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.
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.
NASA Astrophysics Data System (ADS)
Wu, Shunguang; Hong, Lang
2008-04-01
A framework of simultaneously estimating the motion and structure parameters of a 3D object by using high range resolution (HRR) and ground moving target indicator (GMTI) measurements with template information is given. By decoupling the motion and structure information and employing rigid-body constraints, we have developed the kinematic and measurement equations of the problem. Since the kinematic system is unobservable by using only one scan HRR and GMTI measurements, we designed an architecture to run the motion and structure filters in parallel by using multi-scan measurements. Moreover, to improve the estimation accuracy in large noise and/or false alarm environments, an interacting multi-template joint tracking (IMTJT) algorithm is proposed. Simulation results have shown that the averaged root mean square errors for both motion and structure state vectors have been significantly reduced by using the template information.
NASA Astrophysics Data System (ADS)
Cofaru, Corneliu; Philips, Wilfried; Van Paepegem, Wim
2011-09-01
Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman- McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques.
Adaptive vehicle motion estimation and prediction
NASA Astrophysics Data System (ADS)
Zhao, Liang; Thorpe, Chuck E.
1999-01-01
Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.
Bayesian estimation of turbulent motion.
Héas, Patrick; Herzet, Cédric; Mémin, Etienne; Heitz, Dominique; Mininni, Pablo D
2013-06-01
Based on physical laws describing the multiscale structure of turbulent flows, this paper proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyperparameters, and to select the most likely physical prior among a set of models. Hyperparameter and model inference are conducted by posterior maximization, obtained by marginalizing out non--Gaussian motion variables. The Bayesian estimator is assessed on several image sequences depicting synthetic and real turbulent fluid flows. Results obtained with the proposed approach exceed the state-of-the-art results in fluid flow estimation. PMID:23599051
Leveraging Two Kinect Sensors for Accurate Full-Body Motion Capture
Gao, Zhiquan; Yu, Yao; Zhou, Yu; Du, Sidan
2015-01-01
Accurate motion capture plays an important role in sports analysis, the medical field and virtual reality. Current methods for motion capture often suffer from occlusions, which limits the accuracy of their pose estimation. In this paper, we propose a complete system to measure the pose parameters of the human body accurately. Different from previous monocular depth camera systems, we leverage two Kinect sensors to acquire more information about human movements, which ensures that we can still get an accurate estimation even when significant occlusion occurs. Because human motion is temporally constant, we adopt a learning analysis to mine the temporal information across the posture variations. Using this information, we estimate human pose parameters accurately, regardless of rapid movement. Our experimental results show that our system can perform an accurate pose estimation of the human body with the constraint of information from the temporal domain. PMID:26402681
Leveraging Two Kinect Sensors for Accurate Full-Body Motion Capture.
Gao, Zhiquan; Yu, Yao; Zhou, Yu; Du, Sidan
2015-01-01
Accurate motion capture plays an important role in sports analysis, the medical field and virtual reality. Current methods for motion capture often suffer from occlusions, which limits the accuracy of their pose estimation. In this paper, we propose a complete system to measure the pose parameters of the human body accurately. Different from previous monocular depth camera systems, we leverage two Kinect sensors to acquire more information about human movements, which ensures that we can still get an accurate estimation even when significant occlusion occurs. Because human motion is temporally constant, we adopt a learning analysis to mine the temporal information across the posture variations. Using this information, we estimate human pose parameters accurately, regardless of rapid movement. Our experimental results show that our system can perform an accurate pose estimation of the human body with the constraint of information from the temporal domain. PMID:26402681
Accurate pose estimation for forensic identification
NASA Astrophysics Data System (ADS)
Merckx, Gert; Hermans, Jeroen; Vandermeulen, Dirk
2010-04-01
In forensic authentication, one aims to identify the perpetrator among a series of suspects or distractors. A fundamental problem in any recognition system that aims for identification of subjects in a natural scene is the lack of constrains on viewing and imaging conditions. In forensic applications, identification proves even more challenging, since most surveillance footage is of abysmal quality. In this context, robust methods for pose estimation are paramount. In this paper we will therefore present a new pose estimation strategy for very low quality footage. Our approach uses 3D-2D registration of a textured 3D face model with the surveillance image to obtain accurate far field pose alignment. Starting from an inaccurate initial estimate, the technique uses novel similarity measures based on the monogenic signal to guide a pose optimization process. We will illustrate the descriptive strength of the introduced similarity measures by using them directly as a recognition metric. Through validation, using both real and synthetic surveillance footage, our pose estimation method is shown to be accurate, and robust to lighting changes and image degradation.
Frame rate up conversion via Bayesian motion estimation
NASA Astrophysics Data System (ADS)
Wang, Yue; Ma, Siwei; Gao, Wen
2010-07-01
In this paper, a novel block-based motion compensated frame interpolation (MCI) algorithm is proposed to enhance the temporal resolution of video sequences. We formulated motion estimation into MAP framework, and solved it via Bayesian belief propagation. By effectively incorporating a priori knowledge of the motion field and optimizing the whole motion field synchronously, it could derive more accurate motion vectors than traditional methods. Finally, adaptive overlapped block motion compensation (OBMC) is used to reduce blocking artifacts. Experimental results show that the proposed method outperforms other methods in both objective and subjective quality.
Estimation of ground motion parameters
Boore, David M.; Oliver, Adolph A., III; Page, Robert A.; Joyner, William B.
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. Data from the San Fernando earthquake are examined to assess the effects of associated structures and of geologic site conditions on peak recorded motions. 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. 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. Three recently published relationships for predicting peak horizontal acceleration are compared and discussed. Considerations are reviewed relevant to ground motion predictions at close distances where there are insufficient recorded data points.
Estimation of ground motion parameters
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
Accurate estimation of sigma(exp 0) using AIRSAR data
NASA Technical Reports Server (NTRS)
Holecz, Francesco; Rignot, Eric
1995-01-01
During recent years signature analysis, classification, and modeling of Synthetic Aperture Radar (SAR) data as well as estimation of geophysical parameters from SAR data have received a great deal of interest. An important requirement for the quantitative use of SAR data is the accurate estimation of the backscattering coefficient sigma(exp 0). In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived from sensor position and Digital Elevation Model (DEM) data must always be considered. Especially in the airborne case, the antenna gain pattern can be an additional source of radiometric error, because the radar look angle is not known precisely as a result of the the aircraft motions and the local surface topography. Consequently, radiometric distortions due to the antenna gain pattern must also be corrected for each resolution cell, by taking into account aircraft displacements (position and attitude) and position of the backscatter element, defined by the DEM data. In this paper, a method to derive an accurate estimation of the backscattering coefficient using NASA/JPL AIRSAR data is presented. The results are evaluated in terms of geometric accuracy, radiometric variations of sigma(exp 0), and precision of the estimated forest biomass.
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.
Measuring accurate body parameters of dressed humans with large-scale motion using a Kinect sensor.
Xu, Huanghao; Yu, Yao; Zhou, Yu; Li, Yang; Du, Sidan
2013-01-01
Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Current methods for measuring the human body without physical contact usually cannot handle humans wearing clothes, which limits their applicability in public environments. In this paper, we propose an effective solution that can measure accurate parameters of the human body with large-scale motion from a Kinect sensor, assuming that the people are wearing clothes. Because motion can drive clothes attached to the human body loosely or tightly, we adopt a space-time analysis to mine the information across the posture variations. Using this information, we recover the human body, regardless of the effect of clothes, and measure the human body parameters accurately. Experimental results show that our system can perform more accurate parameter estimation on the human body than state-of-the-art methods. PMID:24064597
Nonlinear circuits for naturalistic visual motion estimation
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
31 CFR 205.24 - How are accurate estimates maintained?
Code of Federal Regulations, 2010 CFR
2010-07-01
... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false How are accurate estimates maintained... Treasury-State Agreement § 205.24 How are accurate estimates maintained? (a) If a State has knowledge that an estimate does not reasonably correspond to the State's cash needs for a Federal assistance...
Accurate Biomass Estimation via Bayesian Adaptive Sampling
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay
2005-01-01
The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.
Micromagnetometer calibration for accurate orientation estimation.
Zhang, Zhi-Qiang; Yang, Guang-Zhong
2015-02-01
Micromagnetometers, together with inertial sensors, are widely used for attitude estimation for a wide variety of applications. However, appropriate sensor calibration, which is essential to the accuracy of attitude reconstruction, must be performed in advance. Thus far, many different magnetometer calibration methods have been proposed to compensate for errors such as scale, offset, and nonorthogonality. They have also been used for obviate magnetic errors due to soft and hard iron. However, in order to combine the magnetometer with inertial sensor for attitude reconstruction, alignment difference between the magnetometer and the axes of the inertial sensor must be determined as well. This paper proposes a practical means of sensor error correction by simultaneous consideration of sensor errors, magnetic errors, and alignment difference. We take the summation of the offset and hard iron error as the combined bias and then amalgamate the alignment difference and all the other errors as a transformation matrix. A two-step approach is presented to determine the combined bias and transformation matrix separately. In the first step, the combined bias is determined by finding an optimal ellipsoid that can best fit the sensor readings. In the second step, the intrinsic relationships of the raw sensor readings are explored to estimate the transformation matrix as a homogeneous linear least-squares problem. Singular value decomposition is then applied to estimate both the transformation matrix and magnetic vector. The proposed method is then applied to calibrate our sensor node. Although there is no ground truth for the combined bias and transformation matrix for our node, the consistency of calibration results among different trials and less than 3(°) root mean square error for orientation estimation have been achieved, which illustrates the effectiveness of the proposed sensor calibration method for practical applications. PMID:25265625
Estimating Motion From MRI Data
OZTURK, CENGIZHAN; DERBYSHIRE, J. ANDREW; MCVEIGH, ELLIOT R.
2007-01-01
Invited Paper Magnetic resonance imaging (MRI) is an ideal imaging modality to measure blood flow and tissue motion. It provides excellent contrast between soft tissues, and images can be acquired at positions and orientations freely defined by the user. From a temporal sequence of MR images, boundaries and edges of tissues can be tracked by image processing techniques. Additionally, MRI permits the source of the image signal to be manipulated. For example, temporary magnetic tags displaying a pattern of variable brightness may be placed in the object using MR saturation techniques, giving the user a known pattern to detect for motion tracking. The MRI signal is a modulated complex quantity, being derived from a rotating magnetic field in the form of an induced current. Well-defined patterns can also be introduced into the phase of the magnetization, and could be thought of as generalized tags. If the phase of each pixel is preserved during image reconstruction, relative phase shifts can be used to directly encode displacement, velocity and acceleration. New methods for modeling motion fields from MRI have now found application in cardiovascular and other soft tissue imaging. In this review, we shall describe the methods used for encoding, imaging, and modeling motion fields with MRI. PMID:18958181
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.
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.
Optimal quad-tree-based motion estimator
NASA Astrophysics Data System (ADS)
Schuster, Guido M.; Katsaggelos, Aggelos K.
1996-09-01
In this paper we propose an optimal quad-tree (QT)-based motion estimator for video compression. It is optimal in the sense that for a given bit budget for encoding the displacement vector field (DVF) and the QT segmentation, the scheme finds a DVF and a QT segmentation which minimizes the energy of the resulting displaced frame difference (DFD). We find the optimal QT decomposition and the optimal DVF jointly using the Lagrangian multiplier method and a multilevel dynamic program. The resulting DVF is spatially inhomogeneous since large blocks are used in areas with simple motion and small blocks in areas with complex motion. We present results with the proposed QT-based motion estimator which show that for the same DFD energy the proposed estimator uses about 30% fewer bits than the commonly used block matching algorithm.
Robust Sparse Matching and Motion Estimation Using Genetic Algorithms
NASA Astrophysics Data System (ADS)
Shahbazi, M.; Sohn, G.; Théau, J.; Ménard, P.
2015-03-01
In this paper, we propose a robust technique using genetic algorithm for detecting inliers and estimating accurate motion parameters from putative correspondences containing any percentage of outliers. The proposed technique aims to increase computational efficiency and modelling accuracy in comparison with the state-of-the-art via the following contributions: i) guided generation of initial populations for both avoiding degenerate solutions and increasing the rate of useful hypotheses, ii) replacing random search with evolutionary search, iii) possibility of evaluating the individuals of every population by parallel computation, iv) being performable on images with unknown internal orientation parameters, iv) estimating the motion model via detecting a minimum, however more than enough, set of inliers, v) ensuring the robustness of the motion model against outliers, degeneracy and poorperspective camera models, vi) making no assumptions about the probability distribution of inliers and/or outliers residuals from the estimated motion model, vii) detecting all the inliers by setting the threshold on their residuals adaptively with regard to the uncertainty of the estimated motion model and the position of the matches. The proposed method was evaluated both on synthetic data and real images. The results were compared with the most popular techniques from the state-of-the-art, including RANSAC, MSAC, MLESAC, Least Trimmed Squares and Least Median of Squares. Experimental results proved that the proposed approach perform better than others in terms of accuracy of motion estimation, accuracy of inlier detection and the computational efficiency.
A Fourier approach to cloud motion estimation
NASA Technical Reports Server (NTRS)
Arking, A.; Lo, R. C.; Rosenfeld, A.
1978-01-01
A Fourier phase-difference technique for cloud motion estimation from pairs of pictures is described, and results obtained using this technique are compared with the results of a Fourier-domain cross-correlation scheme. The phase-difference technique makes use of the phase of the cross-spectral density and allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. When objects being tracked do not change their shape, size, and orientation to more than a limited degree, both techniques are effective. The phase difference technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects; in these circumstances, the cross-correlation scheme is preferable. It is suggested that the Fourier transform phase difference estimation methods can be applied in problems such as landmark matching.
Human heading estimation during visually simulated curvilinear motion
NASA Technical Reports Server (NTRS)
Stone, L. S.; Perrone, J. A.
1997-01-01
Recent studies have suggested that humans cannot estimate their direction of forward translation (heading) from the resulting retinal motion (flow field) alone when rotation rates are higher than approximately 1 deg/sec. It has been argued that either oculomotor or static depth cues are necessary to disambiguate the rotational and translational components of the flow field and, thus, to support accurate heading estimation. We have re-examined this issue using visually simulated motion along a curved path towards a layout of random points as the stimulus. Our data show that, in this curvilinear motion paradigm, five of six observers could estimate their heading relatively accurately and precisely (error and uncertainty < approximately 4 deg), even for rotation rates as high as 16 deg/sec, without the benefit of either oculomotor or static depth cues signaling rotation rate. Such performance is inconsistent with models of human self-motion estimation that require rotation information from sources other than the flow field to cancel the rotational flow.
Quantifying Accurate Calorie Estimation Using the "Think Aloud" Method
ERIC Educational Resources Information Center
Holmstrup, Michael E.; Stearns-Bruening, Kay; Rozelle, Jeffrey
2013-01-01
Objective: Clients often have limited time in a nutrition education setting. An improved understanding of the strategies used to accurately estimate calories may help to identify areas of focused instruction to improve nutrition knowledge. Methods: A "Think Aloud" exercise was recorded during the estimation of calories in a standard dinner meal…
Cloud motion estimation using a sky imager
NASA Astrophysics Data System (ADS)
Chauvin, R.; Nou, J.; Thil, S.; Grieu, S.
2016-05-01
The present paper deals with an image processing methodology based on a sky-imaging system developed at the PROMES-CNRS laboratory (France). It is part of a project which aims at improving solar plant control procedures using Direct Normal Irradiance (DNI) forecasts under various sky conditions at short term horizon (5-30 minutes) and high spatial resolution (~1 km2). This work focuses on estimating cloud motion, based on a block-wise cross correlation algorithm. The choice of the algorithm is explained in the first section of this paper. The second section aims at optimizing the algorithm parameters in order to reduce as much as possible the computational time while keeping the best possible accuracy. The paper ends with the spatial and temporal filtering processes that allow estimating the mean cloud motion. The stability of the estimation over time tends to validate the proposed approach.
Ground motion estimation and nonlinear seismic analysis
McCallen, D.B.; Hutchings, L.J.
1995-08-14
Site specific predictions of the dynamic response of structures to extreme earthquake ground motions are a critical component of seismic design for important structures. With the rapid development of computationally based methodologies and powerful computers over the past few years, engineers and scientists now have the capability to perform numerical simulations of many of the physical processes associated with the generation of earthquake ground motions and dynamic structural response. This paper describes application of a physics based, deterministic, computational approach for estimation of earthquake ground motions which relies on site measurements of frequently occurring small (i.e. M < 3 ) earthquakes. Case studies are presented which illustrate application of this methodology for two different sites, and nonlinear analyses of a typical six story steel frame office building are performed to illustrate the potential sensitivity of nonlinear response to site conditions and proximity to the causative fault.
Motion field estimation for a dynamic scene using a 3D LiDAR.
Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington
2014-01-01
This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868
Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR
Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington
2014-01-01
This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868
Accurate parameter estimation for unbalanced three-phase system.
Chen, Yuan; So, Hing Cheung
2014-01-01
Smart grid is an intelligent power generation and control console in modern electricity networks, where the unbalanced three-phase power system is the commonly used model. Here, parameter estimation for this system is addressed. After converting the three-phase waveforms into a pair of orthogonal signals via the α β-transformation, the nonlinear least squares (NLS) estimator is developed for accurately finding the frequency, phase, and voltage parameters. The estimator is realized by the Newton-Raphson scheme, whose global convergence is studied in this paper. Computer simulations show that the mean square error performance of NLS method can attain the Cramér-Rao lower bound. Moreover, our proposal provides more accurate frequency estimation when compared with the complex least mean square (CLMS) and augmented CLMS. PMID:25162056
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.
Accurate pose estimation using single marker single camera calibration system
NASA Astrophysics Data System (ADS)
Pati, Sarthak; Erat, Okan; Wang, Lejing; Weidert, Simon; Euler, Ekkehard; Navab, Nassir; Fallavollita, Pascal
2013-03-01
Visual marker based tracking is one of the most widely used tracking techniques in Augmented Reality (AR) applications. Generally, multiple square markers are needed to perform robust and accurate tracking. Various marker based methods for calibrating relative marker poses have already been proposed. However, the calibration accuracy of these methods relies on the order of the image sequence and pre-evaluation of pose-estimation errors, making the method offline. Several studies have shown that the accuracy of pose estimation for an individual square marker depends on camera distance and viewing angle. We propose a method to accurately model the error in the estimated pose and translation of a camera using a single marker via an online method based on the Scaled Unscented Transform (SUT). Thus, the pose estimation for each marker can be estimated with highly accurate calibration results independent of the order of image sequences compared to cases when this knowledge is not used. This removes the need for having multiple markers and an offline estimation system to calculate camera pose in an AR application.
Complex Principal Components for Robust Motion Estimation
Mauldin, F. William; Viola, Francesco; Walker, William F.
2010-01-01
Bias and variance errors in motion estimation result from electronic noise, decorrelation, aliasing, and inherent algorithm limitations. Unlike most error sources, decorrelation is coherent over time and has the same power spectrum as the signal. Thus, reducing decorrelation is impossible through frequency domain filtering or simple averaging and must be achieved through other methods. In this paper, we present a novel motion estimator, termed the principal component displacement estimator (PCDE), which takes advantage of the signal separation capabilities of principal component analysis (PCA) to reject decorrelation and noise. Furthermore, PCDE only requires the computation of a single principal component, enabling computational speed that is on the same order of magnitude or faster than the commonly used Loupas algorithm. Unlike prior PCA strategies, PCDE uses complex data to generate motion estimates using only a single principal component. The use of complex echo data is critical because it allows for separation of signal components based on motion, which is revealed through phase changes of the complex principal components. PCDE operates on the assumption that the signal component of interest is also the most energetic component in an ensemble of echo data. This assumption holds in most clinical ultrasound environments. However, in environments where electronic noise SNR is less than 0 dB or in blood flow data for which the wall signal dominates the signal from blood flow, the calculation of more than one PC is required to obtain the signal of interest. We simulated synthetic ultrasound data to assess the performance of PCDE over a wide range of imaging conditions and in the presence of decorrelation and additive noise. Under typical ultrasonic elasticity imaging conditions (0.98 signal correlation, 25 dB SNR, 1 sample shift), PCDE decreased estimation bias by more than 10% and standard deviation by more than 30% compared with the Loupas method and normalized
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.
An Accurate Link Correlation Estimator for Improving Wireless Protocol Performance
Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun
2015-01-01
Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation. PMID:25686314
An accurate link correlation estimator for improving wireless protocol performance.
Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun
2015-01-01
Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation. PMID:25686314
Fast and accurate estimation for astrophysical problems in large databases
NASA Astrophysics Data System (ADS)
Richards, Joseph W.
2010-10-01
A recent flood of astronomical data has created much demand for sophisticated statistical and machine learning tools that can rapidly draw accurate inferences from large databases of high-dimensional data. In this Ph.D. thesis, methods for statistical inference in such databases will be proposed, studied, and applied to real data. I use methods for low-dimensional parametrization of complex, high-dimensional data that are based on the notion of preserving the connectivity of data points in the context of a Markov random walk over the data set. I show how this simple parameterization of data can be exploited to: define appropriate prototypes for use in complex mixture models, determine data-driven eigenfunctions for accurate nonparametric regression, and find a set of suitable features to use in a statistical classifier. In this thesis, methods for each of these tasks are built up from simple principles, compared to existing methods in the literature, and applied to data from astronomical all-sky surveys. I examine several important problems in astrophysics, such as estimation of star formation history parameters for galaxies, prediction of redshifts of galaxies using photometric data, and classification of different types of supernovae based on their photometric light curves. Fast methods for high-dimensional data analysis are crucial in each of these problems because they all involve the analysis of complicated high-dimensional data in large, all-sky surveys. Specifically, I estimate the star formation history parameters for the nearly 800,000 galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7 spectroscopic catalog, determine redshifts for over 300,000 galaxies in the SDSS photometric catalog, and estimate the types of 20,000 supernovae as part of the Supernova Photometric Classification Challenge. Accurate predictions and classifications are imperative in each of these examples because these estimates are utilized in broader inference problems
Accurate and robust estimation of camera parameters using RANSAC
NASA Astrophysics Data System (ADS)
Zhou, Fuqiang; Cui, Yi; Wang, Yexin; Liu, Liu; Gao, He
2013-03-01
Camera calibration plays an important role in the field of machine vision applications. The popularly used calibration approach based on 2D planar target sometimes fails to give reliable and accurate results due to the inaccurate or incorrect localization of feature points. To solve this problem, an accurate and robust estimation method for camera parameters based on RANSAC algorithm is proposed to detect the unreliability and provide the corresponding solutions. Through this method, most of the outliers are removed and the calibration errors that are the main factors influencing measurement accuracy are reduced. Both simulative and real experiments have been carried out to evaluate the performance of the proposed method and the results show that the proposed method is robust under large noise condition and quite efficient to improve the calibration accuracy compared with the original state.
Accurate Satellite-Derived Estimates of Tropospheric Ozone Radiative Forcing
NASA Technical Reports Server (NTRS)
Joiner, Joanna; Schoeberl, Mark R.; Vasilkov, Alexander P.; Oreopoulos, Lazaros; Platnick, Steven; Livesey, Nathaniel J.; Levelt, Pieternel F.
2008-01-01
Estimates of the radiative forcing due to anthropogenically-produced tropospheric O3 are derived primarily from models. Here, we use tropospheric ozone and cloud data from several instruments in the A-train constellation of satellites as well as information from the GEOS-5 Data Assimilation System to accurately estimate the instantaneous radiative forcing from tropospheric O3 for January and July 2005. We improve upon previous estimates of tropospheric ozone mixing ratios from a residual approach using the NASA Earth Observing System (EOS) Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) by incorporating cloud pressure information from OMI. Since we cannot distinguish between natural and anthropogenic sources with the satellite data, our estimates reflect the total forcing due to tropospheric O3. We focus specifically on the magnitude and spatial structure of the cloud effect on both the shortand long-wave radiative forcing. The estimates presented here can be used to validate present day O3 radiative forcing produced by models.
Robust ODF smoothing for accurate estimation of fiber orientation.
Beladi, Somaieh; Pathirana, Pubudu N; Brotchie, Peter
2010-01-01
Q-ball imaging was presented as a model free, linear and multimodal diffusion sensitive approach to reconstruct diffusion orientation distribution function (ODF) using diffusion weighted MRI data. The ODFs are widely used to estimate the fiber orientations. However, the smoothness constraint was proposed to achieve a balance between the angular resolution and noise stability for ODF constructs. Different regularization methods were proposed for this purpose. However, these methods are not robust and quite sensitive to the global regularization parameter. Although, numerical methods such as L-curve test are used to define a globally appropriate regularization parameter, it cannot serve as a universal value suitable for all regions of interest. This may result in over smoothing and potentially end up in neglecting an existing fiber population. In this paper, we propose to include an interpolation step prior to the spherical harmonic decomposition. This interpolation based approach is based on Delaunay triangulation provides a reliable, robust and accurate smoothing approach. This method is easy to implement and does not require other numerical methods to define the required parameters. Also, the fiber orientations estimated using this approach are more accurate compared to other common approaches. PMID:21096202
Accurate estimators of correlation functions in Fourier space
NASA Astrophysics Data System (ADS)
Sefusatti, E.; Crocce, M.; Scoccimarro, R.; Couchman, H. M. P.
2016-08-01
Efficient estimators of Fourier-space statistics for large number of objects rely on fast Fourier transforms (FFTs), which are affected by aliasing from unresolved small-scale modes due to the finite FFT grid. Aliasing takes the form of a sum over images, each of them corresponding to the Fourier content displaced by increasing multiples of the sampling frequency of the grid. These spurious contributions limit the accuracy in the estimation of Fourier-space statistics, and are typically ameliorated by simultaneously increasing grid size and discarding high-frequency modes. This results in inefficient estimates for e.g. the power spectrum when desired systematic biases are well under per cent level. We show that using interlaced grids removes odd images, which include the dominant contribution to aliasing. In addition, we discuss the choice of interpolation kernel used to define density perturbations on the FFT grid and demonstrate that using higher order interpolation kernels than the standard Cloud-In-Cell algorithm results in significant reduction of the remaining images. We show that combining fourth-order interpolation with interlacing gives very accurate Fourier amplitudes and phases of density perturbations. This results in power spectrum and bispectrum estimates that have systematic biases below 0.01 per cent all the way to the Nyquist frequency of the grid, thus maximizing the use of unbiased Fourier coefficients for a given grid size and greatly reducing systematics for applications to large cosmological data sets.
Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology
NASA Astrophysics Data System (ADS)
Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan
2016-05-01
This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.
Accurate estimation of human body orientation from RGB-D sensors.
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. PMID:23893759
Accurate Orientation Estimation Using AHRS under Conditions of Magnetic Distortion
Yadav, Nagesh; Bleakley, Chris
2014-01-01
Low cost, compact attitude heading reference systems (AHRS) are now being used to track human body movements in indoor environments by estimation of the 3D orientation of body segments. In many of these systems, heading estimation is achieved by monitoring the strength of the Earth's magnetic field. However, the Earth's magnetic field can be locally distorted due to the proximity of ferrous and/or magnetic objects. Herein, we propose a novel method for accurate 3D orientation estimation using an AHRS, comprised of an accelerometer, gyroscope and magnetometer, under conditions of magnetic field distortion. The system performs online detection and compensation for magnetic disturbances, due to, for example, the presence of ferrous objects. The magnetic distortions are detected by exploiting variations in magnetic dip angle, relative to the gravity vector, and in magnetic strength. We investigate and show the advantages of using both magnetic strength and magnetic dip angle for detecting the presence of magnetic distortions. The correction method is based on a particle filter, which performs the correction using an adaptive cost function and by adapting the variance during particle resampling, so as to place more emphasis on the results of dead reckoning of the gyroscope measurements and less on the magnetometer readings. The proposed method was tested in an indoor environment in the presence of various magnetic distortions and under various accelerations (up to 3 g). In the experiments, the proposed algorithm achieves <2° static peak-to-peak error and <5° dynamic peak-to-peak error, significantly outperforming previous methods. PMID:25347584
Accurate estimation of object location in an image sequence using helicopter flight data
NASA Technical Reports Server (NTRS)
Tang, Yuan-Liang; Kasturi, Rangachar
1994-01-01
In autonomous navigation, it is essential to obtain a three-dimensional (3D) description of the static environment in which the vehicle is traveling. For a rotorcraft conducting low-latitude flight, this description is particularly useful for obstacle detection and avoidance. In this paper, we address the problem of 3D position estimation for static objects from a monocular sequence of images captured from a low-latitude flying helicopter. Since the environment is static, it is well known that the optical flow in the image will produce a radiating pattern from the focus of expansion. We propose a motion analysis system which utilizes the epipolar constraint to accurately estimate 3D positions of scene objects in a real world image sequence taken from a low-altitude flying helicopter. Results show that this approach gives good estimates of object positions near the rotorcraft's intended flight-path.
Effective Echo Detection and Accurate Orbit Estimation Algorithms for Space Debris Radar
NASA Astrophysics Data System (ADS)
Isoda, Kentaro; Sakamoto, Takuya; Sato, Toru
Orbit estimation of space debris, objects of no inherent value orbiting the earth, is a task that is important for avoiding collisions with spacecraft. The Kamisaibara Spaceguard Center radar system was built in 2004 as the first radar facility in Japan devoted to the observation of space debris. In order to detect the smaller debris, coherent integration is effective in improving SNR (Signal-to-Noise Ratio). However, it is difficult to apply coherent integration to real data because the motions of the targets are unknown. An effective algorithm is proposed for echo detection and orbit estimation of the faint echoes from space debris. The characteristics of the evaluation function are utilized by the algorithm. Experiments show the proposed algorithm improves SNR by 8.32dB and enables estimation of orbital parameters accurately to allow for re-tracking with a single radar.
Flow in left atrium using MR fluid motion estimation
NASA Astrophysics Data System (ADS)
Wong, Kelvin K. L.; Kelso, Richard M.; Worthley, Steve M.; Sanders, Prash; Mazumdar, Jagannath; Abbott, Derek
2007-12-01
A recent development based on optical flow applied onto Fast Imaging in Steady State Free Precession (TrueFISP) magnetic resonance imaging is able to deliver good estimation of the flow profile in the human heart chamber. The examination of cardiac flow based on tracking of MR signals emitted by moving blood is able to give medical doctors insight into the flow patterns within the human heart using standard MRI procedure without specifically subjecting the patient to longer scan times using more dedicated scan protocols such as phase contrast MRI. Although MR fluid motion estimation has its limitations in terms of accurate flow mapping, the use of a comparatively quick scan procedure and computational post-processing gives satisfactory flow quantification and can assist in management of cardiac patients. In this study, we present flow in the left atria of five human subjects using MR fluid motion tracking. The measured flow shows that vortices exist within the atrium of heart. Although the scan is two-dimensional, we have produced multiple slices of flow maps in a spatial direction to show that the vortex exist in a three-dimensional space.
Hwang, Beomsoo; Jeon, Doyoung
2015-01-01
In exoskeletal robots, the quantification of the user's muscular effort is important to recognize the user's motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users' muscular efforts accurately using joint torque sensor which contains the measurements of dynamic effect of human body such as the inertial, Coriolis, and gravitational torques as well as torque by active muscular effort. It is important to extract the dynamic effects of the user's limb accurately from the measured torque. The user's limb dynamics are formulated and a convenient method of identifying user-specific parameters is suggested for estimating the user's muscular torque in robotic exoskeletons. Experiments were carried out on a wheelchair-integrated lower limb exoskeleton, EXOwheel, which was equipped with torque sensors in the hip and knee joints. The proposed methods were evaluated by 10 healthy participants during body weight-supported gait training. The experimental results show that the torque sensors are to estimate the muscular torque accurately in cases of relaxed and activated muscle conditions. PMID:25860074
Estimating Myocardial Motion by 4D Image Warping
Sundar, Hari; Litt, Harold; Shen, Dinggang
2009-01-01
A method for spatio-temporally smooth and consistent estimation of cardiac motion from MR cine sequences is proposed. Myocardial motion is estimated within a 4-dimensional (4D) registration framework, in which all 3D images obtained at different cardiac phases are simultaneously registered. This facilitates spatio-temporally consistent estimation of motion as opposed to other registration-based algorithms which estimate the motion by sequentially registering one frame to another. To facilitate image matching, an attribute vector (AV) is constructed for each point in the image, and is intended to serve as a “morphological signature” of that point. The AV includes intensity, boundary, and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points to refine the registration. Experimental results on real data demonstrate good performance of the proposed method for cardiac image registration and motion estimation. The motion estimation is validated via comparisons with motion estimates obtained from MR images with myocardial tagging. PMID:20379351
An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging
NASA Astrophysics Data System (ADS)
Abd. Rahni, Ashrani Aizzuddin; Wells, Kevin; Lewis, Emma; Guy, Matthew; Goswami, Budhaditya
2011-03-01
The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications.
A simplified motion model for estimating respiratory motion from orbiting views
NASA Astrophysics Data System (ADS)
Zeng, Rongping; Fessler, Jeffrey A.; Balter, James M.
2007-03-01
We have shown previously that the internal motion caused by a patient's breathing can be estimated from a sequence of slowly rotating 2D cone-beam X-ray projection views and a static prior of of the patient's anatomy. 1, 2 The estimator iteratively updates a parametric 3D motion model so that the modeled projection views of the deformed reference volume best match the measured projection views. Complicated motion models with many degrees of freedom may better describe the real motion, but the optimizations assiciated with them may overfit noise and may be easily trapped by local minima due to a large number of parameters. For the latter problem, we believe it can be solved by offering the optimization algorithm a good starting point within the valley containing the global minimum point. Therefore, we propose to start the motion estimation with a simplified motion model, in which we assume the displacement of each voxel at any time is proportional to the full movement of that voxel from extreme exhale to extreme inhale. We first obtain the full motion by registering two breath-hold CT volumes at end-expiration and end-inspiration. We then estimate a sequence of scalar displacement proportionality parameters. Thus the goal simplifies to finding a motion amplitude signal. This estimation problem can be solved quickly using the exhale reference volume and projection views with coarse (downsampled) resolution, while still providing acceptable estimation accuracy. The estimated simple motion then can be used to initialize a more complicated motion estimator.
Theory and Validation of Magnetic Resonance Fluid Motion Estimation Using Intensity Flow Data
Wong, Kelvin Kian Loong; Kelso, Richard Malcolm; Worthley, Stephen Grant; Sanders, Prashanthan; Mazumdar, Jagannath; Abbott, Derek
2009-01-01
Background Motion tracking based on spatial-temporal radio-frequency signals from the pixel representation of magnetic resonance (MR) imaging of a non-stationary fluid is able to provide two dimensional vector field maps. This supports the underlying fundamentals of magnetic resonance fluid motion estimation and generates a new methodology for flow measurement that is based on registration of nuclear signals from moving hydrogen nuclei in fluid. However, there is a need to validate the computational aspect of the approach by using velocity flow field data that we will assume as the true reference information or ground truth. Methodology/Principal Findings In this study, we create flow vectors based on an ideal analytical vortex, and generate artificial signal-motion image data to verify our computational approach. The analytical and computed flow fields are compared to provide an error estimate of our methodology. The comparison shows that the fluid motion estimation approach using simulated MR data is accurate and robust enough for flow field mapping. To verify our methodology, we have tested the computational configuration on magnetic resonance images of cardiac blood and proved that the theory of magnetic resonance fluid motion estimation can be applicable practically. Conclusions/Significance The results of this work will allow us to progress further in the investigation of fluid motion prediction based on imaging modalities that do not require velocity encoding. This article describes a novel theory of motion estimation based on magnetic resonating blood, which may be directly applied to cardiac flow imaging. PMID:19270756
Viola, Francesco; Coe, Ryan L.; Owen, Kevin; Guenther, Drake A.; Walker, William F.
2008-01-01
Image registration and motion estimation play central roles in many fields, including RADAR, SONAR, light microscopy, and medical imaging. Because of its central significance, estimator accuracy, precision, and computational cost are of critical importance. We have previously presented a highly accurate, spline-based time delay estimator that directly determines sub-sample time delay estimates from sampled data. The algorithm uses cubic splines to produce a continuous representation of a reference signal and then computes an analytical matching function between this reference and a delayed signal. The location of the minima of this function yields estimates of the time delay. In this paper we describe the MUlti-dimensional Spline-based Estimator (MUSE) that allows accurate and precise estimation of multidimensional displacements/strain components from multidimensional data sets. We describe the mathematical formulation for two- and three-dimensional motion/strain estimation and present simulation results to assess the intrinsic bias and standard deviation of this algorithm and compare it to currently available multi-dimensional estimators. In 1000 noise-free simulations of ultrasound data we found that 2D MUSE exhibits maximum bias of 2.6 × 10−4 samples in range and 2.2 × 10−3 samples in azimuth (corresponding to 4.8 and 297 nm, respectively). The maximum simulated standard deviation of estimates in both dimensions was comparable at roughly 2.8 × 10−3 samples (corresponding to 54 nm axially and 378 nm laterally). These results are between two and three orders of magnitude better than currently used 2D tracking methods. Simulation of performance in 3D yielded similar results to those observed in 2D. We also present experimental results obtained using 2D MUSE on data acquired by an Ultrasonix Sonix RP imaging system with an L14-5/38 linear array transducer operating at 6.6 MHz. While our validation of the algorithm was performed using ultrasound data, MUSE
Proceedings: Earthquake Ground-Motion Estimation in Eastern North America
1988-08-01
Experts in seismology and earthquake engineering convened to evaluate state-of-the-art methods for estimating ground motion from earthquakes in eastern North America. Workshop results presented here will help focus research priorities in ground-motion studies to provide more-realistic design standards for critical facilities.
Wang, Liang; Basarab, Adrian; Girard, Patrick R; Croisille, Pierre; Clarysse, Patrick; Delachartre, Philippe
2015-08-01
Different mathematical tools, such as multidimensional analytic signals, allow for the calculation of 2D spatial phases of real-value images. The motion estimation method proposed in this paper is based on two spatial phases of the 2D analytic signal applied to cardiac sequences. By combining the information of these phases issued from analytic signals of two successive frames, we propose an analytical estimator for 2D local displacements. To improve the accuracy of the motion estimation, a local bilinear deformation model is used within an iterative estimation scheme. The main advantages of our method are: (1) The phase-based method allows the displacement to be estimated with subpixel accuracy and is robust to image intensity variation in time; (2) Preliminary filtering is not required due to the bilinear model. The proposed algorithm, integrating phase-based optical flow motion estimation and the combination of global motion compensation with local bilinear transform, allows spatio-temporal cardiac motion analysis, e.g. strain and dense trajectory estimation over the cardiac cycle. Results from 7 realistic simulated tagged magnetic resonance imaging (MRI) sequences show that our method is more accurate compared with state-of-the-art method for cardiac motion analysis and with another differential approach from the literature. The motion estimation errors (end point error) of the proposed method are reduced by about 33% compared with that of the two methods. In our work, the frame-to-frame displacements are further accumulated in time, to allow for the calculation of myocardial Lagrangian cardiac strains and point trajectories. Indeed, from the estimated trajectories in time on 11 in vivo data sets (9 patients and 2 healthy volunteers), the shape of myocardial point trajectories belonging to pathological regions are clearly reduced in magnitude compared with the ones from normal regions. Myocardial point trajectories, estimated from our phase-based analytic
Fast and Accurate Learning When Making Discrete Numerical Estimates.
Sanborn, Adam N; Beierholm, Ulrik R
2016-04-01
Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155
Fast and Accurate Learning When Making Discrete Numerical Estimates
Sanborn, Adam N.; Beierholm, Ulrik R.
2016-01-01
Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155
The application of mean field theory to image motion estimation.
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. PMID:18289956
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.
Bioaccessibility tests accurately estimate bioavailability of lead to quail
Technology Transfer Automated Retrieval System (TEKTRAN)
Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb, we incorporated Pb-contaminated soils or Pb acetate into diets for Japanese quail (Coturnix japonica), fed the quail for 15 days, and ...
BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE BIOAVAILABILITY OF LEAD TO QUAIL
Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contami...
Luo, Xiongbiao; Wan, Ying; He, Xiangjian; Mori, Kensaku
2015-08-01
This paper proposes an observation-driven adaptive differential evolution algorithm that fuses bronchoscopic video sequences, electromagnetic sensor measurements, and computed tomography images for accurate and smooth bronchoscope three-dimensional motion tracking. Currently an electromagnetic tracker with a position sensor fixed at the bronchoscope tip is commonly used to estimate bronchoscope movements. The large tracking error from directly using sensor measurements, which may be deteriorated heavily by patient respiratory motion and the magnetic field distortion of the tracker, limits clinical applications. How to effectively use sensor measurements for precise and stable bronchoscope electromagnetic tracking remains challenging. We here exploit an observation-driven adaptive differential evolution framework to address such a challenge and boost the tracking accuracy and smoothness. In our framework, two advantageous points are distinguished from other adaptive differential evolution methods: (1) the current observation including sensor measurements and bronchoscopic video images is used in the mutation equation and the fitness computation, respectively and (2) the mutation factor and the crossover rate are determined adaptively on the basis of the current image observation. The experimental results demonstrate that our framework provides much more accurate and smooth bronchoscope tracking than the state-of-the-art methods. Our approach reduces the tracking error from 3.96 to 2.89 mm, improves the tracking smoothness from 4.08 to 1.62 mm, and increases the visual quality from 0.707 to 0.741. PMID:25660001
Large viewing angle three-dimensional display with smooth motion parallax and accurate depth cues.
