those calculated from a simple Monte Carlo simulation. Spatial correlation of ground motion and loss is induced by the systematic attenuation of ground motion with distance from the source, by common site conditions, and by the finite length of fault ruptures. Spatial correlation is also strongly dependent on the partitioning of the variability, given an event, into interevent and intraevent components. Intraevent variability reduces the spatial correlation of losses. Interevent variability increases spatial correlation of losses. The higher the spatial correlation, the larger the variance in losses to a port-folio, and the more likely extreme values become. This result underscores the importance of accurately determining the relative magnitudes of intraevent and interevent variability in ground-motion studies, because of the strong impact in estimating earthquake losses to a portfolio. The direct method offers an alternative to simulation for calculating the variance of losses to a portfolio, which may reduce the amount of calculation required.

Regional cardiac wall motion from gated myocardial perfusion SPECT studies

NASA Astrophysics Data System (ADS)

Smith, M. F.; Brigger, P.; Ferrand, S. K.; Dilsizian, V.; Bacharach, S. L.

1999-06-01

A method for estimating regional epicardial and endocardial wall motion from gated myocardial perfusion SPECT studies has been developed. The method uses epicardial and endocardial boundaries determined from four long-axis slices at each gate of the cardiac cycle. The epicardial and endocardial wall position at each time gate is computed with respect to stationary reference ellipsoids, and wall motion is measured along lines normal to these ellipsoids. An initial quantitative evaluation of the method was made using the beating heart from the dynamic mathematical cardiac torso (MCAT) phantom, with and without a 1.5-cm FWHM Gaussian blurring filter. Epicardial wall motion was generally well-estimated within a fraction of a 3.56-mm voxel, although apical motion was overestimated with the Gaussian filter. Endocardial wall motion was underestimated by about two voxels with and without the Gaussian filter. The MCAT heart phantom was modified to model hypokinetic and dyskinetic wall motion. The wall motion analysis method enabled this abnormal motion to be differentiated from normal motion. Regional cardiac wall motion also was analyzed for /sup 201/Tl patient studies. Estimated wall motion was consistent with a nuclear medicine physician's visual assessment of motion from gated long-axis slices for male and female study examples. Additional research is required for a comprehensive evaluation of the applicability of the method to patient studies with normal and abnormal wall motion.

Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.

PubMed

Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien

2017-01-01

Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.

Accelerometer-based wireless body area network to estimate intensity of therapy in post-acute rehabilitation

PubMed Central

Choquette, Stéphane; Hamel, Mathieu; Boissy, Patrick

2008-01-01

Background It has been suggested that there is a dose-response relationship between the amount of therapy and functional recovery in post-acute rehabilitation care. To this day, only the total time of therapy has been investigated as a potential determinant of this dose-response relationship because of methodological and measurement challenges. The primary objective of this study was to compare time and motion measures during real life physical therapy with estimates of active time (i.e. the time during which a patient is active physically) obtained with a wireless body area network (WBAN) of 3D accelerometer modules positioned at the hip, wrist and ankle. The secondary objective was to assess the differences in estimates of active time when using a single accelerometer module positioned at the hip. Methods Five patients (77.4 ± 5.2 y) with 4 different admission diagnoses (stroke, lower limb fracture, amputation and immobilization syndrome) were recruited in a post-acute rehabilitation center and observed during their physical therapy sessions throughout their stay. Active time was recorded by a trained observer using a continuous time and motion analysis program running on a Tablet-PC. Two WBAN configurations were used: 1) three accelerometer modules located at the hip, wrist and ankle (M3) and 2) one accelerometer located at the hip (M1). Acceleration signals from the WBANs were synchronized with the observations. Estimates of active time were computed based on the temporal density of the acceleration signals. Results A total of 62 physical therapy sessions were observed. Strong associations were found between WBANs estimates of active time and time and motion measures of active time. For the combined sessions, the intraclass correlation coefficient (ICC) was 0.93 (P ≤ 0.001) for M3 and 0.79 (P ≤ 0.001) for M1. The mean percentage of differences between observation measures and estimates from the WBAN of active time was -8.7% ± 2.0% using data from M3 and -16.4% ± 10.4% using data from M1. Conclusion WBANs estimates of active time compare favorably with results from observation-based time and motion measures. While the investigation on the association between active time and outcomes of rehabilitation needs to be studied in a larger scale study, the use of an accelerometer-based WBAN to measure active time is a promising approach that offers a better overall precision than methods relying on work sampling. Depending on the accuracy needed, the use of a single accelerometer module positioned on the hip may still be an interesting alternative to using multiple modules. PMID:18764954

Estimating 3D positions and velocities of projectiles from monocular views.

PubMed

Ribnick, Evan; Atev, Stefan; Papanikolopoulos, Nikolaos P

2009-05-01

In this paper, we consider the problem of localizing a projectile in 3D based on its apparent motion in a stationary monocular view. A thorough theoretical analysis is developed, from which we establish the minimum conditions for the existence of a unique solution. The theoretical results obtained have important implications for applications involving projectile motion. A robust, nonlinear optimization-based formulation is proposed, and the use of a local optimization method is justified by detailed examination of the local convexity structure of the cost function. The potential of this approach is validated by experimental results.

Efficient region-based approach for blotch detection in archived video using texture information

NASA Astrophysics Data System (ADS)

Yous, Hamza; Serir, Amina

2017-03-01

We propose a method for blotch detection in archived videos by modeling their spatiotemporal properties. We introduce an adaptive spatiotemporal segmentation to extract candidate regions that can be classified as blotches. Then, the similarity between the preselected regions and their corresponding motion-compensated regions in the adjacent frames is assessed by means of motion trajectory estimation and textural information analysis. Perceived ground truth based on just noticeable contrast is employed for the evaluation of our approach against the state-of-the-art, and the reported results show a better performance for our approach.

Vertical Jump Height Estimation Algorithm Based on Takeoff and Landing Identification Via Foot-Worn Inertial Sensing.

PubMed

Wang, Jianren; Xu, Junkai; Shull, Peter B

2018-03-01

Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were -2.2±2.1 cm and -0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=-10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.

Determining the 3-D structure and motion of objects using a scanning laser range sensor

NASA Technical Reports Server (NTRS)

Nandhakumar, N.; Smith, Philip W.

1993-01-01

In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

Multi-Shot Sensitivity-Encoded Diffusion Data Recovery Using Structured Low-Rank Matrix Completion (MUSSELS)

PubMed Central

Mani, Merry; Jacob, Mathews; Kelley, Douglas; Magnotta, Vincent

2017-01-01

Purpose To introduce a novel method for the recovery of multi-shot diffusion weighted (MS-DW) images from echo-planar imaging (EPI) acquisitions. Methods Current EPI-based MS-DW reconstruction methods rely on the explicit estimation of the motion-induced phase maps to recover artifact-free images. In the new formulation, the k-space data of the artifact-free DWI is recovered using a structured low-rank matrix completion scheme, which does not require explicit estimation of the phase maps. The structured matrix is obtained as the lifting of the multi-shot data. The smooth phase-modulations between shots manifest as null-space vectors of this matrix, which implies that the structured matrix is low-rank. The missing entries of the structured matrix are filled in using a nuclear-norm minimization algorithm subject to the data-consistency. The formulation enables the natural introduction of smoothness regularization, thus enabling implicit motion-compensated recovery of the MS-DW data. Results Our experiments on in-vivo data show effective removal of artifacts arising from inter-shot motion using the proposed method. The method is shown to achieve better reconstruction than the conventional phase-based methods. Conclusion We demonstrate the utility of the proposed method to effectively recover artifact-free images from Cartesian fully/under-sampled and partial Fourier acquired data without the use of explicit phase estimates. PMID:27550212

Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

PubMed

Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

2017-12-25

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

A pose estimation method for unmanned ground vehicles in GPS denied environments

NASA Astrophysics Data System (ADS)

Tamjidi, Amirhossein; Ye, Cang

2012-06-01

This paper presents a pose estimation method based on the 1-Point RANSAC EKF (Extended Kalman Filter) framework. The method fuses the depth data from a LIDAR and the visual data from a monocular camera to estimate the pose of a Unmanned Ground Vehicle (UGV) in a GPS denied environment. Its estimation framework continuy updates the vehicle's 6D pose state and temporary estimates of the extracted visual features' 3D positions. In contrast to the conventional EKF-SLAM (Simultaneous Localization And Mapping) frameworks, the proposed method discards feature estimates from the extended state vector once they are no longer observed for several steps. As a result, the extended state vector always maintains a reasonable size that is suitable for online calculation. The fusion of laser and visual data is performed both in the feature initialization part of the EKF-SLAM process and in the motion prediction stage. A RANSAC pose calculation procedure is devised to produce pose estimate for the motion model. The proposed method has been successfully tested on the Ford campus's LIDAR-Vision dataset. The results are compared with the ground truth data of the dataset and the estimation error is ~1.9% of the path length.

Adaptive mesh optimization and nonrigid motion recovery based image registration for wide-field-of-view ultrasound imaging.

PubMed

Tan, Chaowei; Wang, Bo; Liu, Paul; Liu, Dong

2008-01-01

Wide field of view (WFOV) imaging mode obtains an ultrasound image over an area much larger than the real time window normally available. As the probe is moved over the region of interest, new image frames are combined with prior frames to form a panorama image. Image registration techniques are used to recover the probe motion, eliminating the need for a position sensor. Speckle patterns, which are inherent in ultrasound imaging, change, or become decorrelated, as the scan plane moves, so we pre-smooth the image to reduce the effects of speckle in registration, as well as reducing effects from thermal noise. Because we wish to track the movement of features such as structural boundaries, we use an adaptive mesh over the entire smoothed image to home in on areas with feature. Motion estimation using blocks centered at the individual mesh nodes generates a field of motion vectors. After angular correction of motion vectors, we model the overall movement between frames as a nonrigid deformation. The polygon filling algorithm for precise, persistence-based spatial compounding constructs the final speckle reduced WFOV image.

Magnetowetting and sliding motion of a sessile ferrofluid droplet in the presence of a permanent magnet.

PubMed

Nguyen, Nam-Trung; Zhu, Guiping; Chua, Yong-Chin; Phan, Vinh-Nguyen; Tan, Say-Hwa

2010-08-03

Motion of a droplet on a planar surface has applications in droplet-based lab on a chip technology. This paper reports the experimental results of the shape, contact angles, and motion of ferrofluid droplets driven by a permanent magnet on a planar homogeneous surface. The water-based ferrofluid in use is a colloidal suspension of single-domain magnetic nanoparticles. The effect of the magnetic field on the apparent contact angle of the ferrofluid droplet was first investigated. The results show that an increasing magnetic flux decreases the apparent contact angle of a sessile ferrofluid droplet. Next, the dynamic contact angle was investigated by observing the shape and the motion of a sessile ferrofluid droplet. The advancing and receding contact angles of the moving ferrofluid were measured at different moving speeds and magnetic field strengths. The measured contact angles were used to estimate the magnitude of the forces involved in the sliding motion. Scaling analysis was carried out to derive the critical velocity, beyond which the droplet is not able to catch up with the moving magnet.

Motion Estimation Using the Firefly Algorithm in Ultrasonic Image Sequence of Soft Tissue

PubMed Central

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method. PMID:25873987

Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.