Yu, Xunbo; Sang, Xinzhu; Gao, Xin; Chen, Zhidong; Chen, Duo; Duan, Wei; Yan, Binbin; Yu, Chongxiu; Xu, Daxiong
2015-10-01
A three-dimensional (3D) display with smooth motion parallax and large viewing angle is demonstrated, which is based on a microlens array and a coded two-dimensional (2D) image on a 50 inch liquid crystal device (LCD) panel with the resolution of 3840 × 2160. Combining with accurate depth cues expressing, the flipping images of the traditional integral imaging (II) are eliminated, and smooth motion parallax can be achieved. The image on the LCD panel is coded as an elemental image packed repeatedly, and the depth cue is determined by the repeated period of elemental image. To construct the 3D image with complex depth structure, the varying period of elemental image is required. Here, the detailed principle and coding method are presented. The shape and the texture of a target 3D image are designed by a structure image and an elemental image, respectively. In the experiment, two groups of structure images and their corresponding elemental images are utilized to construct a 3D scene with a football in a green net. The constructed 3D image exhibits obviously enhanced 3D perception and smooth motion parallax. The viewing angle is 60°, which is much larger than that of the traditional II. PMID:26480110
Image-based camera motion estimation using prior probabilities
NASA Astrophysics Data System (ADS)
Sargent, Dusty; Park, Sun Young; Spofford, Inbar; Vosburgh, Kirby
2011-03-01
Image-based camera motion estimation from video or still images is a difficult problem in the field of computer vision. Many algorithms have been proposed for estimating intrinsic camera parameters, detecting and matching features between images, calculating extrinsic camera parameters based on those features, and optimizing the recovered parameters with nonlinear methods. These steps in the camera motion inference process all face challenges in practical applications: locating distinctive features can be difficult in many types of scenes given the limited capabilities of current feature detectors, camera motion inference can easily fail in the presence of noise and outliers in the matched features, and the error surfaces in optimization typically contain many suboptimal local minima. The problems faced by these techniques are compounded when they are applied to medical video captured by an endoscope, which presents further challenges such as non-rigid scenery and severe barrel distortion of the images. In this paper, we study these problems and propose the use of prior probabilities to stabilize camera motion estimation for the application of computing endoscope motion sequences in colonoscopy. Colonoscopy presents a special case for camera motion estimation in which it is possible to characterize typical motion sequences of the endoscope. As the endoscope is restricted to move within a roughly tube-shaped structure, forward/backward motion is expected, with only small amounts of rotation and horizontal movement. We formulate a probabilistic model of endoscope motion by maneuvering an endoscope and attached magnetic tracker through a synthetic colon model and fitting a distribution to the observed motion of the magnetic tracker. This model enables us to estimate the probability of the current endoscope motion given previously observed motion in the sequence. We add these prior probabilities into the camera motion calculation as an additional penalty term in RANSAC
Motion estimation using the correlation transform.
Drulea, Marius; Nedevschi, Sergiu
2013-08-01
The zero-mean normalized cross-correlation is shown to improve the accuracy of optical flow, but its analytical form is quite complicated for the variational framework. This paper addresses this issue and presents a new direct approach to this matching measure. Our approach uses the correlation transform to define very discriminative descriptors that are precomputed and that have to be matched in the target frame. It is equivalent to the computation of the optical flow for the correlation transforms of the images. The smoothness energy is non-local and uses a robust penalty in order to preserve motion discontinuities. The model is associated with a fast and parallelizable minimization procedure based on the projected-proximal point algorithm. The experiments confirm the strength of this model and implicitly demonstrate the correctness of our solution. The results demonstrate that the involved data term is very robust with respect to changes in illumination, especially where large illumination exists. PMID:23686953
Zhang, Zhijun; Ashraf, Muhammad; Sahn, David J.; Song, Xubo
2014-01-01
Purpose: 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. Methods: 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. Results: Experiments with simulated datasets, images of an ex 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. Conclusions: 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. PMID:24784402
Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation.
Leonhardt, Aljoscha; Ammer, Georg; Meier, Matthias; Serbe, Etienne; Bahl, Armin; Borst, Alexander
2016-05-01
The reliable estimation of motion across varied surroundings represents a survival-critical task for sighted animals. How neural circuits have adapted to the particular demands of natural environments, however, is not well understood. We explored this question in the visual system of Drosophila melanogaster. Here, as in many mammalian retinas, motion is computed in parallel streams for brightness increments (ON) and decrements (OFF). When genetically isolated, ON and OFF pathways proved equally capable of accurately matching walking responses to realistic motion. To our surprise, detailed characterization of their functional tuning properties through in vivo calcium imaging and electrophysiology revealed stark differences in temporal tuning between ON and OFF channels. We trained an in silico motion estimation model on natural scenes and discovered that our optimized detector exhibited differences similar to those of the biological system. Thus, functional ON-OFF asymmetries in fly visual circuitry may reflect ON-OFF asymmetries in natural environments. PMID:26928063
NASA Astrophysics Data System (ADS)
Qu, Xiaolei; Azuma, Takashi; Sugiyama, Ryusuke; Kanazawa, Kengo; Seki, Mika; Sasaki, Akira; Takeuchi, Hideki; Fujiwara, Keisuke; Itani, Kazunori; Tamano, Satoshi; Takagi, Shu; Sakuma, Ichiro; Matsumoto, Yoichiro
2016-07-01
Visualizing an area subjected to high-intensity focused ultrasound (HIFU) therapy is necessary for controlling the amount of HIFU exposure. One of the promising monitoring methods is localized motion imaging (LMI), which estimates coagulation length by detecting the change in stiffness. In this study, we improved the accuracy of our previous LMI by dynamic cross-correlation window (DCCW) and maximum vibration amount (MVA) methods. The DCCW method was used to increase the accuracy of estimating vibration amplitude, and the MVA method was employed to increase signal–noise ratio of the decrease ratio at the coagulated area. The qualitative comparison of results indicated that the two proposed methods could suppress the effect of noise. Regarding the results of the quantitative comparison, coagulation length was estimated with higher accuracy by the improved LMI method, and the root-mean-square error (RMSE) was reduced from 2.51 to 1.69 mm.
Motion estimation for nuclear medicine: a probabilistic approach
NASA Astrophysics Data System (ADS)
Smith, Rhodri; Abd. Rahni, Ashrani Aizzuddin; Jones, John; Tahavori, Fatemeh; Wells, Kevin
2014-03-01
Accurate, Respiratory Motion Modelling of the abdominal-thoracic organs serves as a pre-requisite for motion correction of Nuclear Medicine (NM) Images. Many respiratory motion models to date build a static correspondence between a parametrized external surrogate signal and internal motion. Mean drifts in respiratory motion, changes in respiratory style and noise conditions of the external surrogate signal motivates a more adaptive approach to capture non-stationary behavior. To this effect we utilize the application of our novel Kalman model with an incorporated expectation maximization step to allow adaptive learning of model parameters with changing respiratory observations. A comparison is made with a popular total least squares (PCA) based approach. It is demonstrated that in the presence of noisy observations the Kalman framework outperforms the static PCA model, however, both methods correct for respiratory motion in the computational anthropomorphic phantom to < 2mm. Motion correction performed on 3 dynamic MRI patient datasets using the Kalman model results in correction of respiratory motion to ≍ 3mm.
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. PMID:26712656
Lagrangian speckle model and tissue-motion estimation--theory.
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. PMID:10504093
How Accurately Do Spectral Methods Estimate Effective Elastic Thickness?
NASA Astrophysics Data System (ADS)
Perez-Gussinye, M.; Lowry, A. R.; Watts, A. B.; Velicogna, I.
2002-12-01
The effective elastic thickness, Te, is an important parameter that has the potential to provide information on the long-term thermal and mechanical properties of the the lithosphere. Previous studies have estimated Te using both forward and inverse (spectral) methods. While there is generally good agreement between the results obtained using these methods, spectral methods are limited because they depend on the spectral estimator and the window size chosen for analysis. In order to address this problem, we have used a multitaper technique which yields optimal estimates of the bias and variance of the Bouguer coherence function relating topography and gravity anomaly data. The technique has been tested using realistic synthetic topography and gravity. Synthetic data were generated assuming surface and sub-surface (buried) loading of an elastic plate with fractal statistics consistent with real data sets. The cases of uniform and spatially varying Te are examined. The topography and gravity anomaly data consist of 2000x2000 km grids sampled at 8 km interval. The bias in the Te estimate is assessed from the difference between the true Te value and the mean from analyzing 100 overlapping windows within the 2000x2000 km data grids. For the case in which Te is uniform, the bias and variance decrease with window size and increase with increasing true Te value. In the case of a spatially varying Te, however, there is a trade-off between spatial resolution and variance. With increasing window size the variance of the Te estimate decreases, but the spatial changes in Te are smeared out. We find that for a Te distribution consisting of a strong central circular region of Te=50 km (radius 600 km) and progressively smaller Te towards its edges, the 800x800 and 1000x1000 km window gave the best compromise between spatial resolution and variance. Our studies demonstrate that assumed stationarity of the relationship between gravity and topography data yields good results even in
Accurate feature detection and estimation using nonlinear and multiresolution analysis
NASA Astrophysics Data System (ADS)
Rudin, Leonid; Osher, Stanley
1994-11-01
A program for feature detection and estimation using nonlinear and multiscale analysis was completed. The state-of-the-art edge detection was combined with multiscale restoration (as suggested by the first author) and robust results in the presence of noise were obtained. Successful applications to numerous images of interest to DOD were made. Also, a new market in the criminal justice field was developed, based in part, on this work.
Highly accurate analytic formulae for projectile motion subjected to quadratic drag
NASA Astrophysics Data System (ADS)
Turkyilmazoglu, Mustafa
2016-05-01
The classical phenomenon of motion of a projectile fired (thrown) into the horizon through resistive air charging a quadratic drag onto the object is revisited in this paper. No exact solution is known that describes the full physical event under such an exerted resistance force. Finding elegant analytical approximations for the most interesting engineering features of dynamical behavior of the projectile is the principal target. Within this purpose, some analytical explicit expressions are derived that accurately predict the maximum height, its arrival time as well as the flight range of the projectile at the highest ascent. The most significant property of the proposed formulas is that they are not restricted to the initial speed and firing angle of the object, nor to the drag coefficient of the medium. In combination with the available approximations in the literature, it is possible to gain information about the flight and complete the picture of a trajectory with high precision, without having to numerically simulate the full governing equations of motion.
Self-Motion and Depth Estimation from Image Sequences
NASA Technical Reports Server (NTRS)
Perrone, John
1999-01-01
An image-based version of a computational model of human self-motion perception (developed in collaboration with Dr. Leland S. Stone at NASA Ames Research Center) has been generated and tested. The research included in the grant proposal sought to extend the utility of the self-motion model so that it could be used for explaining and predicting human performance in a greater variety of aerospace applications. The model can now be tested with video input sequences (including computer generated imagery) which enables simulation of human self-motion estimation in a variety of applied settings.
Threshold adjusted calcium scoring using CT is less susceptible to cardiac motion and more accurate.
Groen, J M; Dijkstra, H; Greuter, M J W; Oudkerk, M
2009-02-01
The purpose of this paper is to investigate calcium scoring on computed tomography (CT) using an adjusted threshold depending on the maximum Hounsfield value within the calcification (HU(peak)). The volume of 19 calcifications was retrospectively determined on 64-slice multidetector CT and dual source CT (DSCT) at different thresholds and the threshold associated with the physical volume was determined. In addition, approximately 10 000 computer simulations were done simulating the same process for calcifications with mixed density. Using these data a relation between the HU(peak) and the threshold could be established. Hereafter, this relation was assessed by scanning six calcifications in a phantom at 40-110 beats per minute using DSCT. The influence of motion was determined and the measured calcium scores were compared to the physical volumes and mass. A positive linear correlation was found between the scoring threshold and the HU(peak) of the calcifications both for the phantom measurements as for the computer simulations. Using this relation the individual threshold for each calcification could be calculated. Calcium scores of the moving calcifications determined with an adjusted threshold were approximately 30% less susceptible to cardiac motion compared to standard calcium scoring. Furthermore, these scores approximated the physical volume and mass at least 10% better than the standard calcium scores. The threshold in calcium scoring should be adjusted for each individual calcification based on the HU(peak) of the calcification. Calcium scoring using an adjusted threshold is less susceptible to cardiac motion and more accurate compared to the physical values. PMID:19291982
Accurate tempo estimation based on harmonic + noise decomposition
NASA Astrophysics Data System (ADS)
Alonso, Miguel; Richard, Gael; David, Bertrand
2006-12-01
We present an innovative tempo estimation system that processes acoustic audio signals and does not use any high-level musical knowledge. Our proposal relies on a harmonic + noise decomposition of the audio signal by means of a subspace analysis method. Then, a technique to measure the degree of musical accentuation as a function of time is developed and separately applied to the harmonic and noise parts of the input signal. This is followed by a periodicity estimation block that calculates the salience of musical accents for a large number of potential periods. Next, a multipath dynamic programming searches among all the potential periodicities for the most consistent prospects through time, and finally the most energetic candidate is selected as tempo. Our proposal is validated using a manually annotated test-base containing 961 music signals from various musical genres. In addition, the performance of the algorithm under different configurations is compared. The robustness of the algorithm when processing signals of degraded quality is also measured.
Bioaccessibility tests accurately estimate bioavailability of lead to quail
Beyer, W. Nelson; Basta, Nicholas T; Chaney, Rufus L.; Henry, Paula F.; Mosby, David; Rattner, Barnett A.; Scheckel, Kirk G.; Sprague, Dan; Weber, John
2016-01-01
Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from five Pb-contaminated Superfund sites had relative bioavailabilities from 33%-63%, with a mean of about 50%. Treatment of two of the soils with phosphorus significantly reduced the bioavailability of Pb. Bioaccessibility of Pb in the test soils was then measured in six in vitro tests and regressed on bioavailability. They were: the “Relative Bioavailability Leaching Procedure” (RBALP) at pH 1.5, the same test conducted at pH 2.5, the “Ohio State University In vitro Gastrointestinal” method (OSU IVG), the “Urban Soil Bioaccessible Lead Test”, the modified “Physiologically Based Extraction Test” and the “Waterfowl Physiologically Based Extraction Test.” All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the RBALP pH 2.5 and OSU IVG tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter (24%), or present as Pb sulfate (18%). Additional Pb was associated with P (chloropyromorphite, hydroxypyromorphite and tertiary Pb phosphate), and with Pb carbonates, leadhillite (a lead sulfate carbonate hydroxide), and Pb sulfide. The formation of chloropyromorphite reduced the bioavailability of Pb and the amendment of Pb-contaminated soils with P may be a thermodynamically favored means to sequester Pb.
A robust motion estimation system for minimal invasive laparoscopy
NASA Astrophysics Data System (ADS)
Marcinczak, Jan Marek; von Öhsen, Udo; Grigat, Rolf-Rainer
2012-02-01
Laparoscopy is a reliable imaging method to examine the liver. However, due to the limited field of view, a lot of experience is required from the surgeon to interpret the observed anatomy. Reconstruction of organ surfaces provide valuable additional information to the surgeon for a reliable diagnosis. Without an additional external tracking system the structure can be recovered from feature correspondences between different frames. In laparoscopic images blurred frames, specular reflections and inhomogeneous illumination make feature tracking a challenging task. We propose an ego-motion estimation system for minimal invasive laparoscopy that can cope with specular reflection, inhomogeneous illumination and blurred frames. To obtain robust feature correspondence, the approach combines SIFT and specular reflection segmentation with a multi-frame tracking scheme. The calibrated five-point algorithm is used with the MSAC robust estimator to compute the motion of the endoscope from multi-frame correspondence. The algorithm is evaluated using endoscopic videos of a phantom. The small incisions and the rigid endoscope limit the motion in minimal invasive laparoscopy. These limitations are considered in our evaluation and are used to analyze the accuracy of pose estimation that can be achieved by our approach. The endoscope is moved by a robotic system and the ground truth motion is recorded. The evaluation on typical endoscopic motion gives precise results and demonstrates the practicability of the proposed pose estimation system.
Incorporating Uncertainty in Ground Motion into Damage Estimation Calculations
NASA Astrophysics Data System (ADS)
Latchman, S.; Simic, M.
2012-04-01
It is well known that a ground motion prediction equation produces not just a point estimate but a variation around this point estimate. This variation in ground motion is given by a standard deviation and ground motions can be said to be lognormally distributed. When estimating the damage to a property from an earthquake, for a given fixed ground motion intensity of say 0.5g there would be a variation in damage modelled. Therefore, there are two properties varying - the intensity of the earthquake and the vulnerability of the structure. Typically, combining the two probability distributions would be computationally expensive and possibly unrealistic if a large number of locations were being modelled. This paper seeks to investigate theoretically how the two distributions can be combined to give a single probability distribution of damage and we also investigate methods which allow this computation to be speeded up through approximations. Finally the change in mean damage amount and standard deviation after accounting for uncertainty in the ground motion (as opposed to using a point estimate) is also investigated.
Bioaccessibility tests accurately estimate bioavailability of lead to quail.
Beyer, W Nelson; Basta, Nicholas T; Chaney, Rufus L; Henry, Paula F P; Mosby, David E; Rattner, Barnett A; Scheckel, Kirk G; Sprague, Daniel T; Weber, John S
2016-09-01
Hazards of soil-borne lead (Pb) to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, the authors measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from 5 Pb-contaminated Superfund sites had relative bioavailabilities from 33% to 63%, with a mean of approximately 50%. Treatment of 2 of the soils with phosphorus (P) significantly reduced the bioavailability of Pb. Bioaccessibility of Pb in the test soils was then measured in 6 in vitro tests and regressed on bioavailability: the relative bioavailability leaching procedure at pH 1.5, the same test conducted at pH 2.5, the Ohio State University in vitro gastrointestinal method, the urban soil bioaccessible lead test, the modified physiologically based extraction test, and the waterfowl physiologically based extraction test. All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the relative bioavailability leaching procedure at pH 2.5 and Ohio State University in vitro gastrointestinal tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter (24%), or present as Pb sulfate (18%). Additional Pb was associated with P (chloropyromorphite, hydroxypyromorphite, and tertiary Pb phosphate) and with Pb carbonates, leadhillite (a lead sulfate carbonate hydroxide), and Pb sulfide. The formation of chloropyromorphite reduced the bioavailability of Pb, and the amendment of Pb-contaminated soils with P may be a thermodynamically favored means to sequester Pb. Environ Toxicol Chem 2016;35:2311-2319. Published 2016 Wiley Periodicals Inc. on behalf of
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.
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. PMID:27385378
Accurate Visual Heading Estimation at High Rotation Rate Without Oculomotor or Static-Depth Cues
NASA Technical Reports Server (NTRS)
Stone, Leland S.; Perrone, John A.; Null, Cynthia H. (Technical Monitor)
1995-01-01
It has been claimed that either oculomotor or static depth cues provide the signals about self-rotation necessary approx.-1 deg/s. We tested this hypothesis by simulating self-motion along a curved path with the eyes fixed in the head (plus or minus 16 deg/s of rotation). Curvilinear motion offers two advantages: 1) heading remains constant in retinotopic coordinates, and 2) there is no visual-oculomotor conflict (both actual and simulated eye position remain stationary). We simulated 400 ms of rotation combined with 16 m/s of translation at fixed angles with respect to gaze towards two vertical planes of random dots initially 12 and 24 m away, with a field of view of 45 degrees. Four subjects were asked to fixate a central cross and to respond whether they were translating to the left or right of straight-ahead gaze. From the psychometric curves, heading bias (mean) and precision (semi-interquartile) were derived. The mean bias over 2-5 runs was 3.0, 4.0, -2.0, -0.4 deg for the first author and three naive subjects, respectively (positive indicating towards the rotation direction). The mean precision was 2.0, 1.9, 3.1, 1.6 deg. respectively. The ability of observers to make relatively accurate and precise heading judgments, despite the large rotational flow component, refutes the view that extra-flow-field information is necessary for human visual heading estimation at high rotation rates. Our results support models that process combined translational/rotational flow to estimate heading, but should not be construed to suggest that other cues do not play an important role when they are available to the observer.