PubMed

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

Joint estimation of subject motion and tracer kinetic parameters of dynamic PET data in an EM framework

NASA Astrophysics Data System (ADS)

Jiao, Jieqing; Salinas, Cristian A.; Searle, Graham E.; Gunn, Roger N.; Schnabel, Julia A.

2012-02-01

Dynamic Positron Emission Tomography is a powerful tool for quantitative imaging of in vivo biological processes. The long scan durations necessitate motion correction, to maintain the validity of the dynamic measurements, which can be particularly challenging due to the low signal-to-noise ratio (SNR) and spatial resolution, as well as the complex tracer behaviour in the dynamic PET data. In this paper we develop a novel automated expectation-maximisation image registration framework that incorporates temporal tracer kinetic information to correct for inter-frame subject motion during dynamic PET scans. We employ the Zubal human brain phantom to simulate dynamic PET data using SORTEO (a Monte Carlo-based simulator), in order to validate the proposed method for its ability to recover imposed rigid motion. We have conducted a range of simulations using different noise levels, and corrupted the data with a range of rigid motion artefacts. The performance of our motion correction method is compared with pairwise registration using normalised mutual information as a voxel similarity measure (an approach conventionally used to correct for dynamic PET inter-frame motion based solely on intensity information). To quantify registration accuracy, we calculate the target registration error across the images. The results show that our new dynamic image registration method based on tracer kinetics yields better realignment of the simulated datasets, halving the target registration error when compared to the conventional method at small motion levels, as well as yielding smaller residuals in translation and rotation parameters. We also show that our new method is less affected by the low signal in the first few frames, which the conventional method based on normalised mutual information fails to realign.

Repurposing video recordings for structure motion estimations

NASA Astrophysics Data System (ADS)

Khaloo, Ali; Lattanzi, David

2016-04-01

Video monitoring of public spaces is becoming increasingly ubiquitous, particularly near essential structures and facilities. During any hazard event that dynamically excites a structure, such as an earthquake or hurricane, proximal video cameras may inadvertently capture the motion time-history of the structure during the event. If this dynamic time-history could be extracted from the repurposed video recording it would become a valuable forensic analysis tool for engineers performing post-disaster structural evaluations. The difficulty is that almost all potential video cameras are not installed to monitor structure motions, leading to camera perspective distortions and other associated challenges. This paper presents a method for extracting structure motions from videos using a combination of computer vision techniques. Images from a video recording are first reprojected into synthetic images that eliminate perspective distortion, using as-built knowledge of a structure for calibration. The motion of the camera itself during an event is also considered. Optical flow, a technique for tracking per-pixel motion, is then applied to these synthetic images to estimate the building motion. The developed method was validated using the experimental records of the NEESHub earthquake database. The results indicate that the technique is capable of estimating structural motions, particularly the frequency content of the response. Further work will evaluate variants and alternatives to the optical flow algorithm, as well as study the impact of video encoding artifacts on motion estimates.

The Influence of Head Motion on Intrinsic Functional Connectivity MRI

PubMed Central

Van Dijk, Koene R.A.; Sabuncu, Mert R.; Buckner, Randy L.

2011-01-01

Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (> 0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to estimated head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks – two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions – a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals. PMID:21810475

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

NASA Technical Reports Server (NTRS)

Maimone, Mark; Johnson, Andrew; Cheng, Yang; Willson, Reg; Matthies, Larry H.

2004-01-01

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

A novel unscented predictive filter for relative position and attitude estimation of satellite formation

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Xiaoqian; Misra, Arun K.

2015-07-01

This paper presents a novel sigma-point unscented predictive filter (UPF) for relative position and attitude estimation of satellite formation taking into account the influence of J2. A coupled relative translational dynamics model is formulated to represent orbital motion of arbitrary feature points on the deputy spacecraft, and the relative attitude motion is formulated by considering a rotational dynamics for a satellite without gyros. Based on the proposed coupled dynamic model, the UPF is developed based on unscented transformation technique, extending the capability of a traditional predictive filter (PF). The algorithm flow of the UPF is described first. Then it is demonstrated that the estimation accuracy of the model error and system state for UPF is higher than that of the traditional PF. In addition, the unscented Kalman filter (UKF) is also employed in order to compare the performance of the proposed UPF with that of the UKF. Several different scenarios are simulated to validate the effectiveness of the coupled dynamics model and the performance of the proposed UPF. Through comparisons, the proposed UPF is shown to yield highly accurate estimation of relative position and attitude during satellite formation flying.

Automatic assessment of average diaphragm motion trajectory from 4DCT images through machine learning.

PubMed

Li, Guang; Wei, Jie; Huang, Hailiang; Gaebler, Carl Philipp; Yuan, Amy; Deasy, Joseph O

2015-12-01

To automatically estimate average diaphragm motion trajectory (ADMT) based on four-dimensional computed tomography (4DCT), facilitating clinical assessment of respiratory motion and motion variation and retrospective motion study. We have developed an effective motion extraction approach and a machine-learning-based algorithm to estimate the ADMT. Eleven patients with 22 sets of 4DCT images (4DCT1 at simulation and 4DCT2 at treatment) were studied. After automatically segmenting the lungs, the differential volume-per-slice (dVPS) curves of the left and right lungs were calculated as a function of slice number for each phase with respective to the full-exhalation. After 5-slice moving average was performed, the discrete cosine transform (DCT) was applied to analyze the dVPS curves in frequency domain. The dimensionality of the spectrum data was reduced by using several lowest frequency coefficients ( f v ) to account for most of the spectrum energy (Σ f v 2 ). Multiple linear regression (MLR) method was then applied to determine the weights of these frequencies by fitting the ground truth-the measured ADMT, which are represented by three pivot points of the diaphragm on each side. The 'leave-one-out' cross validation method was employed to analyze the statistical performance of the prediction results in three image sets: 4DCT1, 4DCT2, and 4DCT1 + 4DCT2. Seven lowest frequencies in DCT domain were found to be sufficient to approximate the patient dVPS curves ( R = 91%-96% in MLR fitting). The mean error in the predicted ADMT using leave-one-out method was 0.3 ± 1.9 mm for the left-side diaphragm and 0.0 ± 1.4 mm for the right-side diaphragm. The prediction error is lower in 4DCT2 than 4DCT1, and is the lowest in 4DCT1 and 4DCT2 combined. This frequency-analysis-based machine learning technique was employed to predict the ADMT automatically with an acceptable error (0.2 ± 1.6 mm). This volumetric approach is not affected by the presence of the lung tumors, providing an automatic robust tool to evaluate diaphragm motion.