Image deblurring by motion estimation for remote sensing
NASA Astrophysics Data System (ADS)
Chen, Yueting; Wu, Jiagu; Xu, Zhihai; Li, Qi; Feng, Huajun
2010-08-01
The imagery resolution of imaging systems for remote sensing is often limited by image degradation resulting from unwanted motion disturbances of the platform during image exposures. Since the form of the platform vibration can be arbitrary, the lack of priori knowledge about the motion function (the PSF) suggests blind restoration approaches. A deblurring method which combines motion estimation and image deconvolution both for area-array and TDI remote sensing has been proposed in this paper. The image motion estimation is accomplished by an auxiliary high-speed detector and a sub-pixel correlation algorithm. The PSF is then reconstructed from estimated image motion vectors. Eventually, the clear image can be recovered by the Richardson-Lucy (RL) iterative deconvolution algorithm from the blurred image of the prime camera with the constructed PSF. The image deconvolution for the area-array detector is direct. While for the TDICCD detector, an integral distortion compensation step and a row-by-row deconvolution scheme are applied. Theoretical analyses and experimental results show that, the performance of the proposed concept is convincing. Blurred and distorted images can be properly recovered not only for visual observation, but also with significant objective evaluation increment.
Particle filtering for sensor-to-sensor self-calibration and motion estimation
NASA Astrophysics Data System (ADS)
Yang, Yafei; Li, Jianguo
2013-01-01
This paper addresses the problem of calibrating the six degrees-of-freedom rigid body transform between a camera and an inertial measurement unit (IMU) while at the same time estimating the 3D motion of a vehicle. A high-fidelity measurement model for the camera and IMU are derived and the estimation algorithm are implemented within the particle filter (PF) framework. Belonging to the class of Monte Carlo sequential methods, the filter uses the unscented Kalman filter (UKF) to generate importance proposal distribution. It can not only avoid the limitation of the UKF which can only apply to Gaussian distribution, but also avoid the limitation of the standard PF which can not include the new measurements. Moreover, the proposed algorithm requires no additional hardware equipment. Simulation results illustrate the ill effects of misalignment on motion estimation and demonstrate accurate estimation of both the calibration parameters and the state of the vehicle.
Motion Estimation Based on Mutual Information and Adaptive Multi-Scale Thresholding.
Xu, Rui; Taubman, David; Naman, Aous Thabit
2016-03-01
This paper proposes a new method of calculating a matching metric for motion estimation. The proposed method splits the information in the source images into multiple scale and orientation subbands, reduces the subband values to a binary representation via an adaptive thresholding algorithm, and uses mutual information to model the similarity of corresponding square windows in each image. A moving window strategy is applied to recover a dense estimated motion field whose properties are explored. The proposed matching metric is a sum of mutual information scores across space, scale, and orientation. This facilitates the exploitation of information diversity in the source images. Experimental comparisons are performed amongst several related approaches, revealing that the proposed matching metric is better able to exploit information diversity, generating more accurate motion fields. PMID:26742132
An Adaptive Motion Estimation Scheme for Video Coding
Gao, Yuan; Jia, Kebin
2014-01-01
The unsymmetrical-cross multihexagon-grid search (UMHexagonS) is one of the best fast Motion Estimation (ME) algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV) distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised. PMID:24672313
Intrathoracic tumour motion estimation from CT imaging using the 3D optical flow method
NASA Astrophysics Data System (ADS)
Guerrero, Thomas; Zhang, Geoffrey; Huang, Tzung-Chi; Lin, Kang-Ping
2004-09-01
The purpose of this work was to develop and validate an automated method for intrathoracic tumour motion estimation from breath-hold computed tomography (BH CT) imaging using the three-dimensional optical flow method (3D OFM). A modified 3D OFM algorithm provided 3D displacement vectors for each voxel which were used to map tumour voxels on expiration BH CT onto inspiration BH CT images. A thoracic phantom and simulated expiration/inspiration BH CT pairs were used for validation. The 3D OFM was applied to the measured inspiration and expiration BH CT images from one lung cancer and one oesophageal cancer patient. The resulting displacements were plotted in histogram format and analysed to provide insight regarding the tumour motion. The phantom tumour displacement was measured as 1.20 and 2.40 cm with full-width at tenth maximum (FWTM) for the distribution of displacement estimates of 0.008 and 0.006 cm, respectively. The maximum error of any single voxel's motion estimate was 1.1 mm along the z-dimension or approximately one-third of the z-dimension voxel size. The simulated BH CT pairs revealed an rms error of less than 0.25 mm. The displacement of the oesophageal tumours was nonuniform and up to 1.4 cm, this was a new finding. A lung tumour maximum displacement of 2.4 cm was found in the case evaluated. In conclusion, 3D OFM provided an accurate estimation of intrathoracic tumour motion, with estimated errors less than the voxel dimension in a simulated motion phantom study. Surprisingly, oesophageal tumour motion was large and nonuniform, with greatest motion occurring at the gastro-oesophageal junction. Presented at The IASTED Second International Conference on Biomedical Engineering (BioMED 2004), Innsbruck, Austria, 16-18 February 2004.
Improving visual estimates of cervical spine range of motion.
Hirsch, Brandon P; Webb, Matthew L; Bohl, Daniel D; Fu, Michael; Buerba, Rafael A; Gruskay, Jordan A; Grauer, Jonathan N
2014-11-01
Cervical spine range of motion (ROM) is a common measure of cervical conditions, surgical outcomes, and functional impairment. Although ROM is routinely assessed by visual estimation in clinical practice, visual estimates have been shown to be unreliable and inaccurate. Reliable goniometers can be used for assessments, but the associated costs and logistics generally limit their clinical acceptance. To investigate whether training can improve visual estimates of cervical spine ROM, we asked attending surgeons, residents, and medical students at our institution to visually estimate the cervical spine ROM of healthy subjects before and after a training session. This training session included review of normal cervical spine ROM in 3 planes and demonstration of partial and full motion in 3 planes by multiple subjects. Estimates before, immediately after, and 1 month after this training session were compared to assess reliability and accuracy. Immediately after training, errors decreased by 11.9° (flexion-extension), 3.8° (lateral bending), and 2.9° (axial rotation). These improvements were statistically significant. One month after training, visual estimates remained improved, by 9.5°, 1.6°, and 3.1°, respectively, but were statistically significant only in flexion-extension. Although the accuracy of visual estimates can be improved, clinicians should be aware of the limitations of visual estimates of cervical spine ROM. Our study results support scrutiny of visual assessment of ROM as a criterion for diagnosing permanent impairment or disability. PMID:25379754
Validation and Comparison of Approaches to Respiratory Motion Estimation
NASA Astrophysics Data System (ADS)
Kabus, Sven; Klinder, Tobias; Murphy, Keelin; Werner, René; Sarrut, David
The accuracy of respiratory motion estimation has a direct impact on the success of clinical applications such as diagnosis, as well as planning, delivery, and assessment of therapy for lung or other thoracic diseases. While rigid registration is well suited to validation and has reached a mature state in clinical applications, for non-rigid registration no gold-standard exists. This chapter investigates the validation of non-rigid registration accuracy with a focus on lung motion. The central questions addressed in this chapter are (1) how to measure registration accuracy, (2) how to generate ground-truth for validation, and (3) how to interpret accuracy assessment results.
NASA Astrophysics Data System (ADS)
Merckel, Loic; Nishida, Toyoaki
In this paper, we introduce a method for recognizing a subject complex object in real world environment. We use a three dimensional model described by line segments of the object and the data provided by a three-axis orientation sensor attached to the video camera. We assume that existing methods for finding line features in the image allow at least one model line segment to be detected as a single continuous segment. The method consists of two main steps: generation of pose hypotheses and then evaluation of each pose in order to select the most appropriate one. The first stage is three-fold: model visibility, line matching and pose estimation; the second stage aims to rank the poses by evaluating the similarity between the projected model lines and the image lines. Furthermore, we propose an additional step that consists of refining the best candidate pose by using the Lie group formalism of spatial rigid motions. Such a formalism provides an efficient local parameterization of the set of rigid rotation via the exponential map. A set of experiments demonstrating the robustness of this approach is presented.
Estimation of self-motion duration and distance in rodents
Kautzky, Magdalena
2016-01-01
Spatial orientation and navigation rely on information about landmarks and self-motion cues gained from multi-sensory sources. In this study, we focused on self-motion and examined the capability of rodents to extract and make use of information about own movement, i.e. path integration. Path integration has been investigated in depth in insects and humans. Demonstrations in rodents, however, mostly stem from experiments on heading direction; less is known about distance estimation. We introduce a novel behavioural paradigm that allows for probing temporal and spatial contributions to path integration. The paradigm is a bisection task comprising movement in a virtual reality environment in combination with either timing the duration ran or estimating the distance covered. We performed experiments with Mongolian gerbils and could show that the animals can keep track of time and distance during spatial navigation. PMID:27293792
An Alternative Estimate of the Motion of the Capricorn Plate
NASA Astrophysics Data System (ADS)
Burris, S. G.; Gordon, R. G.
2013-12-01
Diffuse plate boundaries cover ~15% of Earth's surface and can exceed 1000 km in across-strike width. Deforming oceanic lithosphere in the equatorial Indian Ocean accommodates the motion between the India and Capricorn plates and serves as their mutual diffuse plate boundary. This deforming lithosphere lies between the Central Indian Ridge to the west and the Sumatra trench to the east; the plates diverge to the west of ≈74°E and converge to the east of it. Many data have shown that the pole of rotation between the India and Capricorn plates lies within this diffuse plate boundary [1,2]. Surprisingly, however, the recently estimated angular velocity in the MORVEL global set of angular velocities [3] places this pole of rotation north of prior poles by several degrees, and north of the diffuse plate boundary. The motion between the India and Capricorn plates can only be estimated indirectly by differencing the motion of the India plate relative to the Somalia plate, on the one hand, and the motion of the Capricorn plate relative to Somalia plate, on the other. While the MORVEL India-Somalia angular velocity is similar to prior estimates, the MORVEL Capricorn-Somalia pole of rotation lies northwest of its predecessors. The difference is not caused by new transform azimuth data incorporated into MORVEL or by the new application of a correction to spreading rates for outward displacement. Instead the difference appears to be caused by a few anomalous spreading rates near the northern end of the Capricorn-Somalia plate boundary along the Central Indian Ridge. Rejecting these data leads to consistency with prior results. Implications for the motion of the Capricorn plate relative to Australia will be discussed. [1] DeMets, C., R. G. Gordon, and J.-Y. Royer, 2005. Motion between the Indian, Capricorn, and Somalian plates since 20 Ma: implications for the timing and magnitude of distributed deformation in the equatorial Indian ocean, Geophys. J. Int., 161, 445-468. [2
Wood, Nathan A.; del Agua, Diego Moral; Zenati, Marco A.; Riviere, Cameron N.
2012-01-01
HeartLander, a small mobile robot designed to provide treatments to the surface of the beating heart, overcomes a major difficulty of minimally invasive cardiac surgery, providing a stable operating platform. This is achieved inherently in the way the robot adheres to and crawls over the surface of the heart. This mode of operation does not require physiological motion compensation to provide this stable environment; however, modeling of physiological motion is advantageous in providing more accurate position estimation as well as synchronization of motion to the physiological cycles. The work presented uses an Extended Kalman Filter framework to estimate parameters of non-stationary Fourier series models of the motion of the heart due to the respiratory and cardiac cycles as well as the position of the robot as it moves over the surface of the heart. The proposed method is demonstrated in the laboratory with HeartLander operating on a physiological motion simulator. Improved performance is demonstrated in comparison to the filtering methods previously used with HeartLander. The use of detected physiological cycle phases to synchronize locomotion of HeartLander is also described. PMID:23066511
Cook, Andrea J.; Elmore, Joann G.; Zhu, Weiwei; Jackson, Sara L.; Carney, Patricia A.; Flowers, Chris; Onega, Tracy; Geller, Berta; Rosenberg, Robert D.; Miglioretti, Diana L.
2013-01-01
Objective To determine if U.S. radiologists accurately estimate their own interpretive performance of screening mammography and how they compare their performance to their peers’. Materials and Methods 174 radiologists from six Breast Cancer Surveillance Consortium (BCSC) registries completed a mailed survey between 2005 and 2006. Radiologists’ estimated and actual recall, false positive, and cancer detection rates and positive predictive value of biopsy recommendation (PPV2) for screening mammography were compared. Radiologists’ ratings of their performance as lower, similar, or higher than their peers were compared to their actual performance. Associations with radiologist characteristics were estimated using weighted generalized linear models. The study was approved by the institutional review boards of the participating sites, informed consent was obtained from radiologists, and procedures were HIPAA compliant. Results While most radiologists accurately estimated their cancer detection and recall rates (74% and 78% of radiologists), fewer accurately estimated their false positive rate and PPV2 (19% and 26%). Radiologists reported having similar (43%) or lower (31%) recall rates and similar (52%) or lower (33%) false positive rates compared to their peers, and similar (72%) or higher (23%) cancer detection rates and similar (72%) or higher (38%) PPV2. Estimation accuracy did not differ by radiologists’ characteristics except radiologists who interpret ≤1,000 mammograms annually were less accurate at estimating their recall rates. Conclusion Radiologists perceive their performance to be better than it actually is and at least as good as their peers. Radiologists have particular difficulty estimating their false positive rates and PPV2. PMID:22915414
Strong Ground Motion Estimation During the Kutch, India Earthquake
NASA Astrophysics Data System (ADS)
Iyengar, R. N.; Kanth, S. T. G. Raghu
2006-01-01
In the absence of strong motion records, ground motion during the 26th January, 2001 Kutch, India earthquake, has been estimated by analytical methods. A contour map of peak ground acceleration (PGA) values in the near source region is provided. These results are validated by comparing them with spectral response recorder data and field observations. It is found that very near the epicenter, PGA would have exceeded 0.6 g. A set of three aftershock records have been used as empirical Green's functions to simulate ground acceleration time history and 5% damped response spectrum at Bhuj City. It is found that at Bhuj, PGA would have been 0.31 g 0.37 g. It is demonstrated that source mechanism models can be effectively used to understand spatial variability of large-scale ground movements near urban areas due to the rupture of active faults.
A mathematical model for efficient estimation of aircraft motions
NASA Technical Reports Server (NTRS)
Bach, R. E., Jr.
1983-01-01
In the usual formulation of the aircraft state-estimation problem, motions along a flight trajectory are represented by a plant consisting of nonlinear state and measurement models. Problem solution using this formulation requires that both state- and measurement-dependent Jacobian matrices be evaluated along any trajectory. In this paper it is shown that a set of state variables can be chosen to realize a linear state model of very simple form, such that all nonlinearities appear in the measurement model. The potential advantage of the new formulation is computational: the Jacobian matrix corresponding to a linear state model is constant, a feature that should outweigh the fact that the measurement model is more complicated than in the conventinal formulation. To compare the modeling methods, aircraft motions from typical flight-test and accident data were estimated, using each formulation with the same off-line (smoothing) algorithm. The results of these experiments, reported in the paper, demonstrate clearly the computational superiority of the linear state-variable formulation. The procedure advocated here may be extended to other nonlinear estimation problems, including on-line (filtering) applications.
Browning, Sharon R.; Browning, Brian L.
2015-01-01
Existing methods for estimating historical effective population size from genetic data have been unable to accurately estimate effective population size during the most recent past. We present a non-parametric method for accurately estimating recent effective population size by using inferred long segments of identity by descent (IBD). We found that inferred segments of IBD contain information about effective population size from around 4 generations to around 50 generations ago for SNP array data and to over 200 generations ago for sequence data. In human populations that we examined, the estimates of effective size were approximately one-third of the census size. We estimate the effective population size of European-ancestry individuals in the UK four generations ago to be eight million and the effective population size of Finland four generations ago to be 0.7 million. Our method is implemented in the open-source IBDNe software package. PMID:26299365
Pose estimation for one-dimensional object with general motion
NASA Astrophysics Data System (ADS)
Liu, Jinbo; Song, Ge; Zhang, Xiaohu
2014-11-01
Our primary interest is in real-time one-dimensional object's pose estimation. In this paper, a method to estimate general motion one-dimensional object's pose, that is, the position and attitude parameters, using a single camera is proposed. Centroid-movement is necessarily continuous and orderly in temporal space, which means it follows at least approximately certain motion law in a short period of time. Therefore, the centroid trajectory in camera frame can be described as a combination of temporal polynomials. Two endpoints on one-dimensional object, A and B, at each time are projected on the corresponding image plane. With the relationship between A, B and centroid C, we can obtain a linear equation system related to the temporal polynomials' coefficients, in which the camera has been calibrated and the image coordinates of A and B are known. Then in the cases that object moves continuous in natural temporal space within the view of a stationary camera, the position of endpoints on the one-dimensional object can be located and also the attitude can be estimated using two end points. Moreover the position of any other point aligned on one-dimensional object can also be solved. Scene information is not needed in the proposed method. If the distance between the endpoints is not known, a scale factor between the object's real positions and the estimated results will exist. In order to improve the algorithm's performance from accuracy and robustness, we derive a pain of linear and optimal algorithms. Simulations' and experiments' results show that the method is valid and robust with respect to various Gaussian noise levels. The paper's work contributes to making self-calibration algorithms using one-dimensional objects applicable to practice. Furthermore, the method can also be used to estimate the pose and shape parameters of parallelogram, prism or cylinder objects.
Real-Time Baseline Error Estimation and Correction for GNSS/Strong Motion Seismometer Integration
NASA Astrophysics Data System (ADS)
Li, C. Y. N.; Groves, P. D.; Ziebart, M. K.
2014-12-01
Accurate and rapid estimation of permanent surface displacement is required immediately after a slip event for earthquake monitoring or tsunami early warning. It is difficult to achieve the necessary accuracy and precision at high- and low-frequencies using GNSS or seismometry alone. GNSS and seismic sensors can be integrated to overcome the limitations of each. Kalman filter algorithms with displacement and velocity states have been developed to combine GNSS and accelerometer observations to obtain the optimal displacement solutions. However, the sawtooth-like phenomena caused by the bias or tilting of the sensor decrease the accuracy of the displacement estimates. A three-dimensional Kalman filter algorithm with an additional baseline error state has been developed. An experiment with both a GNSS receiver and a strong motion seismometer mounted on a movable platform and subjected to known displacements was carried out. The results clearly show that the additional baseline error state enables the Kalman filter to estimate the instrument's sensor bias and tilt effects and correct the state estimates in real time. Furthermore, the proposed Kalman filter algorithm has been validated with data sets from the 2010 Mw 7.2 El Mayor-Cucapah Earthquake. The results indicate that the additional baseline error state can not only eliminate the linear and quadratic drifts but also reduce the sawtooth-like effects from the displacement solutions. The conventional zero-mean baseline-corrected results cannot show the permanent displacements after an earthquake; the two-state Kalman filter can only provide stable and optimal solutions if the strong motion seismometer had not been moved or tilted by the earthquake. Yet the proposed Kalman filter can achieve the precise and accurate displacements by estimating and correcting for the baseline error at each epoch. The integration filters out noise-like distortions and thus improves the real-time detection and measurement capability
Real time estimation of ship motions using Kalman filtering techniques
NASA Technical Reports Server (NTRS)
Triantafyllou, M. S.; Bodson, M.; Athans, M.
1983-01-01
The estimation of the heave, pitch, roll, sway, and yaw motions of a DD-963 destroyer is studied, using Kalman filtering techniques, for application in VTOL aircraft landing. The governing equations are obtained from hydrodynamic considerations in the form of linear differential equations with frequency dependent coefficients. In addition, nonminimum phase characteristics are obtained due to the spatial integration of the water wave forces. The resulting transfer matrix function is irrational and nonminimum phase. The conditions for a finite-dimensional approximation are considered and the impact of the various parameters is assessed. A detailed numerical application for a DD-963 destroyer is presented and simulations of the estimations obtained from Kalman filters are discussed.