Horizontal crustal motion in the central and eastern Mediterranean inferred from Satellite Laser Ranging measurements

NASA Technical Reports Server (NTRS)

Smith, David E.; Kolenkiewicz, Ron; Robbins, John W.; Dunn, Peter J.; Torrence, Mark H.

1994-01-01

Four campaigns to acquire Satellite Laser Ranging (SLR) measurements at sites in the Mediterranean region have been completed. These measurements to the LAGEOS satellite, made largely by mobile systems, cover a time span beginning in November 1985 and ending in June 1993. The range data from 18 sites in the central and eastern Mediterranean have been simultaneously analyzed with data acquired by the remainder of the global laser tracking network. Estimates of horizontal motion were placed into a regional, northern Europe-fixed, kinematic reference frame. Uncertainties are on the order of 5 mm/yr for sites having at least four occupations by mobile systems and approach 1 mm/yr for permanently located sites with long histories of tracking. The resulting relative motion between sites in the Aegean exhibit characteristics of broadly distributed pattern of radial extension, but at rates that are about 50% larger than those implied from studies of seismic strain rates based on seismicity of magnitude 6 or greater or across the region. The motion estimated for sites in Turkey exhibit velocity components associated with the westward motion of the Anatolian Block relative to Eurasia. These results provide a present-day 'snapshot' of ongoing deformational processes as experienced by the locations occupied by SLR systems.

Time-frequency analysis of human motion during rhythmic exercises.

PubMed

Omkar, S N; Vyas, Khushi; Vikranth, H N

2011-01-01

Biomechanical signals due to human movements during exercise are represented in time-frequency domain using Wigner Distribution Function (WDF). Analysis based on WDF reveals instantaneous spectral and power changes during a rhythmic exercise. Investigations were carried out on 11 healthy subjects who performed 5 cycles of sun salutation, with a body-mounted Inertial Measurement Unit (IMU) as a motion sensor. Variance of Instantaneous Frequency (I.F) and Instantaneous Power (I.P) for performance analysis of the subject is estimated using one-way ANOVA model. Results reveal that joint Time-Frequency analysis of biomechanical signals during motion facilitates a better understanding of grace and consistency during rhythmic exercise.

Measuring the self-similarity exponent in Lévy stable processes of financial time series

NASA Astrophysics Data System (ADS)

Fernández-Martínez, M.; Sánchez-Granero, M. A.; Trinidad Segovia, J. E.

2013-11-01

Geometric method-based procedures, which will be called GM algorithms herein, were introduced in [M.A. Sánchez Granero, J.E. Trinidad Segovia, J. García Pérez, Some comments on Hurst exponent and the long memory processes on capital markets, Phys. A 387 (2008) 5543-5551], to efficiently calculate the self-similarity exponent of a time series. In that paper, the authors showed empirically that these algorithms, based on a geometrical approach, are more accurate than the classical algorithms, especially with short length time series. The authors checked that GM algorithms are good when working with (fractional) Brownian motions. Moreover, in [J.E. Trinidad Segovia, M. Fernández-Martínez, M.A. Sánchez-Granero, A note on geometric method-based procedures to calculate the Hurst exponent, Phys. A 391 (2012) 2209-2214], a mathematical background for the validity of such procedures to estimate the self-similarity index of any random process with stationary and self-affine increments was provided. In particular, they proved theoretically that GM algorithms are also valid to explore long-memory in (fractional) Lévy stable motions. In this paper, we prove empirically by Monte Carlo simulation that GM algorithms are able to calculate accurately the self-similarity index in Lévy stable motions and find empirical evidence that they are more precise than the absolute value exponent (denoted by AVE onwards) and the multifractal detrended fluctuation analysis (MF-DFA) algorithms, especially with a short length time series. We also compare them with the generalized Hurst exponent (GHE) algorithm and conclude that both GM2 and GHE algorithms are the most accurate to study financial series. In addition to that, we provide empirical evidence, based on the accuracy of GM algorithms to estimate the self-similarity index in Lévy motions, that the evolution of the stocks of some international market indices, such as U.S. Small Cap and Nasdaq100, cannot be modelized by means of a Brownian motion.

Estimation of interplate coupling along Nankai trough considering the block motion model based on onland GNSS and seafloor GPS/A observation data using MCMC method

NASA Astrophysics Data System (ADS)

Kimura, H.; Ito, T.; Tadokoro, K.