Fast-coding robust motion estimation model in a GPU
NASA Astrophysics Data System (ADS)
García, Carlos; Botella, Guillermo; de Sande, Francisco; Prieto-Matias, Manuel
2015-02-01
Nowadays vision systems are used with countless purposes. Moreover, the motion estimation is a discipline that allow to extract relevant information as pattern segmentation, 3D structure or tracking objects. However, the real-time requirements in most applications has limited its consolidation, considering the adoption of high performance systems to meet response times. With the emergence of so-called highly parallel devices known as accelerators this gap has narrowed. Two extreme endpoints in the spectrum of most common accelerators are Field Programmable Gate Array (FPGA) and Graphics Processing Systems (GPU), which usually offer higher performance rates than general propose processors. Moreover, the use of GPUs as accelerators involves the efficient exploitation of any parallelism in the target application. This task is not easy because performance rates are affected by many aspects that programmers should overcome. In this paper, we evaluate OpenACC standard, a programming model with directives which favors porting any code to a GPU in the context of motion estimation application. The results confirm that this programming paradigm is suitable for this image processing applications achieving a very satisfactory acceleration in convolution based problems as in the well-known Lucas & Kanade method.
NASA Astrophysics Data System (ADS)
Vizireanu, D. N.; Halunga, S. V.
2012-04-01
A simple, fast and accurate amplitude estimation algorithm of sinusoidal signals for DSP based instrumentation is proposed. It is shown that eight samples, used in two steps, are sufficient. A practical analytical formula for amplitude estimation is obtained. Numerical results are presented. Simulations have been performed when the sampled signal is affected by white Gaussian noise and when the samples are quantized on a given number of bits.
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
th 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.
Reliable camera motion estimation from compressed MPEG videos using machine learning approach
NASA Astrophysics Data System (ADS)
Wang, Zheng; Ren, Jinchang; Wang, Yubin; Sun, Meijun; Jiang, Jianmin
2013-05-01
As an important feature in characterizing video content, camera motion has been widely applied in various multimedia and computer vision applications. A novel method for fast and reliable estimation of camera motion from MPEG videos is proposed, using support vector machine for estimation in a regression model trained on a synthesized sequence. Experiments conducted on real sequences show that the proposed method yields much improved results in estimating camera motions while the difficulty in selecting valid macroblocks and motion vectors is skipped.
Interferometric estimation of ice sheet motion and topography
NASA Technical Reports Server (NTRS)
Joughlin, Ian; Kwok, Ron; Fahnestock, Mark; Winebrenner, Dale; Tulaczyk, Slawek; Gogenini, Prasad
1997-01-01
With ERS-1/2 satellite radar interferometry, it is possible to make measurements of glacier motion with high accuracy and fine spatial resolution. Interferometric techniques were applied to map velocity and topography for several outlet glaciers in Greenland. For the Humboldt and Petermann glaciers, data from several adjacent tracks were combined to make a wide-area map that includes the enhanced flow regions of both glaciers. The discharge flux of the Petermann glacier upstream of the grounding line was estimated, thereby establishing the potential use of ERS-1/2 interferometric data for monitoring ice-sheet discharge. Interferograms collected along a single track are sensitive to only one component of motion. By utilizing data from ascending and descending passes and by making a surface-parallel flow assumption, it is possible to measure the full three-dimensional vector flow field. The application of this technique for an area on the Ryder glacier is demonstrated. Finally, ERS-1/2 interferograms were used to observe a mini-surge on the Ryder glacier that occurred in autumn of 1995.
Stereo image motion monitor for atmospheric mitigation and estimation
NASA Astrophysics Data System (ADS)
Gibson, Kristofor B.
2015-09-01
The knowledge of the turbulence strength in the atmosphere is important for many applications. Imagery in the atmosphere experience significant blur when the turbulence is strong. This can be automatically improved (without user intervention) if the turbulence strength is known. The performance of a high-power laser emitting in the atmosphere can be predicted if the statistics of the turbulence strength is known. If not predicted correctly, the laser may unintentionally destroy a target or fail to be able to disable a target. In this article, we review existing methods that estimate turbulence strength, provide a more in depth error analysis, and propose a new method for estimating and mitigating turbulence in the atmosphere. We focus on methods that are passive in design in order to prevent detection in surveillance scenarios and tactical situations. We also propose a new method, stereo image motion monitor (SIMM) which is a system containing two independent apertures. Our goal in this approach is threefold: 1) We can measure r0 using the DIMM method 2) We can simultaneously estimate r0 individually for each aperture and 3) We have multiple views of the same scene thus can increase the number of frames used in turbulence mitigation methods.
Fractional-order variational optical flow model for motion estimation.
Chen, Dali; Sheng, Hu; Chen, YangQuan; Xue, Dingyü
2013-05-13
A new class of fractional-order variational optical flow models, which generalizes the differential of optical flow from integer order to fractional order, is proposed for motion estimation in this paper. The corresponding Euler-Lagrange equations are derived by solving a typical fractional variational problem, and the numerical implementation based on the Grünwald-Letnikov fractional derivative definition is proposed to solve these complicated fractional partial differential equations. Theoretical analysis reveals that the proposed fractional-order variational optical flow model is the generalization of the typical Horn and Schunck (first-order) variational optical flow model and the second-order variational optical flow model, which provides a new idea for us to study the optical flow model and has an important theoretical implication in optical flow model research. The experiments demonstrate the validity of the generalization of differential order. PMID:23547225
Object tracking by combining detection, motion estimation, and verification
NASA Astrophysics Data System (ADS)
Sidla, Oliver
2010-01-01
Object detection and tracking play an increasing role in modern surveillance systems. Vision research is still confronted with many challenges when it comes to robust tracking in realistic imaging scenarios. We describe a tracking framework which is aimed at the detection and tracking of objects in real-world situations (e.g. from surveillance cameras) and in real-time. Although the current system is used for pedestrian tracking only, it can easily be adapted to other detector types and object classes. The proposed tracker combines i) a simple background model to speed up all following computations, ii)1 a fast object detector realized with a cascaded HOG detector, iii) motion estimation with a KLT Tracker iv) object verification based on texture/color analysis by means of DCT coefficients and , v) dynamic trajectory and object management. The tracker has been successfully applied in indoor and outdoor scenarios it a public transportation hub in the City of Graz, Austria.
Ground motions estimates for a cascadia earthquake from liquefaction evidence
Dickenson, S.E.; Obermeier, S.F.
1998-01-01
Paleoseismic studies conducted in the coastal regions of the Pacific Northwest in the past decade have revealed evidence of crustal downdropping and subsequent tsunami inundation, attributable to a large earthquake along the Cascadia subduction zone which occurred approximately 300 years ago, and most likely in 1700 AD. In order to characterize the severity of ground motions from this earthquake, we report on results of a field search for seismically induced liquefaction features. The search was made chiefly along the coastal portions of several river valleys in Washington, rivers along the central Oregon coast, as well as on islands in the Columbia River of Oregon and Washington. In this paper we focus only on the results of the Columbia River investigation. Numerous liquefaction features were found in some regions, but not in others. The regional distribution of liquefaction features is evaluated as a function of geologic and geotechnical factors at each site in order to estimate the intensity of ground shaking.
On the accurate estimation of gap fraction during daytime with digital cover photography
NASA Astrophysics Data System (ADS)
Hwang, Y. R.; Ryu, Y.; Kimm, H.; Macfarlane, C.; Lang, M.; Sonnentag, O.
2015-12-01
Digital cover photography (DCP) has emerged as an indirect method to obtain gap fraction accurately. Thus far, however, the intervention of subjectivity, such as determining the camera relative exposure value (REV) and threshold in the histogram, hindered computing accurate gap fraction. Here we propose a novel method that enables us to measure gap fraction accurately during daytime under various sky conditions by DCP. The novel method computes gap fraction using a single DCP unsaturated raw image which is corrected for scattering effects by canopies and a reconstructed sky image from the raw format image. To test the sensitivity of the novel method derived gap fraction to diverse REVs, solar zenith angles and canopy structures, we took photos in one hour interval between sunrise to midday under dense and sparse canopies with REV 0 to -5. The novel method showed little variation of gap fraction across different REVs in both dense and spares canopies across diverse range of solar zenith angles. The perforated panel experiment, which was used to test the accuracy of the estimated gap fraction, confirmed that the novel method resulted in the accurate and consistent gap fractions across different hole sizes, gap fractions and solar zenith angles. These findings highlight that the novel method opens new opportunities to estimate gap fraction accurately during daytime from sparse to dense canopies, which will be useful in monitoring LAI precisely and validating satellite remote sensing LAI products efficiently.
A new geometric-based model to accurately estimate arm and leg inertial estimates.
Wicke, Jason; Dumas, Geneviève A
2014-06-01
Segment estimates of mass, center of mass and moment of inertia are required input parameters to analyze the forces and moments acting across the joints. The objectives of this study were to propose a new geometric model for limb segments, to evaluate it against criterion values obtained from DXA, and to compare its performance to five other popular models. Twenty five female and 24 male college students participated in the study. For the criterion measures, the participants underwent a whole body DXA scan, and estimates for segment mass, center of mass location, and moment of inertia (frontal plane) were directly computed from the DXA mass units. For the new model, the volume was determined from two standing frontal and sagittal photographs. Each segment was modeled as a stack of slices, the sections of which were ellipses if they are not adjoining another segment and sectioned ellipses if they were adjoining another segment (e.g. upper arm and trunk). Length of axes of the ellipses was obtained from the photographs. In addition, a sex-specific, non-uniform density function was developed for each segment. A series of anthropometric measurements were also taken by directly following the definitions provided of the different body segment models tested, and the same parameters determined for each model. Comparison of models showed that estimates from the new model were consistently closer to the DXA criterion than those from the other models, with an error of less than 5% for mass and moment of inertia and less than about 6% for center of mass location. PMID:24735506
Accurate Estimation of the Entropy of Rotation-Translation Probability Distributions.
Fogolari, Federico; Dongmo Foumthuim, Cedrix Jurgal; Fortuna, Sara; Soler, Miguel Angel; Corazza, Alessandra; Esposito, Gennaro
2016-01-12
The estimation of rotational and translational entropies in the context of ligand binding has been the subject of long-time investigations. The high dimensionality (six) of the problem and the limited amount of sampling often prevent the required resolution to provide accurate estimates by the histogram method. Recently, the nearest-neighbor distance method has been applied to the problem, but the solutions provided either address rotation and translation separately, therefore lacking correlations, or use a heuristic approach. Here we address rotational-translational entropy estimation in the context of nearest-neighbor-based entropy estimation, solve the problem numerically, and provide an exact and an approximate method to estimate the full rotational-translational entropy. PMID:26605696
Estimating nonrigid motion from inconsistent intensity with robust shape features
Liu, Wenyang; Ruan, Dan
2013-12-15
Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided
Damon, Bruce M.; Heemskerk, Anneriet M.; Ding, Zhaohua
2012-01-01
Fiber curvature is a functionally significant muscle structural property, but its estimation from diffusion-tensor MRI fiber tracking data may be confounded by noise. The purpose of this study was to investigate the use of polynomial fitting of fiber tracts for improving the accuracy and precision of fiber curvature (κ) measurements. Simulated image datasets were created in order to provide data with known values for κ and pennation angle (θ). Simulations were designed to test the effects of increasing inherent fiber curvature (3.8, 7.9, 11.8, and 15.3 m−1), signal-to-noise ratio (50, 75, 100, and 150), and voxel geometry (13.8 and 27.0 mm3 voxel volume with isotropic resolution; 13.5 mm3 volume with an aspect ratio of 4.0) on κ and θ measurements. In the originally reconstructed tracts, θ was estimated accurately under most curvature and all imaging conditions studied; however, the estimates of κ were imprecise and inaccurate. Fitting the tracts to 2nd order polynomial functions provided accurate and precise estimates of κ for all conditions except very high curvature (κ=15.3 m−1), while preserving the accuracy of the θ estimates. Similarly, polynomial fitting of in vivo fiber tracking data reduced the κ values of fitted tracts from those of unfitted tracts and did not change the θ values. Polynomial fitting of fiber tracts allows accurate estimation of physiologically reasonable values of κ, while preserving the accuracy of θ estimation. PMID:22503094
Myocardial motion estimation in tagged MR sequences by using alphaMI-based non rigid registration.
Oubel, E; Tobon-Gomez, C; Hero, A O; Frangi, A F
2005-01-01
Tagged Magnetic Resonance Imaging (MRI) is currently the reference MR modality for myocardial motion and strain analysis. NMI-based non rigid registration has proven to be an accurate method to retrieve cardiac deformation fields. The use of alphaMI permits higher dimensional features to be implemented in myocardial deformation estimation through image registration. This paper demonstrates that this is feasible with a set of Haar wavelet features of high dimension. While we do not demonstrate performance improvement for this set of features, there is no significant degradation as compared to implementing the registration method with the traditional NMI metric. We use Entropic Spanning Graphs (ESGs) to estimate the alphaMI of the wavelet feature vectors WFVs since this is not possible with histograms. To the best of our knowledge, this is the first time that ESGs are used for non rigid registration. PMID:16685969
Complex phase error and motion estimation in synthetic aperture radar imaging
NASA Astrophysics Data System (ADS)
Soumekh, M.; Yang, H.
1991-06-01
Attention is given to a SAR wave equation-based system model that accurately represents the interaction of the impinging radar signal with the target to be imaged. The model is used to estimate the complex phase error across the synthesized aperture from the measured corrupted SAR data by combining the two wave equation models governing the collected SAR data at two temporal frequencies of the radar signal. The SAR system model shows that the motion of an object in a static scene results in coupled Doppler shifts in both the temporal frequency domain and the spatial frequency domain of the synthetic aperture. The velocity of the moving object is estimated through these two Doppler shifts. It is shown that once the dynamic target's velocity is known, its reconstruction can be formulated via a squint-mode SAR geometry with parameters that depend upon the dynamic target's velocity.
Accurate estimation of forest carbon stocks by 3-D remote sensing of individual trees.
Omasa, Kenji; Qiu, Guo Yu; Watanuki, Kenichi; Yoshimi, Kenji; Akiyama, Yukihide
2003-03-15
Forests are one of the most important carbon sinks on Earth. However, owing to the complex structure, variable geography, and large area of forests, accurate estimation of forest carbon stocks is still a challenge for both site surveying and remote sensing. For these reasons, the Kyoto Protocol requires the establishment of methodologies for estimating the carbon stocks of forests (Kyoto Protocol, Article 5). A possible solution to this challenge is to remotely measure the carbon stocks of every tree in an entire forest. Here, we present a methodology for estimating carbon stocks of a Japanese cedar forest by using a high-resolution, helicopter-borne 3-dimensional (3-D) scanning lidar system that measures the 3-D canopy structure of every tree in a forest. Results show that a digital image (10-cm mesh) of woody canopy can be acquired. The treetop can be detected automatically with a reasonable accuracy. The absolute error ranges for tree height measurements are within 42 cm. Allometric relationships of height to carbon stocks then permit estimation of total carbon storage by measurement of carbon stocks of every tree. Thus, we suggest that our methodology can be used to accurately estimate the carbon stocks of Japanese cedar forests at a stand scale. Periodic measurements will reveal changes in forest carbon stocks. PMID:12680675
Reference trajectory generation for rehabilitation robots: complementary limb motion estimation.
Vallery, Heike; van Asseldonk, Edwin H F; Buss, Martin; van der Kooij, Herman
2009-02-01
For gait rehabilitation robots, an important question is how to ensure stable gait, while avoiding any interaction forces between robot and human in case the patient walks correctly. To achieve this, the definition of "correct" gait needs to adapted both to the individual patient and to the situation. Recently, we proposed a method for online trajectory generation that can be applied for hemiparetic subjects. Desired states for one (disabled) leg are generated online based on the movements of the other (sound) leg. An instantaneous mapping between legs is performed by exploiting physiological interjoint couplings. This way, the patient generates the reference motion for the affected leg autonomously. The approach, called Complementary Limb Motion Estimation (CLME), is implemented on the LOPES gait rehabilitation robot and evaluated with healthy subjects in two different experiments. In a previously described study, subjects walk only with one leg, while the robot's other leg acts as a fake prosthesis, to simulate complete loss of function in one leg. This study showed that CLME ensures stable gait. In a second study, to be presented in this paper, healthy subjects walk with both their own legs to assess the interference with self-determined walking. Evaluation criteria are: Power delivered to the joints by the robot, electromyography (EMG) distortions, and kinematic distortions, all compared to zero torque control, which is the baseline of minimum achievable interference. Results indicate that interference of the robot is lower with CLME than with a fixed reference trajectory, mainly in terms of lowered exchanged power and less alteration of EMG. This implies that subjects can walk more naturally with CLME, and they are assisted less by the robot when it is not needed. Future studies with patients are yet to show whether these properties of CLME transfer to the clinical domain. PMID:19211320
Accurate and portable weigh-in-motion system for manifesting air cargo
Nodine, R.N.; Scudiere, M.B.; Jordan, J.K.
1995-12-01
An automated and portable weigh-in-motion system has been developed at Oak Ridge National Laboratory for the purpose of manifesting cargo onto aircraft. The system has an accuracv range of {plus_minus} 3.0% to {plus_minus} 6.0% measuring gross vehicle weight and locating the center of balance of moving vehicles at speeds of 1 to 5 mph. This paper reviews the control/user interface system and weight determination algorithm developed to acquire, process, and interpret multiple sensor inputs. The development effort resulted in a self-zeroing, user-friendly system capable of weighing a wide range of vehicles in any random order. The control system is based on the STANDARD (STD) bus and incorporates custom-designed data acquisition and sensor fusion hardware controlled by a personal computer (PC) based single-board computer. The user interface is written in the ``C`` language to display number of axles, axle weight, axle spacing, gross weight, and center of balance. The weighing algorithm developed will function with any linear weight sensor and a set of four axle switches per sensor.
Bi, Sheng; Zeng, Xiao; Tang, Xin; Qin, Shujia; Lai, King Wai Chiu
2016-01-01
Compressive sensing (CS) theory has opened up new paths for the development of signal processing applications. Based on this theory, a novel single pixel camera architecture has been introduced to overcome the current limitations and challenges of traditional focal plane arrays. However, video quality based on this method is limited by existing acquisition and recovery methods, and the method also suffers from being time-consuming. In this paper, a multi-frame motion estimation algorithm is proposed in CS video to enhance the video quality. The proposed algorithm uses multiple frames to implement motion estimation. Experimental results show that using multi-frame motion estimation can improve the quality of recovered videos. To further reduce the motion estimation time, a block match algorithm is used to process motion estimation. Experiments demonstrate that using the block match algorithm can reduce motion estimation time by 30%. PMID:26950127
Bi, Sheng; Zeng, Xiao; Tang, Xin; Qin, Shujia; Lai, King Wai Chiu
2016-01-01
Compressive sensing (CS) theory has opened up new paths for the development of signal processing applications. Based on this theory, a novel single pixel camera architecture has been introduced to overcome the current limitations and challenges of traditional focal plane arrays. However, video quality based on this method is limited by existing acquisition and recovery methods, and the method also suffers from being time-consuming. In this paper, a multi-frame motion estimation algorithm is proposed in CS video to enhance the video quality. The proposed algorithm uses multiple frames to implement motion estimation. Experimental results show that using multi-frame motion estimation can improve the quality of recovered videos. To further reduce the motion estimation time, a block match algorithm is used to process motion estimation. Experiments demonstrate that using the block match algorithm can reduce motion estimation time by 30%. PMID:26950127
NASA Astrophysics Data System (ADS)
Xin, Tiantian; Zhao, Hongying; Liu, Sijie; Wang, Lu
2015-03-01
Videos from a small Unmanned Aerial Vehicle (UAV) are always unstable because of the wobble of the vehicle and the impact of surroundings, especially when the motion has a large drifting. Electronic image stabilization aims at removing the unwanted wobble and obtaining the stable video. Then estimation of intended motion, which represents the tendency of global motion, becomes the key to image stabilization. It is usually impossible for general methods of intended motion estimation to obtain stable intended motion remaining as much information of video images and getting a path as much close to the real flying path at the same time. This paper proposed a fuzzy Kalman filtering method to estimate the intended motion to solve these problems. Comparing with traditional methods, the fuzzy Kalman filtering method can achieve better effect to estimate the intended motion.
[An improved motion estimation of medical image series via wavelet transform].