2017-12-01

Introduction In southwest Japan, Philippine sea plate is subducting under the overriding plate such as Amurian plate, and mega interplate earthquakes has occurred at about 100 years interval. There is no occurrence of mega interplate earthquakes in southwest Japan, although it has passed about 70 years since the last mega interplate earthquakes: 1944 and 1946 along Nankai trough, meaning that the strain has been accumulated at plate interface. Therefore, it is essential to reveal the interplate coupling more precisely for predicting or understanding the mechanism of next occurring mega interplate earthquake. Recently, seafloor geodetic observation revealed the detailed interplate coupling distribution in expected source region of Nankai trough earthquake (e.g., Yokota et al. [2016]). In this study, we estimated interplate coupling in southwest Japan, considering block motion model and using seafloor geodetic observation data as well as onland GNSS observation data, based on Markov Chain Monte Carlo (MCMC) method. Method Observed crustal deformation is assumed that sum of rigid block motion and elastic deformation due to coupling at block boundaries. We modeled this relationship as a non-linear inverse problem that the unknown parameters are Euler pole of each block and coupling at each subfault, and solved them simultaneously based on MCMC method. Input data we used in this study are 863 onland GNSS observation data and 24 seafloor GPS/A observation data. We made some block division models based on the map of active fault tracing and selected the best model based on Akaike's Information Criterion (AIC): that is consist of 12 blocks. Result We find that the interplate coupling along Nankai trough has heterogeneous spatial distribution, strong at the depth of 0 to 20km at off Tokai region, and 0 to 30km at off Shikoku region. Moreover, we find that observed crustal deformation at off Tokai region is well explained by elastic deformation due to subducting Izu Micro Plate. We will present more details of our result, and discuss about not only interplate coupling but also rigid block motion, elastic deformation due to inland fault coupling, and resolution of estimated parameters.

Contact angle hysteresis and motion behaviors of a water nano-droplet on suspended graphene under temperature gradient

NASA Astrophysics Data System (ADS)

Foroutan, Masumeh; Fatemi, S. Mahmood; Esmaeilian, Farshad; Fadaei Naeini, Vahid; Baniassadi, Majid

2018-05-01

In the present work, the effect of temperature gradient on the behavior of a water nano-droplet resting on a suspended graphene was studied based on a non-equilibrium molecular dynamics simulation. The acquired results indicate that the applied temperature gradient to the suspended graphene drives the water nano-droplet to the colder region. The droplet accelerates its motion toward the cold reservoir as the temperature gradient is increased. In addition to the translational motion of the nano-droplet, the vortical motion of the water molecules was also observed. Contact angle analysis was also utilized to describe the directional motion of the nano-droplet. The translational motion of the droplet leads to the estimation of contact angle hysteresis through advancing and receding contact angles while the rotational motion resulted in the advancing and receding fronts being switched with one another through the simulation. The average displacement vector of the water molecules shows that parts of the droplet seem to stagnate while other parts rotate around them. The reason behind this particular behavior was studied based on interaction energy contours between a water molecule and the suspended graphene. The obtained data indicate that the rotational motion is in agreement with the migration of the water molecules to low interaction energy regions in order to avoid high interaction energy areas.

Slow dynamics of a protein backbone in molecular dynamics simulation revealed by time-structure based independent component analysis

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2013-12-01

We recently proposed the method of time-structure based independent component analysis (tICA) to examine the slow dynamics involved in conformational fluctuations of a protein as estimated by molecular dynamics (MD) simulation [Y. Naritomi and S. Fuchigami, J. Chem. Phys. 134, 065101 (2011)]. Our previous study focused on domain motions of the protein and examined its dynamics by using rigid-body domain analysis and tICA. However, the protein changes its conformation not only through domain motions but also by various types of motions involving its backbone and side chains. Some of these motions might occur on a slow time scale: we hypothesize that if so, we could effectively detect and characterize them using tICA. In the present study, we investigated slow dynamics of the protein backbone using MD simulation and tICA. The selected target protein was lysine-, arginine-, ornithine-binding protein (LAO), which comprises two domains and undergoes large domain motions. MD simulation of LAO in explicit water was performed for 1 μs, and the obtained trajectory of Cα atoms in the backbone was analyzed by tICA. This analysis successfully provided us with slow modes for LAO that represented either domain motions or local movements of the backbone. Further analysis elucidated the atomic details of the suggested local motions and confirmed that these motions truly occurred on the expected slow time scale.

Model-Based Wavefront Control for CCAT

NASA Technical Reports Server (NTRS)

Redding, David; Lou, John Z.; Kissil, Andy; Bradford, Matt; Padin, Steve; Woody, David

2011-01-01

The 25-m aperture CCAT submillimeter-wave telescope will have a primary mirror that is divided into 162 individual segments, each of which is provided with 3 positioning actuators. CCAT will be equipped with innovative Imaging Displacement Sensors (IDS) inexpensive optical edge sensors capable of accurately measuring all segment relative motions. These measurements are used in a Kalman-filter-based Optical State Estimator to estimate wavefront errors, permitting use of a minimum-wavefront controller without direct wavefront measurement. This controller corrects the optical impact of errors in 6 degrees of freedom per segment, including lateral translations of the segments, using only the 3 actuated degrees of freedom per segment. The global motions of the Primary and Secondary Mirrors are not measured by the edge sensors. These are controlled using a gravity-sag look-up table. Predicted performance is illustrated by simulated response to errors such as gravity sag.

CFD simulation of vertical linear motion mixing in anaerobic digester tanks.

PubMed

Meroney, Robert N; Sheker, Robert E

2014-09-01

Computational fluid dynamics (CFD) was used to simulate the mixing characteristics of a small circular anaerobic digester tank (diameter 6 m) equipped sequentially with 13 different plunger type vertical linear motion mixers and two different type internal draft-tube mixers. Rates of mixing of step injection of tracers were calculated from which active volume (AV) and hydraulic retention time (HRT) could be calculated. Washout characteristics were compared to analytic formulae to estimate any presence of partial mixing, dead volume, short-circuiting, or piston flow. Active volumes were also estimated based on tank regions that exceeded minimum velocity criteria. The mixers were ranked based on an ad hoc criteria related to the ratio of AV to unit power (UP) or AV/UP. The best plunger mixers were found to behave about the same as the conventional draft-tube mixers of similar UP.