Zhang, Ying; Rao, Nini; Wang, Gang
2006-10-01
The compression of medical image series is very important in telemedicine. The motion estimation plays a key role in the video sequence compression. In this paper, an improved square-diamond search (SDS) algorithm is proposed for the motion estimation of medical image series. The improved SDS algorithm reduces the number of the searched points. This improved SDS algorithm is used in wavelet transformation field to estimate the motion of medical image series. A simulation experiment for digital subtraction angiography (DSA) is made. The experiment results show that the algorithm accuracy is higher than that of other algorithms in the motion estimation of medical image series. PMID:17121333
Motion Estimation Using the Single-row Superposition-type Planar Compound-like Eye
Cheng, Chi-Cheng; Lin, Gwo-Long
2007-01-01
How can the compound eye of insects capture the prey so accurately and quickly? This interesting issue is explored from the perspective of computer vision instead of from the viewpoint of biology. The focus is on performance evaluation of noise immunity for motion recovery using the single-row superposition-type planar compound like eye (SPCE). The SPCE owns a special symmetrical framework with tremendous amount of ommatidia inspired by compound eye of insects. The noise simulates possible ambiguity of image patterns caused by either environmental uncertainty or low resolution of CCD devices. Results of extensive simulations indicate that this special visual configuration provides excellent motion estimation performance regardless of the magnitude of the noise. Even when the noise interference is serious, the SPCE is able to dramatically reduce errors of motion recovery of the ego-translation without any type of filters. In other words, symmetrical, regular, and multiple vision sensing devices of the compound-like eye have statistical averaging advantage to suppress possible noises. This discovery lays the basic foundation in terms of engineering approaches for the secret of the compound eye of insects.
Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D
2016-06-15
The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26790540
Gaze estimation using a hybrid appearance and motion descriptor
NASA Astrophysics Data System (ADS)
Xiong, Chunshui; Huang, Lei; Liu, Changping
2015-03-01
It is a challenging problem to realize a robust and low cost gaze estimation system. Existing appearance-based and feature-based methods both have achieved impressive progress in the past several years, while their improvements are still limited by feature representation. Therefore, in this paper, we propose a novel descriptor combining eye appearance and pupil center-cornea reflections (PCCR). The hybrid gaze descriptor represents eye structure from both feature level and topology level. At the feature level, a glints-centered appearance descriptor is presented to capture intensity and contour information of eye, and a polynomial representation of normalized PCCR vector is employed to capture motion information of eyeball. At the topology level, the partial least squares is applied for feature fusion and selection. At last, sparse representation based regression is employed to map the descriptor to the point-of-gaze (PoG). Experimental results show that the proposed method achieves high accuracy and has a good tolerance to head movements.
Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
Lavoie, Benjamin R; Okoniewski, Michal; Fear, Elise C
2016-01-01
We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range. PMID:27611785
Loewe, Axel; Wilhelms, Mathias; Schmid, Jochen; Krause, Mathias J.; Fischer, Fathima; Thomas, Dierk; Scholz, Eberhard P.; Dössel, Olaf; Seemann, Gunnar
2016-01-01
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non
Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness
2015-01-01
Background Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. The lack of knowledge on the number of different strains in a quasispecies population is observed to hinder the precision of existing Viral Quasispecies Spectrum Reconstruction (QSR) methods due to the uncontrolled reconstruction of a large number of in silico false positives. In this work, we formulated a novel probabilistic method for strain richness estimation specifically targeting viral quasispecies. By using this approach we improved our recently proposed spectrum reconstruction pipeline ViQuaS to achieve higher levels of precision in reconstructed quasispecies spectra without compromising the recall rates. We also discuss how one other existing popular QSR method named ShoRAH can be improved using this new approach. Results On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. Conclusions The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors. Availability http://sourceforge.net/projects/viquas/ PMID:26678073
NASA Astrophysics Data System (ADS)
Yang, Que; Wang, Shanshan; Wang, Kai; Zhang, Chunyu; Zhang, Lu; Meng, Qingyu; Zhu, Qiudong
2015-08-01
For normal eyes without history of any ocular surgery, traditional equations for calculating intraocular lens (IOL) power, such as SRK-T, Holladay, Higis, SRK-II, et al., all were relativley accurate. However, for eyes underwent refractive surgeries, such as LASIK, or eyes diagnosed as keratoconus, these equations may cause significant postoperative refractive error, which may cause poor satisfaction after cataract surgery. Although some methods have been carried out to solve this problem, such as Hagis-L equation[1], or using preoperative data (data before LASIK) to estimate K value[2], no precise equations were available for these eyes. Here, we introduced a novel intraocular lens power estimation method by accurate ray tracing with optical design software ZEMAX. Instead of using traditional regression formula, we adopted the exact measured corneal elevation distribution, central corneal thickness, anterior chamber depth, axial length, and estimated effective lens plane as the input parameters. The calculation of intraocular lens power for a patient with keratoconus and another LASIK postoperative patient met very well with their visual capacity after cataract surgery.
NASA Astrophysics Data System (ADS)
Kasaragod, Deepa; Sugiyama, Satoshi; Ikuno, Yasushi; Alonso-Caneiro, David; Yamanari, Masahiro; Fukuda, Shinichi; Oshika, Tetsuro; Hong, Young-Joo; Li, En; Makita, Shuichi; Miura, Masahiro; Yasuno, Yoshiaki
2016-03-01
Polarization sensitive optical coherence tomography (PS-OCT) is a functional extension of OCT that contrasts the polarization properties of tissues. It has been applied to ophthalmology, cardiology, etc. Proper quantitative imaging is required for a widespread clinical utility. However, the conventional method of averaging to improve the signal to noise ratio (SNR) and the contrast of the phase retardation (or birefringence) images introduce a noise bias offset from the true value. This bias reduces the effectiveness of birefringence contrast for a quantitative study. Although coherent averaging of Jones matrix tomography has been widely utilized and has improved the image quality, the fundamental limitation of nonlinear dependency of phase retardation and birefringence to the SNR was not overcome. So the birefringence obtained by PS-OCT was still not accurate for a quantitative imaging. The nonlinear effect of SNR to phase retardation and birefringence measurement was previously formulated in detail for a Jones matrix OCT (JM-OCT) [1]. Based on this, we had developed a maximum a-posteriori (MAP) estimator and quantitative birefringence imaging was demonstrated [2]. However, this first version of estimator had a theoretical shortcoming. It did not take into account the stochastic nature of SNR of OCT signal. In this paper, we present an improved version of the MAP estimator which takes into account the stochastic property of SNR. This estimator uses a probability distribution function (PDF) of true local retardation, which is proportional to birefringence, under a specific set of measurements of the birefringence and SNR. The PDF was pre-computed by a Monte-Carlo (MC) simulation based on the mathematical model of JM-OCT before the measurement. A comparison between this new MAP estimator, our previous MAP estimator [2], and the standard mean estimator is presented. The comparisons are performed both by numerical simulation and in vivo measurements of anterior and
Regularization Based Iterative Point Match Weighting for Accurate Rigid Transformation Estimation.
Liu, Yonghuai; De Dominicis, Luigi; Wei, Baogang; Chen, Liang; Martin, Ralph R
2015-09-01
Feature extraction and matching (FEM) for 3D shapes finds numerous applications in computer graphics and vision for object modeling, retrieval, morphing, and recognition. However, unavoidable incorrect matches lead to inaccurate estimation of the transformation relating different datasets. Inspired by AdaBoost, this paper proposes a novel iterative re-weighting method to tackle the challenging problem of evaluating point matches established by typical FEM methods. Weights are used to indicate the degree of belief that each point match is correct. Our method has three key steps: (i) estimation of the underlying transformation using weighted least squares, (ii) penalty parameter estimation via minimization of the weighted variance of the matching errors, and (iii) weight re-estimation taking into account both matching errors and information learnt in previous iterations. A comparative study, based on real shapes captured by two laser scanners, shows that the proposed method outperforms four other state-of-the-art methods in terms of evaluating point matches between overlapping shapes established by two typical FEM methods, resulting in more accurate estimates of the underlying transformation. This improved transformation can be used to better initialize the iterative closest point algorithm and its variants, making 3D shape registration more likely to succeed. PMID:26357287
Hardware architecture design of a fast global motion estimation method
NASA Astrophysics Data System (ADS)
Liang, Chaobing; Sang, Hongshi; Shen, Xubang
2015-12-01
VLSI implementation of gradient-based global motion estimation (GME) faces two main challenges: irregular data access and high off-chip memory bandwidth requirement. We previously proposed a fast GME method that reduces computational complexity by choosing certain number of small patches containing corners and using them in a gradient-based framework. A hardware architecture is designed to implement this method and further reduce off-chip memory bandwidth requirement. On-chip memories are used to store coordinates of the corners and template patches, while the Gaussian pyramids of both the template and reference frame are stored in off-chip SDRAMs. By performing geometric transform only on the coordinates of the center pixel of a 3-by-3 patch in the template image, a 5-by-5 area containing the warped 3-by-3 patch in the reference image is extracted from the SDRAMs by burst read. Patched-based and burst mode data access helps to keep the off-chip memory bandwidth requirement at the minimum. Although patch size varies at different pyramid level, all patches are processed in term of 3x3 patches, so the utilization of the patch-processing circuit reaches 100%. FPGA implementation results show that the design utilizes 24,080 bits on-chip memory and for a sequence with resolution of 352x288 and frequency of 60Hz, the off-chip bandwidth requirement is only 3.96Mbyte/s, compared with 243.84Mbyte/s of the original gradient-based GME method. This design can be used in applications like video codec, video stabilization, and super-resolution, where real-time GME is a necessity and minimum memory bandwidth requirement is appreciated.
Facial motion parameter estimation and error criteria in model-based image coding
NASA Astrophysics Data System (ADS)
Liu, Yunhai; Yu, Lu; Yao, Qingdong
2000-04-01
Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.
Cancilla, John C; Díaz-Rodríguez, Pablo; Matute, Gemma; Torrecilla, José S
2015-02-14
The estimation of the density and refractive index of ternary mixtures comprising the ionic liquid (IL) 1-butyl-3-methylimidazolium tetrafluoroborate, 2-propanol, and water at a fixed temperature of 298.15 K has been attempted through artificial neural networks. The obtained results indicate that the selection of this mathematical approach was a well-suited option. The mean prediction errors obtained, after simulating with a dataset never involved in the training process of the model, were 0.050% and 0.227% for refractive index and density estimation, respectively. These accurate results, which have been attained only using the composition of the dissolutions (mass fractions), imply that, most likely, ternary mixtures similar to the one analyzed, can be easily evaluated utilizing this algorithmic tool. In addition, different chemical processes involving ILs can be monitored precisely, and furthermore, the purity of the compounds in the studied mixtures can be indirectly assessed thanks to the high accuracy of the model. PMID:25583241
Sansone, Giuseppe; Maschio, Lorenzo; Usvyat, Denis; Schütz, Martin; Karttunen, Antti
2016-01-01
The black phosphorus (black-P) crystal is formed of covalently bound layers of phosphorene stacked together by weak van der Waals interactions. An experimental measurement of the exfoliation energy of black-P is not available presently, making theoretical studies the most important source of information for the optimization of phosphorene production. Here, we provide an accurate estimate of the exfoliation energy of black-P on the basis of multilevel quantum chemical calculations, which include the periodic local Møller-Plesset perturbation theory of second order, augmented by higher-order corrections, which are evaluated with finite clusters mimicking the crystal. Very similar results are also obtained by density functional theory with the D3-version of Grimme's empirical dispersion correction. Our estimate of the exfoliation energy for black-P of -151 meV/atom is substantially larger than that of graphite, suggesting the need for different strategies to generate isolated layers for these two systems. PMID:26651397
NASA Astrophysics Data System (ADS)
Brüggemann, Matthias; Kays, Rüdiger; Springer, Paul; Erdler, Oliver
2015-03-01
In this paper we present a combination of block-matching and differential motion field estimation. We initialize the motion field using a predictive hierarchical block-matching approach. This vector field is refined by a pixel-recursive differential motion estimation method. We integrate image warping and adaptive filter kernels into the Horn and Schunck differential optical flow estimation approach to break the block structure of the initial correspondence vector fields and compute motion field updates to fulfill the smoothness constraint inside motion boundaries. The influence of occlusion areas is reduced by integrating an in-the-loop occlusion detection and adjusting the adaptive filter weights in the iteration process. We integrate the combined estimation into a hierarchical multi-scale framework. The refined motion on the current scale is upscaled and used as prediction for block-matching motion estimation on the next scale. With the proposed system we are able to combine the advantages of block-matching and differential motion estimation and achieve a dense vector field with floating point precision even for large motion.
Lamb mode selection for accurate wall loss estimation via guided wave tomography
Huthwaite, P.; Ribichini, R.; Lowe, M. J. S.; Cawley, P.
2014-02-18
Guided wave tomography offers a method to accurately quantify wall thickness losses in pipes and vessels caused by corrosion. This is achieved using ultrasonic waves transmitted over distances of approximately 1–2m, which are measured by an array of transducers and then used to reconstruct a map of wall thickness throughout the inspected region. To achieve accurate estimations of remnant wall thickness, it is vital that a suitable Lamb mode is chosen. This paper presents a detailed evaluation of the fundamental modes, S{sub 0} and A{sub 0}, which are of primary interest in guided wave tomography thickness estimates since the higher order modes do not exist at all thicknesses, to compare their performance using both numerical and experimental data while considering a range of challenging phenomena. The sensitivity of A{sub 0} to thickness variations was shown to be superior to S{sub 0}, however, the attenuation from A{sub 0} when a liquid loading was present was much higher than S{sub 0}. A{sub 0} was less sensitive to the presence of coatings on the surface of than S{sub 0}.
Lamb mode selection for accurate wall loss estimation via guided wave tomography
NASA Astrophysics Data System (ADS)
Huthwaite, P.; Ribichini, R.; Lowe, M. J. S.; Cawley, P.
2014-02-01
Guided wave tomography offers a method to accurately quantify wall thickness losses in pipes and vessels caused by corrosion. This is achieved using ultrasonic waves transmitted over distances of approximately 1-2m, which are measured by an array of transducers and then used to reconstruct a map of wall thickness throughout the inspected region. To achieve accurate estimations of remnant wall thickness, it is vital that a suitable Lamb mode is chosen. This paper presents a detailed evaluation of the fundamental modes, S0 and A0, which are of primary interest in guided wave tomography thickness estimates since the higher order modes do not exist at all thicknesses, to compare their performance using both numerical and experimental data while considering a range of challenging phenomena. The sensitivity of A0 to thickness variations was shown to be superior to S0, however, the attenuation from A0 when a liquid loading was present was much higher than S0. A0 was less sensitive to the presence of coatings on the surface of than S0.
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.
Removing the thermal component from heart rate provides an accurate VO2 estimation in forest work.
Dubé, Philippe-Antoine; Imbeau, Daniel; Dubeau, Denise; Lebel, Luc; Kolus, Ahmet
2016-05-01
Heart rate (HR) was monitored continuously in 41 forest workers performing brushcutting or tree planting work. 10-min seated rest periods were imposed during the workday to estimate the HR thermal component (ΔHRT) per Vogt et al. (1970, 1973). VO2 was measured using a portable gas analyzer during a morning submaximal step-test conducted at the work site, during a work bout over the course of the day (range: 9-74 min), and during an ensuing 10-min rest pause taken at the worksite. The VO2 estimated, from measured HR and from corrected HR (thermal component removed), were compared to VO2 measured during work and rest. Varied levels of HR thermal component (ΔHRTavg range: 0-38 bpm) originating from a wide range of ambient thermal conditions, thermal clothing insulation worn, and physical load exerted during work were observed. Using raw HR significantly overestimated measured work VO2 by 30% on average (range: 1%-64%). 74% of VO2 prediction error variance was explained by the HR thermal component. VO2 estimated from corrected HR, was not statistically different from measured VO2. Work VO2 can be estimated accurately in the presence of thermal stress using Vogt et al.'s method, which can be implemented easily by the practitioner with inexpensive instruments. PMID:26851474
Granata, Daniele; Carnevale, Vincenzo
2016-01-01
The collective behavior of a large number of degrees of freedom can be often described by a handful of variables. This observation justifies the use of dimensionality reduction approaches to model complex systems and motivates the search for a small set of relevant “collective” variables. Here, we analyze this issue by focusing on the optimal number of variable needed to capture the salient features of a generic dataset and develop a novel estimator for the intrinsic dimension (ID). By approximating geodesics with minimum distance paths on a graph, we analyze the distribution of pairwise distances around the maximum and exploit its dependency on the dimensionality to obtain an ID estimate. We show that the estimator does not depend on the shape of the intrinsic manifold and is highly accurate, even for exceedingly small sample sizes. We apply the method to several relevant datasets from image recognition databases and protein multiple sequence alignments and discuss possible interpretations for the estimated dimension in light of the correlations among input variables and of the information content of the dataset. PMID:27510265
Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation
Wan, Lin; Sun, Kelian; Ding, Qi; Cui, Yuehua; Li, Ming; Wen, Yalu; Elston, Robert C.; Qian, Minping; Fu, Wenjiang J
2009-01-01
Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms. PMID:19586935
Granata, Daniele; Carnevale, Vincenzo
2016-01-01
The collective behavior of a large number of degrees of freedom can be often described by a handful of variables. This observation justifies the use of dimensionality reduction approaches to model complex systems and motivates the search for a small set of relevant "collective" variables. Here, we analyze this issue by focusing on the optimal number of variable needed to capture the salient features of a generic dataset and develop a novel estimator for the intrinsic dimension (ID). By approximating geodesics with minimum distance paths on a graph, we analyze the distribution of pairwise distances around the maximum and exploit its dependency on the dimensionality to obtain an ID estimate. We show that the estimator does not depend on the shape of the intrinsic manifold and is highly accurate, even for exceedingly small sample sizes. We apply the method to several relevant datasets from image recognition databases and protein multiple sequence alignments and discuss possible interpretations for the estimated dimension in light of the correlations among input variables and of the information content of the dataset. PMID:27510265
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.
Methods for accurate estimation of net discharge in a tidal channel
Simpson, M.R.; Bland, R.
2000-01-01
Accurate estimates of net residual discharge in tidally affected rivers and estuaries are possible because of recently developed ultrasonic discharge measurement techniques. Previous discharge estimates using conventional mechanical current meters and methods based on stage/discharge relations or water slope measurements often yielded errors that were as great as or greater than the computed residual discharge. Ultrasonic measurement methods consist of: 1) the use of ultrasonic instruments for the measurement of a representative 'index' velocity used for in situ estimation of mean water velocity and 2) the use of the acoustic Doppler current discharge measurement system to calibrate the index velocity measurement data. Methods used to calibrate (rate) the index velocity to the channel velocity measured using the Acoustic Doppler Current Profiler are the most critical factors affecting the accuracy of net discharge estimation. The index velocity first must be related to mean channel velocity and then used to calculate instantaneous channel discharge. Finally, discharge is low-pass filtered to remove the effects of the tides. An ultrasonic velocity meter discharge-measurement site in a tidally affected region of the Sacramento-San Joaquin Rivers was used to study the accuracy of the index velocity calibration procedure. Calibration data consisting of ultrasonic velocity meter index velocity and concurrent acoustic Doppler discharge measurement data were collected during three time periods. Two sets of data were collected during a spring tide (monthly maximum tidal current) and one of data collected during a neap tide (monthly minimum tidal current). The relative magnitude of instrumental errors, acoustic Doppler discharge measurement errors, and calibration errors were evaluated. Calibration error was found to be the most significant source of error in estimating net discharge. Using a comprehensive calibration method, net discharge estimates developed from the three
MIDAS robust trend estimator for accurate GPS station velocities without step detection
NASA Astrophysics Data System (ADS)
Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien
2016-03-01
Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.
High-Resolution Tsunami Inundation Simulations Based on Accurate Estimations of Coastal Waveforms
NASA Astrophysics Data System (ADS)
Oishi, Y.; Imamura, F.; Sugawara, D.; Furumura, T.
2015-12-01
We evaluate the accuracy of high-resolution tsunami inundation simulations in detail using the actual observational data of the 2011 Tohoku-Oki earthquake (Mw9.0) and investigate the methodologies to improve the simulation accuracy.Due to the recent development of parallel computing technologies, high-resolution tsunami inundation simulations are conducted more commonly than before. To evaluate how accurately these simulations can reproduce inundation processes, we test several types of simulation configurations on a parallel computer, where we can utilize the observational data (e.g., offshore and coastal waveforms and inundation properties) that are recorded during the Tohoku-Oki earthquake.Before discussing the accuracy of inundation processes on land, the incident waves at coastal sites must be accurately estimated. However, for megathrust earthquakes, it is difficult to find the tsunami source that can provide accurate estimations of tsunami waveforms at every coastal site because of the complex spatiotemporal distribution of the source and the limitation of observation. To overcome this issue, we employ a site-specific source inversion approach that increases the estimation accuracy within a specific coastal site by applying appropriate weighting to the observational data in the inversion process.We applied our source inversion technique to the Tohoku tsunami and conducted inundation simulations using 5-m resolution digital elevation model data (DEM) for the coastal area around Miyako Bay and Sendai Bay. The estimated waveforms at the coastal wave gauges of these bays successfully agree with the observed waveforms. However, the simulations overestimate the inundation extent indicating the necessity to improve the inundation model. We find that the value of Manning's roughness coefficient should be modified from the often-used value of n = 0.025 to n = 0.033 to obtain proper results at both cities.In this presentation, the simulation results with several
NASA Technical Reports Server (NTRS)
Hosman, R. J. A. W.; Vandervaart, J. C.
1984-01-01
An experiment to investigate visual roll attitude and roll rate perception is described. The experiment was also designed to assess the improvements of perception due to cockpit motion. After the onset of the motion, subjects were to make accurate and quick estimates of the final magnitude of the roll angle step response by pressing the appropriate button of a keyboard device. The differing time-histories of roll angle, roll rate and roll acceleration caused by a step response stimulate the different perception processes related the central visual field, peripheral visual field and vestibular organs in different, yet exactly known ways. Experiments with either of the visual displays or cockpit motion and some combinations of these were run to asses the roles of the different perception processes. Results show that the differences in response time are much more pronounced than the differences in perception accuracy.
WearDY: Wearable dynamics. A prototype for human whole-body force and motion estimation
NASA Astrophysics Data System (ADS)
Latella, Claudia; Kuppuswamy, Naveen; Nori, Francesco
2016-06-01
Motion capture is a powerful tool used in a large range of applications towards human movement analysis. Although it is a well-established technique, its main limitation is the lack of dynamic information such as forces and torques during the motion capture. In this paper, we present a novel approach for human wearable dynamic (WearDY) motion capture for the simultaneous estimation of whole-body forces along with the motion. Our conceptual framework encompasses traditional passive markers based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational framework for estimating dynamic quantities originally proposed in the domain of humanoid robot control. We present preliminary experimental analysis of our framework on subjects performing a two Degrees-of-Freedom bowing task and we estimate the motion and dynamic quantities. We discuss the implication of our proposal towards the design of a novel wearable force and motion capture suit and its applications.
NASA Technical Reports Server (NTRS)
Simpson, Elizabeth C.
1989-01-01
Motion estimation is a field of great interest because of its many applications in areas such as robotics and image coding. The optic flow method is one such scheme which, although fairly accurate, is prone to error in the presence of noise. This thesis describes the use of the reduced order model Kalman filter (ROMKF) in reducing errors in displacement estimation due to degradation of the sequence. The implementation of filtering and motion estimation algorithms on the SUN workstation is also discussed. Results from preliminary testing were used to determine the degrees of freedom available for the ROMKF in the SUN software. The tests indicated that increasing the state to the left leads to slight improvement over the minimum state case. Therefore, the software uses the minimum model, with the option of adding states to the left only. The ROMKF was then used in conjunction with a hierarchical pel recursive motion estimation algorithm. Applying the ROMKF to the degraded displacements themselves generally yielded slight improvements in cases with noise degradation and noise plus blur. Filtering the images of the degraded sequence prior to motion estimation was less effective in these cases. Both methods performed badly in the case of blur alone, resulting in increased displacement errors. This is thought to be due in part to filter artifacts. Some improvements were obtained by varying the filter parameters when filtering the displacements directly. This result suggests that further study in varying filter parameters may lead to better results. The results of this thesis indicate that the ROMKF can play a part in reducing motion estimation errors from degraded sequences. However, more work needs to be done before the use of the ROMKF can be a practical solution.
Accurate estimation of the RMS emittance from single current amplifier data
Stockli, Martin P.; Welton, R.F.; Keller, R.; Letchford, A.P.; Thomae, R.W.; Thomason, J.W.G.
2002-05-31
This paper presents the SCUBEEx rms emittance analysis, a self-consistent, unbiased elliptical exclusion method, which combines traditional data-reduction methods with statistical methods to obtain accurate estimates for the rms emittance. Rather than considering individual data, the method tracks the average current density outside a well-selected, variable boundary to separate the measured beam halo from the background. The average outside current density is assumed to be part of a uniform background and not part of the particle beam. Therefore the average outside current is subtracted from the data before evaluating the rms emittance within the boundary. As the boundary area is increased, the average outside current and the inside rms emittance form plateaus when all data containing part of the particle beam are inside the boundary. These plateaus mark the smallest acceptable exclusion boundary and provide unbiased estimates for the average background and the rms emittance. Small, trendless variations within the plateaus allow for determining the uncertainties of the estimates caused by variations of the measured background outside the smallest acceptable exclusion boundary. The robustness of the method is established with complementary variations of the exclusion boundary. This paper presents a detailed comparison between traditional data reduction methods and SCUBEEx by analyzing two complementary sets of emittance data obtained with a Lawrence Berkeley National Laboratory and an ISIS H{sup -} ion source.
Schütt, Heiko H; Harmeling, Stefan; Macke, Jakob H; Wichmann, Felix A
2016-05-01
The psychometric function describes how an experimental variable, such as stimulus strength, influences the behaviour of an observer. Estimation of psychometric functions from experimental data plays a central role in fields such as psychophysics, experimental psychology and in the behavioural neurosciences. Experimental data may exhibit substantial overdispersion, which may result from non-stationarity in the behaviour of observers. Here we extend the standard binomial model which is typically used for psychometric function estimation to a beta-binomial model. We show that the use of the beta-binomial model makes it possible to determine accurate credible intervals even in data which exhibit substantial overdispersion. This goes beyond classical measures for overdispersion-goodness-of-fit-which can detect overdispersion but provide no method to do correct inference for overdispersed data. We use Bayesian inference methods for estimating the posterior distribution of the parameters of the psychometric function. Unlike previous Bayesian psychometric inference methods our software implementation-psignifit 4-performs numerical integration of the posterior within automatically determined bounds. This avoids the use of Markov chain Monte Carlo (MCMC) methods typically requiring expert knowledge. Extensive numerical tests show the validity of the approach and we discuss implications of overdispersion for experimental design. A comprehensive MATLAB toolbox implementing the method is freely available; a python implementation providing the basic capabilities is also available. PMID:27013261
SU-E-J-135: An Investigation of Ultrasound Imaging for 3D Intra-Fraction Prostate Motion Estimation
O'Shea, T; Harris, E; Bamber, J; Evans, P
2014-06-01
Purpose: This study investigates the use of a mechanically swept 3D ultrasound (US) probe to estimate intra-fraction motion of the prostate during radiation therapy using an US phantom and simulated transperineal imaging. Methods: A 3D motion platform was used to translate an US speckle phantom while simulating transperineal US imaging. Motion patterns for five representative types of prostate motion, generated from patient data previously acquired with a Calypso system, were using to move the phantom in 3D. The phantom was also implanted with fiducial markers and subsequently tracked using the CyberKnife kV x-ray system for comparison. A normalised cross correlation block matching algorithm was used to track speckle patterns in 3D and 2D US data. Motion estimation results were compared with known phantom translations. Results: Transperineal 3D US could track superior-inferior (axial) and anterior-posterior (lateral) motion to better than 0.8 mm root-mean-square error (RMSE) at a volume rate of 1.7 Hz (comparable with kV x-ray tracking RMSE). Motion estimation accuracy was poorest along the US probe's swept axis (right-left; RL; RMSE < 4.2 mm) but simple regularisation methods could be used to improve RMSE (< 2 mm). 2D US was found to be feasible for slowly varying motion (RMSE < 0.5 mm). 3D US could also allow accurate radiation beam gating with displacement thresholds of 2 mm and 5 mm exhibiting a RMSE of less than 0.5 mm. Conclusion: 2D and 3D US speckle tracking is feasible for prostate motion estimation during radiation delivery. Since RL prostate motion is small in magnitude and frequency, 2D or a hybrid (2D/3D) US imaging approach which also accounts for potential prostate rotations could be used. Regularisation methods could be used to ensure the accuracy of tracking data, making US a feasible approach for gating or tracking in standard or hypo-fractionated prostate treatments.
Schall, Mark C; Fethke, Nathan B; Chen, Howard; Gerr, Fred
2015-05-01
The performance of an inertial measurement unit (IMU) system for directly measuring thoracolumbar trunk motion was compared to that of the Lumbar Motion Monitor (LMM). Thirty-six male participants completed a simulated material handling task with both systems deployed simultaneously. Estimates of thoracolumbar trunk motion obtained with the IMU system were processed using five common methods for estimating trunk motion characteristics. Results of measurements obtained from IMUs secured to the sternum and pelvis had smaller root-mean-square differences and mean bias estimates in comparison to results obtained with the LMM than results of measurements obtained solely from a sternum mounted IMU. Fusion of IMU accelerometer measurements with IMU gyroscope and/or magnetometer measurements was observed to increase comparability to the LMM. Results suggest investigators should consider computing thoracolumbar trunk motion as a function of estimates from multiple IMUs using fusion algorithms rather than using a single accelerometer secured to the sternum in field-based studies. PMID:25683549
Precise Image-Based Motion Estimation for Autonomous Small Body Exploration
NASA Technical Reports Server (NTRS)
Johnson, Andrew E.; Matthies, Larry H.
1998-01-01
Space science and solar system exploration are driving NASA to develop an array of small body missions ranging in scope from near body flybys to complete sample return. This paper presents an algorithm for onboard motion estimation that will enable the precision guidance necessary for autonomous small body landing. Our techniques are based on automatic feature tracking between a pair of descent camera images followed by two frame motion estimation and scale recovery using laser altimetry data. The output of our algorithm is an estimate of rigid motion (attitude and position) and motion covariance between frames. This motion estimate can be passed directly to the spacecraft guidance and control system to enable rapid execution of safe and precise trajectories.
Quick and accurate estimation of the elastic constants using the minimum image method
NASA Astrophysics Data System (ADS)
Tretiakov, Konstantin V.; Wojciechowski, Krzysztof W.
2015-04-01
A method for determining the elastic properties using the minimum image method (MIM) is proposed and tested on a model system of particles interacting by the Lennard-Jones (LJ) potential. The elastic constants of the LJ system are determined in the thermodynamic limit, N → ∞, using the Monte Carlo (MC) method in the NVT and NPT ensembles. The simulation results show that when determining the elastic constants, the contribution of long-range interactions cannot be ignored, because that would lead to erroneous results. In addition, the simulations have revealed that the inclusion of further interactions of each particle with all its minimum image neighbors even in case of small systems leads to results which are very close to the values of elastic constants in the thermodynamic limit. This enables one for a quick and accurate estimation of the elastic constants using very small samples.
Zhang, Zhijun; Sahn, David J.; Song, Xubo
2014-01-01
Quantitative motion analysis from cardiac imaging is important to study the function of heart. Most of existing image-based motion estimation methods model the myocardium as an isotropically elastic continuum. We propose a novel anisotropic regularization method which enforces the transmural homogeneity of the strain along myofiber. The myofiber orientation in the end-diastolic frame is obtained by registering it with a diffusion tensor atlas. Our method is formulated in a diffeomorphic registration framework, and tested on multimodal cardiac image sequences of two subjects using 3D echocardiography and cine and tagged MRI. Results show that the estimated transformations in our method are more smooth and more accurate than those in isotropic regularization. PMID:24505703
A Simple yet Accurate Method for the Estimation of the Biovolume of Planktonic Microorganisms.
Saccà, Alessandro
2016-01-01
Determining the biomass of microbial plankton is central to the study of fluxes of energy and materials in aquatic ecosystems. This is typically accomplished by applying proper volume-to-carbon conversion factors to group-specific abundances and biovolumes. A critical step in this approach is the accurate estimation of biovolume from two-dimensional (2D) data such as those available through conventional microscopy techniques or flow-through imaging systems. This paper describes a simple yet accurate method for the assessment of the biovolume of planktonic microorganisms, which works with any image analysis system allowing for the measurement of linear distances and the estimation of the cross sectional area of an object from a 2D digital image. The proposed method is based on Archimedes' principle about the relationship between the volume of a sphere and that of a cylinder in which the sphere is inscribed, plus a coefficient of 'unellipticity' introduced here. Validation and careful evaluation of the method are provided using a variety of approaches. The new method proved to be highly precise with all convex shapes characterised by approximate rotational symmetry, and combining it with an existing method specific for highly concave or branched shapes allows covering the great majority of cases with good reliability. Thanks to its accuracy, consistency, and low resources demand, the new method can conveniently be used in substitution of any extant method designed for convex shapes, and can readily be coupled with automated cell imaging technologies, including state-of-the-art flow-through imaging devices. PMID:27195667
A Simple yet Accurate Method for the Estimation of the Biovolume of Planktonic Microorganisms
2016-01-01
Determining the biomass of microbial plankton is central to the study of fluxes of energy and materials in aquatic ecosystems. This is typically accomplished by applying proper volume-to-carbon conversion factors to group-specific abundances and biovolumes. A critical step in this approach is the accurate estimation of biovolume from two-dimensional (2D) data such as those available through conventional microscopy techniques or flow-through imaging systems. This paper describes a simple yet accurate method for the assessment of the biovolume of planktonic microorganisms, which works with any image analysis system allowing for the measurement of linear distances and the estimation of the cross sectional area of an object from a 2D digital image. The proposed method is based on Archimedes’ principle about the relationship between the volume of a sphere and that of a cylinder in which the sphere is inscribed, plus a coefficient of ‘unellipticity’ introduced here. Validation and careful evaluation of the method are provided using a variety of approaches. The new method proved to be highly precise with all convex shapes characterised by approximate rotational symmetry, and combining it with an existing method specific for highly concave or branched shapes allows covering the great majority of cases with good reliability. Thanks to its accuracy, consistency, and low resources demand, the new method can conveniently be used in substitution of any extant method designed for convex shapes, and can readily be coupled with automated cell imaging technologies, including state-of-the-art flow-through imaging devices. PMID:27195667
NASA Astrophysics Data System (ADS)
Guarnieri, A.; Milan, N.; Pirotti, F.; Vettore, A.
2011-12-01
In the automotive sector, especially in these last decade, a growing number of investigations have taken into account electronic systems to check and correct the behavior of drivers, increasing road safety. The possibility to identify with high accuracy the vehicle position in a mapping reference frame for driving directions and best-route analysis is also another topic which attracts lot of interest from the research and development sector. To reach the objective of accurate vehicle positioning and integrate response events, it is necessary to estimate time by time the position, orientation and velocity of the system. To this aim low cost GPS and MEMS (sensors can be used. In comparison to a four wheel vehicle, the dynamics of a two wheel vehicle (e.g. a scooter) feature a higher level of complexity. Indeed more degrees of freedom must be taken into account to describe the motion of the latter. For example a scooter can twist sideways, thus generating a roll angle. A slight pitch angle has to be considered as well, since wheel suspensions have a higher degree of motion with respect to four wheel vehicles. In this paper we present a method for the accurate reconstruction of the trajectory of a motorcycle ("Vespa" scooter), which can be used as alternative to the "classical" approach based on the integration of GPS and INS sensors. Position and orientation of the scooter are derived from MEMS data and images acquired by on-board digital camera. A Bayesian filter provides the means for integrating the data from MEMS-based orientation sensor and the GPS receiver.
Accurate Estimation of the Fine Layering Effect on the Wave Propagation in the Carbonate Rocks
NASA Astrophysics Data System (ADS)
Bouchaala, F.; Ali, M. Y.
2014-12-01
The attenuation caused to the seismic wave during its propagation can be mainly divided into two parts, the scattering and the intrinsic attenuation. The scattering is an elastic redistribution of the energy due to the medium heterogeneities. However the intrinsic attenuation is an inelastic phenomenon, mainly due to the fluid-grain friction during the wave passage. The intrinsic attenuation is directly related to the physical characteristics of the medium, so this parameter is very can be used for media characterization and fluid detection, which is beneficial for the oil and gas industry. The intrinsic attenuation is estimated by subtracting the scattering from the total attenuation, therefore the accuracy of the intrinsic attenuation is directly dependent on the accuracy of the total attenuation and the scattering. The total attenuation can be estimated from the recorded waves, by using in-situ methods as the spectral ratio and frequency shift methods. The scattering is estimated by assuming the heterogeneities as a succession of stacked layers, each layer is characterized by a single density and velocity. The accuracy of the scattering is strongly dependent on the layer thicknesses, especially in the case of the media composed of carbonate rocks, such media are known for their strong heterogeneity. Previous studies gave some assumptions for the choice of the layer thickness, but they showed some limitations especially in the case of carbonate rocks. In this study we established a relationship between the layer thicknesses and the frequency of the propagation, after certain mathematical development of the Generalized O'Doherty-Anstey formula. We validated this relationship through some synthetic tests and real data provided from a VSP carried out over an onshore oilfield in the emirate of Abu Dhabi in the United Arab Emirates, primarily composed of carbonate rocks. The results showed the utility of our relationship for an accurate estimation of the scattering
Accurate biopsy-needle depth estimation in limited-angle tomography using multi-view geometry
NASA Astrophysics Data System (ADS)
van der Sommen, Fons; Zinger, Sveta; de With, Peter H. N.
2016-03-01
Recently, compressed-sensing based algorithms have enabled volume reconstruction from projection images acquired over a relatively small angle (θ < 20°). These methods enable accurate depth estimation of surgical tools with respect to anatomical structures. However, they are computationally expensive and time consuming, rendering them unattractive for image-guided interventions. We propose an alternative approach for depth estimation of biopsy needles during image-guided interventions, in which we split the problem into two parts and solve them independently: needle-depth estimation and volume reconstruction. The complete proposed system consists of the previous two steps, preceded by needle extraction. First, we detect the biopsy needle in the projection images and remove it by interpolation. Next, we exploit epipolar geometry to find point-to-point correspondences in the projection images to triangulate the 3D position of the needle in the volume. Finally, we use the interpolated projection images to reconstruct the local anatomical structures and indicate the position of the needle within this volume. For validation of the algorithm, we have recorded a full CT scan of a phantom with an inserted biopsy needle. The performance of our approach ranges from a median error of 2.94 mm for an distributed viewing angle of 1° down to an error of 0.30 mm for an angle larger than 10°. Based on the results of this initial phantom study, we conclude that multi-view geometry offers an attractive alternative to time-consuming iterative methods for the depth estimation of surgical tools during C-arm-based image-guided interventions.
Can student health professionals accurately estimate alcohol content in commonly occurring drinks?
Sinclair, Julia; Searle, Emma
2016-01-01
Objectives: Correct identification of alcohol as a contributor to, or comorbidity of, many psychiatric diseases requires health professionals to be competent and confident to take an accurate alcohol history. Being able to estimate (or calculate) the alcohol content in commonly consumed drinks is a prerequisite for quantifying levels of alcohol consumption. The aim of this study was to assess this ability in medical and nursing students. Methods: A cross-sectional survey of 891 medical and nursing students across different years of training was conducted. Students were asked the alcohol content of 10 different alcoholic drinks by seeing a slide of the drink (with picture, volume and percentage of alcohol by volume) for 30 s. Results: Overall, the mean number of correctly estimated drinks (out of the 10 tested) was 2.4, increasing to just over 3 if a 10% margin of error was used. Wine and premium strength beers were underestimated by over 50% of students. Those who drank alcohol themselves, or who were further on in their clinical training, did better on the task, but overall the levels remained low. Conclusions: Knowledge of, or the ability to work out, the alcohol content of commonly consumed drinks is poor, and further research is needed to understand the reasons for this and the impact this may have on the likelihood to undertake screening or initiate treatment. PMID:27536344
Ultrasound Fetal Weight Estimation: How Accurate Are We Now Under Emergency Conditions?
Dimassi, Kaouther; Douik, Fatma; Ajroudi, Mariem; Triki, Amel; Gara, Mohamed Faouzi
2015-10-01
The primary aim of this study was to evaluate the accuracy of sonographic estimation of fetal weight when performed at due date by first-line sonographers. This was a prospective study including 500 singleton pregnancies. Ultrasound examinations were performed by residents on delivery day. Estimated fetal weights (EFWs) were calculated and compared with the corresponding birth weights. The median absolute difference between EFW and birth weight was 200 g (100-330). This difference was within ±10% in 75.2% of the cases. The median absolute percentage error was 5.53% (2.70%-10.03%). Linear regression analysis revealed a good correlation between EFW and birth weight (r = 0.79, p < 0.0001). According to Bland-Altman analysis, bias was -85.06 g (95% limits of agreement: -663.33 to 494.21). In conclusion, EFWs calculated by residents were as accurate as those calculated by experienced sonographers. Nevertheless, predictive performance remains limited, with a low sensitivity in the diagnosis of macrosomia. PMID:26164286
NASA Astrophysics Data System (ADS)
Hu, Yongxiang; Behrenfeld, Mike; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei; Zhai, Pengwang; Weimer, Carl; Winker, David; Verhappen, Carolus C.; Butler, Carolyn; Liu, Zhaoyan; Hunt, Bill; Omar, Ali; Rodier, Sharon; Lifermann, Anne; Josset, Damien; Hou, Weilin; MacDonnell, David; Rhew, Ray
2016-06-01
Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor). On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraft-based high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.