Five-dimensional motion compensation for respiratory and cardiac motion with cone-beam CT of the thorax region

NASA Astrophysics Data System (ADS)

Sauppe, Sebastian; Hahn, Andreas; Brehm, Marcus; Paysan, Pascal; Seghers, Dieter; Kachelrieß, Marc

2016-03-01

We propose an adapted method of our previously published five-dimensional (5D) motion compensation (MoCo) algorithm1, developed for micro-CT imaging of small animals, to provide for the first time motion artifact-free 5D cone-beam CT (CBCT) images from a conventional flat detector-based CBCT scan of clinical patients. Image quality of retrospectively respiratory- and cardiac-gated volumes from flat detector CBCT scans is deteriorated by severe sparse projection artifacts. These artifacts further complicate motion estimation, as it is required for MoCo image reconstruction. For high quality 5D CBCT images at the same x-ray dose and the same number of projections as todays 3D CBCT we developed a double MoCo approach based on motion vector fields (MVFs) for respiratory and cardiac motion. In a first step our already published four-dimensional (4D) artifact-specific cyclic motion-compensation (acMoCo) approach is applied to compensate for the respiratory patient motion. With this information a cyclic phase-gated deformable heart registration algorithm is applied to the respiratory motion-compensated 4D CBCT data, thus resulting in cardiac MVFs. We apply these MVFs on double-gated images and thereby respiratory and cardiac motion-compensated 5D CBCT images are obtained. Our 5D MoCo approach processing patient data acquired with the TrueBeam 4D CBCT system (Varian Medical Systems). Our double MoCo approach turned out to be very efficient and removed nearly all streak artifacts due to making use of 100% of the projection data for each reconstructed frame. The 5D MoCo patient data show fine details and no motion blurring, even in regions close to the heart where motion is fastest.

Optical Flow Applied to Time-Lapse Image Series to Estimate Glacier Motion in the Southern Patagonia Ice Field

NASA Astrophysics Data System (ADS)

Lannutti, E.; Lenzano, M. G.; Toth, C.; Lenzano, L.; Rivera, A.

2016-06-01

In this work, we assessed the feasibility of using optical flow to obtain the motion estimation of a glacier. In general, former investigations used to detect glacier changes involve solutions that require repeated observations which are many times based on extensive field work. Taking into account glaciers are usually located in geographically complex and hard to access areas, deploying time-lapse imaging sensors, optical flow may provide an efficient solution at good spatial and temporal resolution to describe mass motion. Several studies in computer vision and image processing community have used this method to detect large displacements. Therefore, we carried out a test of the proposed Large Displacement Optical Flow method at the Viedma Glacier, located at South Patagonia Icefield, Argentina. We collected monoscopic terrestrial time-lapse imagery, acquired by a calibrated camera at every 24 hour from April 2014 until April 2015. A filter based on temporal correlation and RGB color discretization between the images was applied to minimize errors related to changes in lighting, shadows, clouds and snow. This selection allowed discarding images that do not follow a sequence of similarity. Our results show a flow field in the direction of the glacier movement with acceleration in the terminus. We analyzed the errors between image pairs, and the matching generally appears to be adequate, although some areas show random gross errors related to the presence of changes in lighting. The proposed technique allowed the determination of glacier motion during one year, providing accurate and reliable motion data for subsequent analysis.

GPS Imaging of Global Vertical Land Motion for Sea Level Studies

NASA Astrophysics Data System (ADS)

Hammond, W. C.; Blewitt, G.; Hamlington, B. D.

2015-12-01

Coastal vertical land motion contributes to the signal of local relative sea level change. Moreover, understanding global sea level change requires understanding local sea level rise at many locations around Earth. It is therefore essential to understand the regional secular vertical land motion attributable to mantle flow, tectonic deformation, glacial isostatic adjustment, postseismic viscoelastic relaxation, groundwater basin subsidence, elastic rebound from groundwater unloading or other processes that can change the geocentric height of tide gauges anchored to the land. These changes can affect inferences of global sea level rise and should be taken into account for global projections. We present new results of GPS imaging of vertical land motion across most of Earth's continents including its ice-free coastlines around North and South America, Europe, Australia, Japan, parts of Africa and Indonesia. These images are based on data from many independent open access globally distributed continuously recording GPS networks including over 13,500 stations. The data are processed in our system to obtain solutions aligned to the International Terrestrial Reference Frame (ITRF08). To generate images of vertical rate we apply the Median Interannual Difference Adjusted for Skewness (MIDAS) algorithm to the vertical times series to obtain robust non-parametric estimates with realistic uncertainties. We estimate the vertical land motion at the location of 1420 tide gauges locations using Delaunay-based geographic interpolation with an empirically derived distance weighting function and median spatial filtering. The resulting image is insensitive to outliers and steps in the GPS time series, omits short wavelength features attributable to unstable stations or unrepresentative rates, and emphasizes long-wavelength mantle-driven vertical rates.

Dynamic estimation of three-dimensional cerebrovascular deformation from rotational angiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Chong; Villa-Uriol, Maria-Cruz; De Craene, Mathieu

2011-03-15

Purpose: The objective of this study is to investigate the feasibility of detecting and quantifying 3D cerebrovascular wall motion from a single 3D rotational x-ray angiography (3DRA) acquisition within a clinically acceptable time and computing from the estimated motion field for the further biomechanical modeling of the cerebrovascular wall. Methods: The whole motion cycle of the cerebral vasculature is modeled using a 4D B-spline transformation, which is estimated from a 4D to 2D+t image registration framework. The registration is performed by optimizing a single similarity metric between the entire 2D+t measured projection sequence and the corresponding forward projections of themore » deformed volume at their exact time instants. The joint use of two acceleration strategies, together with their implementation on graphics processing units, is also proposed so as to reach computation times close to clinical requirements. For further characterizing vessel wall properties, an approximation of the wall thickness changes is obtained through a strain calculation. Results: Evaluation on in silico and in vitro pulsating phantom aneurysms demonstrated an accurate estimation of wall motion curves. In general, the error was below 10% of the maximum pulsation, even in the situation when substantial inhomogeneous intensity pattern was present. Experiments on in vivo data provided realistic aneurysm and vessel wall motion estimates, whereas in regions where motion was neither visible nor anatomically possible, no motion was detected. The use of the acceleration strategies enabled completing the estimation process for one entire cycle in 5-10 min without degrading the overall performance. The strain map extracted from our motion estimation provided a realistic deformation measure of the vessel wall. Conclusions: The authors' technique has demonstrated that it can provide accurate and robust 4D estimates of cerebrovascular wall motion within a clinically acceptable time, although it has to be applied to a larger patient population prior to possible wide application to routine endovascular procedures. In particular, for the first time, this feasibility study has shown that in vivo cerebrovascular motion can be obtained intraprocedurally from a 3DRA acquisition. Results have also shown the potential of performing strain analysis using this imaging modality, thus making possible for the future modeling of biomechanical properties of the vascular wall.« less

Highly-Damped Spectral Acceleration as a Ground Motion Intensity Measure for Estimating Collapse Vulnerability of Buildings

NASA Astrophysics Data System (ADS)

Buyco, K.; Heaton, T. H.

2016-12-01

Current U.S. seismic code and performance-based design recommendations quantify ground motion intensity using 5%-damped spectral acceleration when estimating the collapse vulnerability of buildings. This intensity measure works well for predicting inter-story drift due to moderate shaking, but other measures have been shown to be better for estimating collapse risk.We propose using highly-damped (>10%) spectral acceleration to assess collapse vulnerability. As damping is increased, the spectral acceleration at a given period T begins to behave like a weighted average of the corresponding lowly-damped (i.e. 5%) spectrum at a range of periods. Weights for periods longer than T increase as damping increases. Using high damping is physically intuitive for two reasons. Firstly, ductile buildings dissipate a large amount of hysteretic energy before collapse and thus behave more like highly-damped systems. Secondly, heavily damaged buildings experience period-lengthening, giving further credence to the weighted-averaging property of highly-damped spectral acceleration.To determine the optimal damping value(s) for this ground motion intensity measure, we conduct incremental dynamic analysis for a suite of ground motions on several different mid-rise steel buildings and select the damping value yielding the lowest dispersion of intensity at the collapse threshold. Spectral acceleration calculated with damping as high as 70% has been shown to be a better indicator of collapse than that with 5% damping.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zawisza, I; Yan, H; Yin, F

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogatemore » signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.« less

A novel control architecture for physiological tremor compensation in teleoperated systems.

PubMed

Ghorbanian, A; Zareinejad, M; Rezaei, S M; Sheikhzadeh, H; Baghestan, K

2013-09-01

Telesurgery delivers surgical care to a 'remote' patient by means of robotic manipulators. When accurate positioning of the surgeon's tool is required, as in microsurgery, physiological tremor causes unwanted imprecision during a surgical operation. Accurate estimation/compensation of physiological tremor in teleoperation systems has been shown to improve performance during telesurgery. A new control architecture is proposed for estimation and compensation of physiological tremor in the presence of communication time delays. This control architecture guarantees stability with satisfactory transparency. In addition, the proposed method can be used for applications that require modifications in transmitted signals through communication channels. Stability of the bilateral tremor-compensated teleoperation is preserved by extending the bilateral teleoperation to the equivalent trilateral Dual-master/Single-slave teleoperation. The bandlimited multiple Fourier linear combiner (BMFLC) algorithm is employed for real-time estimation of the operator's physiological tremor. Two kinds of stability analysis are employed. In the model-base controller, Llewellyn's Criterion is used to analyze the teleoperation absolute stability. In the second method, a nonmodel-based controller is proposed and the stability of the time-delayed teleoperated system is proved by employing a Lyapunov function. Experimental results are presented to validate the effectiveness of the new control architecture. The tremorous motion is measured by accelerometer to be compensated in real time. In addition, a Needle-Insertion setup is proposed as a slave robot for the application of brachytherapy, in which the needle penetrates in the desired position. The slave performs the desired task in two classes of environments (free motion of the slave and in the soft tissue). Experiments show that the proposed control architecture effectively compensates the user's tremorous motion and the slave follows only the master's voluntary motion in a stable manner. Copyright © 2012 John Wiley & Sons, Ltd.

Needle detection in ultrasound using the spectral properties of the displacement field: a feasibility study

NASA Astrophysics Data System (ADS)

Beigi, Parmida; Salcudean, Tim; Rohling, Robert; Lessoway, Victoria A.; Ng, Gary C.

2015-03-01

This paper presents a new needle detection technique for ultrasound guided interventions based on the spectral properties of small displacements arising from hand tremour or intentional motion. In a block-based approach, the displacement map is computed for each block of interest versus a reference frame, using an optical flow technique. To compute the flow parameters, the Lucas-Kanade approach is used in a multiresolution and regularized form. A least-squares fit is used to estimate the flow parameters from the overdetermined system of spatial and temporal gradients. Lateral and axial components of the displacement are obtained for each block of interest at consecutive frames. Magnitude-squared spectral coherency is derived between the median displacements of the reference block and each block of interest, to determine the spectral correlation. In vivo images were obtained from the tissue near the abdominal aorta to capture the extreme intrinsic body motion and insertion images were captured from a tissue-mimicking agar phantom. According to the analysis, both the involuntary and intentional movement of the needle produces coherent displacement with respect to a reference window near the insertion site. Intrinsic body motion also produces coherent displacement with respect to a reference window in the tissue; however, the coherency spectra of intrinsic and needle motion are distinguishable spectrally. Blocks with high spectral coherency at high frequencies are selected, estimating a channel for needle trajectory. The needle trajectory is detected from locally thresholded absolute displacement map within the initial estimate. Experimental results show the RMS localization accuracy of 1:0 mm, 0:7 mm, and 0:5 mm for hand tremour, vibrational and rotational needle movements, respectively.

Uncertainties in Earthquake Loss Analysis: A Case Study From Southern California

NASA Astrophysics Data System (ADS)

Mahdyiar, M.; Guin, J.

2005-12-01

Probabilistic earthquake hazard and loss analyses play important roles in many areas of risk management, including earthquake related public policy and insurance ratemaking. Rigorous loss estimation for portfolios of properties is difficult since there are various types of uncertainties in all aspects of modeling and analysis. It is the objective of this study to investigate the sensitivity of earthquake loss estimation to uncertainties in regional seismicity, earthquake source parameters, ground motions, and sites' spatial correlation on typical property portfolios in Southern California. Southern California is an attractive region for such a study because it has a large population concentration exposed to significant levels of seismic hazard. During the last decade, there have been several comprehensive studies of most regional faults and seismogenic sources. There have also been detailed studies on regional ground motion attenuations and regional and local site responses to ground motions. This information has been used by engineering seismologists to conduct regional seismic hazard and risk analysis on a routine basis. However, one of the more difficult tasks in such studies is the proper incorporation of uncertainties in the analysis. From the hazard side, there are uncertainties in the magnitudes, rates and mechanisms of the seismic sources and local site conditions and ground motion site amplifications. From the vulnerability side, there are considerable uncertainties in estimating the state of damage of buildings under different earthquake ground motions. From an analytical side, there are challenges in capturing the spatial correlation of ground motions and building damage, and integrating thousands of loss distribution curves with different degrees of correlation. In this paper we propose to address some of these issues by conducting loss analyses of a typical small portfolio in southern California, taking into consideration various source and ground motion uncertainties. The approach is designed to integrate loss distribution functions with different degrees of correlation for portfolio analysis. The analysis is based on USGS 2002 regional seismicity model.

Image-derived input function in PET brain studies: blood-based methods are resistant to motion artifacts.

PubMed

Zanotti-Fregonara, Paolo; Liow, Jeih-San; Comtat, Claude; Zoghbi, Sami S; Zhang, Yi; Pike, Victor W; Fujita, Masahiro; Innis, Robert B

2012-09-01

Image-derived input function (IDIF) from carotid arteries is an elegant alternative to full arterial blood sampling for brain PET studies. However, a recent study using blood-free IDIFs found that this method is particularly vulnerable to patient motion. The present study used both simulated and clinical [11C](R)-rolipram data to assess the robustness of a blood-based IDIF method (a method that is ultimately normalized with blood samples) with regard to motion artifacts. The impact of motion on the accuracy of IDIF was first assessed with an analytical simulation of a high-resolution research tomograph using a numerical phantom of the human brain, equipped with internal carotids. Different degrees of translational (from 1 to 20 mm) and rotational (from 1 to 15°) motions were tested. The impact of motion was then tested on the high-resolution research tomograph dynamic scans of three healthy volunteers, reconstructed with and without an online motion correction system. IDIFs and Logan-distribution volume (VT) values derived from simulated and clinical scans with motion were compared with those obtained from the scans with motion correction. In the phantom scans, the difference in the area under the curve (AUC) for the carotid time-activity curves was up to 19% for rotations and up to 66% for translations compared with the motionless simulation. However, for the final IDIFs, which were fitted to blood samples, the AUC difference was 11% for rotations and 8% for translations. Logan-VT errors were always less than 10%, except for the maximum translation of 20 mm, in which the error was 18%. Errors in the clinical scans without motion correction appeared to be minor, with differences in AUC and Logan-VT always less than 10% compared with scans with motion correction. When a blood-based IDIF method is used for neurological PET studies, the motion of the patient affects IDIF estimation and kinetic modeling only minimally.

A Method of Time-Intensity Curve Calculation for Vascular Perfusion of Uterine Fibroids Based on Subtraction Imaging with Motion Correction

NASA Astrophysics Data System (ADS)

Zhu, Xinjian; Wu, Ruoyu; Li, Tao; Zhao, Dawei; Shan, Xin; Wang, Puling; Peng, Song; Li, Faqi; Wu, Baoming

2016-12-01

The time-intensity curve (TIC) from contrast-enhanced ultrasound (CEUS) image sequence of uterine fibroids provides important parameter information for qualitative and quantitative evaluation of efficacy of treatment such as high-intensity focused ultrasound surgery. However, respiration and other physiological movements inevitably affect the process of CEUS imaging, and this reduces the accuracy of TIC calculation. In this study, a method of TIC calculation for vascular perfusion of uterine fibroids based on subtraction imaging with motion correction is proposed. First, the fibroid CEUS recording video was decoded into frame images based on the record frame rate. Next, the Brox optical flow algorithm was used to estimate the displacement field and correct the motion between two frames based on warp technique. Then, subtraction imaging was performed to extract the positional distribution of vascular perfusion (PDOVP). Finally, the average gray of all pixels in the PDOVP from each image was determined, and this was considered the TIC of CEUS image sequence. Both the correlation coefficient and mutual information of the results with proposed method were larger than those determined using the original method. PDOVP extraction results have been improved significantly after motion correction. The variance reduction rates were all positive, indicating that the fluctuations of TIC had become less pronounced, and the calculation accuracy has been improved after motion correction. This proposed method can effectively overcome the influence of motion mainly caused by respiration and allows precise calculation of TIC.

Study of the Navigation Method for a Snake Robot Based on the Kinematics Model with MEMS IMU

PubMed Central

Dou, Lihua; Su, Zhong; Liu, Ning

2018-01-01

A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot’s motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot’s motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot’s navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots. PMID:29547515