Estimation of motion parameters for a rigid body from its orthogonal projection
NASA Technical Reports Server (NTRS)
Ganguly, S.; Ghosh, B.; Tarn, T. J.; Bejczy, A. K.
1989-01-01
An estimate is presented of the motion parameters, namely, linear and angular velocities of a rigid body rotating and translating in three-dimensional-space. It is assumed that the velocities are constant and that only the orthogonal projection of the motion is observable. In particular, if (x, y, z) is the Cartesian coordinate, it is assumed that the projection of the motion on the x-y plane is observed and the information along the z coordinate is lost.
Motion estimation in the frequency domain using fuzzy c-planes clustering.
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. PMID:18255527
Discrete state model and accurate estimation of loop entropy of RNA secondary structures.
Zhang, Jian; Lin, Ming; Chen, Rong; Wang, Wei; Liang, Jie
2008-03-28
Conformational entropy makes important contribution to the stability and folding of RNA molecule, but it is challenging to either measure or compute conformational entropy associated with long loops. We develop optimized discrete k-state models of RNA backbone based on known RNA structures for computing entropy of loops, which are modeled as self-avoiding walks. To estimate entropy of hairpin, bulge, internal loop, and multibranch loop of long length (up to 50), we develop an efficient sampling method based on the sequential Monte Carlo principle. Our method considers excluded volume effect. It is general and can be applied to calculating entropy of loops with longer length and arbitrary complexity. For loops of short length, our results are in good agreement with a recent theoretical model and experimental measurement. For long loops, our estimated entropy of hairpin loops is in excellent agreement with the Jacobson-Stockmayer extrapolation model. However, for bulge loops and more complex secondary structures such as internal and multibranch loops, we find that the Jacobson-Stockmayer extrapolation model has large errors. Based on estimated entropy, we have developed empirical formulae for accurate calculation of entropy of long loops in different secondary structures. Our study on the effect of asymmetric size of loops suggest that loop entropy of internal loops is largely determined by the total loop length, and is only marginally affected by the asymmetric size of the two loops. Our finding suggests that the significant asymmetric effects of loop length in internal loops measured by experiments are likely to be partially enthalpic. Our method can be applied to develop improved energy parameters important for studying RNA stability and folding, and for predicting RNA secondary and tertiary structures. The discrete model and the program used to calculate loop entropy can be downloaded at http://gila.bioengr.uic.edu/resources/RNA.html. PMID:18376982
Estimation of muscle strength during motion recognition using multichannel surface EMG signals.
Nagata, Kentaro; Nakano, Takemi; Magatani, Kazushige; Yamada, Masafumi
2008-01-01
The use of kinesiological electromyography is established as an evaluation tool for various kinds of applied research, and surface electromyogram (SEMG) has been widely used as a control source for human interfaces such as in a myoelectric prosthetic hand (we call them 'SEMG interfaces'). It is desirable to be able to control the SEMG interfaces with the same feeling as body movement. The existing SEMG interface mainly focuses on how to achieve accurate recognition of the intended movement. However, detecting muscular strength and reduced number of electrodes are also an important factor in controlling them. Therefore, our objective in this study is the development of and the estimation method for muscular strength that maintains the accuracy of hand motion recognition to reflect the result of measured power in a controlled object. Although the muscular strength can be evaluated by various methods, in this study a grasp force index was applied to evaluate the muscular strength. In order to achieve our objective, we directed our attention to measuring all valuable information for SEMG. This work proposes an application method of two simple linear models, and the selection method of an optimal electrode configuration to use them effectively. Our system required four SEMG measurement electrodes in which locations differed for every subject depending on the individual's characteristics, and those were selected from a 96ch multi electrode using the Monte Carlo method. From the experimental results, the performance in six normal subjects indicated that the recognition rate of four motions were perfect and the grasp force estimated result fit well with the actual measurement result. PMID:19162665
Motion Detection in Diffusion MRI via Online ODF Estimation
Caruyer, Emmanuel; Aganj, Iman; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid
2013-01-01
The acquisition of high angular resolution diffusion MRI is particularly long and subject motion can become an issue. The orientation distribution function (ODF) can be reconstructed online incrementally from diffusion-weighted MRI with a Kalman filtering framework. This online reconstruction provides real-time feedback throughout the acquisition process. In this article, the Kalman filter is first adapted to the reconstruction of the ODF in constant solid angle. Then, a method called STAR (STatistical Analysis of Residuals) is presented and applied to the online detection of motion in high angular resolution diffusion images. Compared to existing techniques, this method is image based and is built on top of a Kalman filter. Therefore, it introduces no additional scan time and does not require additional hardware. The performance of STAR is tested on simulated and real data and compared to the classical generalized likelihood ratio test. Successful detection of small motion is reported (rotation under 2°) with no delay and robustness to noise. PMID:23509445
Feasibility of Measuring Mean Vertical Motion for Estimating Advection. Chapter 6
NASA Technical Reports Server (NTRS)
Vickers, Dean; Mahrt, L.
2005-01-01
Numerous recent studies calculate horizontal and vertical advection terms for budget studies of net ecosystem exchange of carbon. One potential uncertainty in such studies is the estimate of mean vertical motion. This work addresses the reliability of vertical advection estimates by contrasting the vertical motion obtained from the standard practise of measuring the vertical velocity and applying a tilt correction, to the vertical motion calculated from measurements of the horizontal divergence of the flow using a network of towers. Results are compared for three different tilt correction methods. Estimates of mean vertical motion are sensitive to the choice of tilt correction method. The short-term mean (10 to 60 minutes) vertical motion based on the horizontal divergence is more realistic compared to the estimates derived from the standard practise. The divergence shows long-term mean (days to months) sinking motion at the site, apparently due to the surface roughness change. Because all the tilt correction methods rely on the assumption that the long-term mean vertical motion is zero for a given wind direction, they fail to reproduce the vertical motion based on the divergence.
Effectiveness of external respiratory surrogates for in vivo liver motion estimation
Chang, Kai-Hsiang; Ho, Ming-Chih; Yeh, Chi-Chuan; Chen, Yu-Chien; Lian, Feng-Li; Lin, Win-Li; Yen, Jia-Yush; Chen, Yung-Yaw
2012-08-15
Purpose: Due to low frame rate of MRI and high radiation damage from fluoroscopy and CT, liver motion estimation using external respiratory surrogate signals seems to be a better approach to track liver motion in real-time for liver tumor treatments in radiotherapy and thermotherapy. This work proposes a liver motion estimation method based on external respiratory surrogate signals. Animal experiments are also conducted to investigate related issues, such as the sensor arrangement, multisensor fusion, and the effective time period. Methods: Liver motion and abdominal motion are both induced by respiration and are proved to be highly correlated. Contrary to the difficult direct measurement of the liver motion, the abdominal motion can be easily accessed. Based on this idea, our study is split into the model-fitting stage and the motion estimation stage. In the first stage, the correlation between the surrogates and the liver motion is studied and established via linear regression method. In the second stage, the liver motion is estimated by the surrogate signals with the correlation model. Animal experiments on cases of single surrogate signal, multisurrogate signals, and long-term surrogate signals are conducted and discussed to verify the practical use of this approach. Results: The results show that the best single sensor location is at the middle of the upper abdomen, while multisurrogate models are generally better than the single ones. The estimation error is reduced from 0.6 mm for the single surrogate models to 0.4 mm for the multisurrogate models. The long-term validity of the estimation models is quite satisfactory within the period of 10 min with the estimation error less than 1.4 mm. Conclusions: External respiratory surrogate signals from the abdomen motion produces good performance for liver motion estimation in real-time. Multisurrogate signals enhance estimation accuracy, and the estimation model can maintain its accuracy for at least 10 min. This
NASA Astrophysics Data System (ADS)
Khoshelham, Kourosh
2016-04-01
Registration is often a prerequisite step in processing point clouds. While planar surfaces are suitable features for registration, most of the existing plane-based registration methods rely on iterative solutions for the estimation of transformation parameters from plane correspondences. This paper presents a new closed-form solution for the estimation of a rigid motion from a set of point-plane correspondences. The role of normalization is investigated and its importance for accurate plane fitting and plane-based registration is shown. The paper also presents a thorough evaluation of the closed-form solutions and compares their performance with the iterative solution in terms of accuracy, robustness, stability and efficiency. The results suggest that the closed-form solution based on point-plane correspondences should be the method of choice in point cloud registration as it is significantly faster than the iterative solution, and performs as well as or better than the iterative solution in most situations. The normalization of the point coordinates is also recommended as an essential preprocessing step for point cloud registration. An implementation of the closed-form solutions in MATLAB is available at: http://people.eng.unimelb.edu.au/kkhoshelham/research.html#directmotion
Space-to-Space Based Relative Motion Estimation Using Direct Relative Orbit Parameters
NASA Astrophysics Data System (ADS)
Bennett, T.; Schaub, H.
There has been an increasing interest in space-based space situational awareness around satellite assets and the tracking of orbital debris. Of particular interest is the space-based tracking of objects near critical circular orbit regimes, for example near the Geostationary belt or the International Space Station. Relative orbit descriptions such as the Clohessy-Wiltshire equations describe the motion using time-varying Cartesian or curvilinear coordinates. Orbit element differences describe the unperturbed motion using constant variations of inertial orbit elements. With perturbations these only vary slowly, but can be challenging to estimate. Linearized Relative Orbit Elements (LROEs) employ invariants of the linearized relative motion, are thus constant for the unperturbed linear case, and share the benefit of the CW equations in that they directly related to space-based relative motion measurements. The variational LROE equations enable the relative orbit to be directly propagated including perturbation forces. Utilization of the invariant-inspired relative motion parameters exhibits exciting applications in relative motion sensing and control. Many methods of relative motion estimation involve the direct estimation of time-evolving position and velocity variables. Developed is an angles-only relative orbit Extended Kalman filter (EKF) navigation approach that directly estimates these nominally constant LROEs. The proposed variational equations and filtering scheme enables direct estimation of geometric parameters with clear geometric insight. Preliminary numerical simulation results demonstrate the relative orbit insight gained and speed of convergence. EKF implementations often exhibit significant sensitivity to initial conditions, however, initial results show that the LROE filter converges within fractions of an orbit with initialization errors that exceed 100 percent. The manuscript presents the invariants of motion, develops the variational equations for
Respiratory liver motion estimation and its effect on scanned proton beam therapy
NASA Astrophysics Data System (ADS)
Zhang, Ye; Boye, D.; Tanner, C.; Lomax, A. J.; Knopf, A.
2012-04-01
Proton therapy with active scanning beam delivery has significant advantages compared to conventional radiotherapy. However, so far only static targets have been treated in this way, since moving targets potentially lead to interplay effects. For 4D treatment planning, information on the target motion is needed to calculate time-resolved dose distributions. In this study, respiratory liver motion has been extracted from 4D CT data using two deformable image registration algorithms. In moderately moving patient cases (mean motion range around 6 mm), the registration error was no more than 3 mm, while it reached 7 mm for larger motions (range around 13 mm). The obtained deformation fields have then been used to calculate different time-resolved 4D treatment plans. Averaged over both motion estimations, interplay effects can increase the D5-D95 value for the clinical target volume (CTV) from 8.8% in a static plan to 23.4% when motion is considered. It has also been found that the different deformable registration algorithms can provide different motion estimations despite performing similarly for the selected landmarks, which in turn can lead to differing 4D dose distributions. Especially for single-field treatments where no motion mitigation is used, a maximum (mean) dose difference (averaged over three cases) of 32.8% (2.9%) can be observed. However, this registration ambiguity-induced uncertainty can be reduced if rescanning is applied or if the treatment plan consists of multiple fields, where the maximum (mean) difference can decrease to 15.2% (0.57%). Our results indicate the necessity to interpret 4D dose distributions for scanned proton therapy with some caution or with error bars to reflect the uncertainties resulting from the motion estimation. On the other hand, rescanning has been found to be an appropriate motion mitigation technique and, furthermore, has been shown to be a robust approach to also deal with these motion estimation uncertainties.
Goksel, Orcun; Zahiri-Azar, Reza; Salcudean, Septimiu E
2007-01-01
Motion estimation in sequences of ultrasound echo signals is essential for a wide range of applications. In time domain cross correlation, which is a common motion estimation technique, the displacements are typically not integral multiples of the sampling period. Therefore, to estimate the motion with sub-sample accuracy, 1D and 2D interpolation methods such as parabolic, cosine, and ellipsoid fitting have been introduced in the literature. In this paper, a simulation framework is presented in order to compare the performance of currently available techniques. First, the tissue deformation is modeled using the finite element method (FEM) and then the corresponding pre-/post-deformation radio-frequency (RF) signals are generated using Field II ultrasound simulation software. Using these simulated RF data of deformation, both axial and lateral tissue motion are estimated with sub-sample accuracy. The estimated displacements are then evaluated by comparing them to the known displacements computed by the FEM. This simulation approach was used to evaluate three different lateral motion estimation techniques employing (i) two separate 1D sub-sampling, (ii) two consecutive 1D sub-sampling, and (iii) 2D joint sub-sampling estimators. The estimation errors during two different tissue compression tests are presented with and without spatial filtering. Results show that RF signal processing methods involving tissue deformation can be evaluated using the proposed simulation technique, which employs accurate models. PMID:18002416
Ji, Songbai; Fan, Xiaoyao; Roberts, David W.; Hartov, Alex; Paulsen, Keith D.
2014-01-01
Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases – 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7–2.1 mm relative to those determined with the tracked stylus probe. The agreement in feature displacement
Variable disparity-motion estimation based fast three-view video coding
NASA Astrophysics Data System (ADS)
Bae, Kyung-Hoon; Kim, Seung-Cheol; Hwang, Yong Seok; Kim, Eun-Soo
2009-02-01
In this paper, variable disparity-motion estimation (VDME) based 3-view video coding is proposed. In the encoding, key-frame coding (KFC) based motion estimation and variable disparity estimation (VDE) for effectively fast three-view video encoding are processed. These proposed algorithms enhance the performance of 3-D video encoding/decoding system in terms of accuracy of disparity estimation and computational overhead. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm's PSNRs is 37.66 and 40.55 dB, and the processing time is 0.139 and 0.124 sec/frame, respectively.
Motion estimation of objects in KC-135 microgravity
NASA Technical Reports Server (NTRS)
Hewgill, Lisa
1994-01-01
The simulated microgravity environment aboard a KC-135 aircraft flying along a parabolic trajectory was used to study the ability of an autonomous space robot to grasp a freely translating and rotating object. Since the KC-135 cabin environment and the instrumentation for the Extravehicular Activity Helper/Retriever (EVAHR) do not provide a practical intertial reference frame, estimators based on the extended Kalman filter algorithm were used to model the relative translational dynamics of the KC-135 and the EVAHR. The estimator algorithms require intensive mathematical computation and therefore, i860 real-time. Estimator design, implementation concerns, and issues specific to the KC-135 environment are discussed and the architecture of the KC-135 translational state estimator is depicted.
NASA Astrophysics Data System (ADS)
Taki, Hirofumi; Yamakawa, Makoto; Shiina, Tsuyoshi; Sato, Toru
2015-07-01
High-accuracy ultrasound motion estimation has become an essential technique in blood flow imaging, elastography, and motion imaging of the heart wall. Speckle tracking has been one of the best motion estimators; however, conventional speckle-tracking methods neglect the effect of out-of-plane motion and deformation. Our proposed method assumes that the cross-correlation between a reference signal and a comparison signal depends on the spatio-temporal distance between the two signals. The proposed method uses the decrease in the cross-correlation value in a reference frame to compensate for the intrinsic error caused by out-of-plane motion and deformation without a priori information. The root-mean-square error of the estimated lateral tissue motion velocity calculated by the proposed method ranged from 6.4 to 34% of that using a conventional speckle-tracking method. This study demonstrates the high potential of the proposed method for improving the estimation of tissue motion using an ultrasound speckle-tracking method in medical diagnosis.
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.
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).
NASA Astrophysics Data System (ADS)
Mukherjee, Joyeeta Mitra; Pretorius, P. H.; Johnson, K. L.; Hutton, Brian F.; King, Michael A.
2011-03-01
In myocardial perfusion SPECT imaging patient motion during acquisition causes severe artifacts in about 5% of studies. Motion estimation strategies commonly used are a) data-driven, where the motion may be determined by registration and checking consistency with the SPECT acquisition data, and b) external surrogate-based, where the motion is obtained from a dedicated motion-tracking system. In this paper a data-driven strategy similar to a 2D-3D registration scheme with multiple views is investigated, using a partially reconstructed heart for the 3D model. 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 goal of this paper is to compare the performance of different cost-functions in quantifying consistency with the SPECT projection data in a registration-based scheme for motion estimation as the image-quality of the 3D model degrades. Six intensity-based metrics- Mean-squared difference (MSD), Mutual information (MI), Normalized Mutual information NMI), Pattern intensity (PI), normalized cross-correlation (NCC) and Entropy of the difference (EDI) were studied. 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 collimator blurring. Further the image quality of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in acquisitions of anthropomorphic phantoms and patient studies in a real clinical setting. 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 and anthropomorphic phantom acquisitions. In patient studies
Motion Estimation Utilizing Range Detection-Enhanced Visual Odometry
NASA Technical Reports Server (NTRS)
Friend, Paul Russell (Inventor); Chen, Qi (Inventor); Chang, Hong (Inventor); Morris, Daniel Dale (Inventor); Graf, Jodi Seaborn (Inventor)
2016-01-01
A motion determination system is disclosed. The system may receive a first and a second camera image from a camera, the first camera image received earlier than the second camera image. The system may identify corresponding features in the first and second camera images. The system may receive range data comprising at least one of a first and a second range data from a range detection unit, corresponding to the first and second camera images, respectively. The system may determine first positions and the second positions of the corresponding features using the first camera image and the second camera image. The first positions or the second positions may be determined by also using the range data. The system may determine a change in position of the machine based on differences between the first and second positions, and a VO-based velocity of the machine based on the determined change in position.
Motion Estimation Using the Firefly Algorithm in Ultrasonic Image Sequence of Soft Tissue
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 parameter estimation of multiple ground moving targets in multi-static passive radar systems
NASA Astrophysics Data System (ADS)
Subedi, Saurav; Zhang, Yimin D.; Amin, Moeness G.; Himed, Braham
2014-12-01
Multi-static passive radar (MPR) systems typically use narrowband signals and operate under weak signal conditions, making them difficult to reliably estimate motion parameters of ground moving targets. On the other hand, the availability of multiple spatially separated illuminators of opportunity provides a means to achieve multi-static diversity and overall signal enhancement. In this paper, we consider the problem of estimating motion parameters, including velocity and acceleration, of multiple closely located ground moving targets in a typical MPR platform with focus on weak signal conditions, where traditional time-frequency analysis-based methods become unreliable or infeasible. The underlying problem is reformulated as a sparse signal reconstruction problem in a discretized parameter search space. While the different bistatic links have distinct Doppler signatures, they share the same set of motion parameters of the ground moving targets. Therefore, such motion parameters act as a common sparse support to enable the exploitation of group sparsity-based methods for robust motion parameter estimation. This provides a means of combining signal energy from all available illuminators of opportunity and, thereby, obtaining a reliable estimation even when each individual signal is weak. Because the maximum likelihood (ML) estimation of motion parameters involves a multi-dimensional search and its performance is sensitive to target position errors, we also propose a technique that decouples the target motion parameters, yielding a two-step process that sequentially estimates the acceleration and velocity vectors with a reduced dimensionality of the parameter search space. We compare the performance of the sequential method against the ML estimation with the consideration of imperfect knowledge of the initial target positions. The Cramér-Rao bound (CRB) of the underlying parameter estimation problem is derived for a general multiple-target scenario in an MPR system
Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT
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 reconstruction 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
Imani, Farsad; Karimi Rouzbahani, Hamid Reza; Goudarzi, Mehrdad; Tarrahi, Mohammad Javad; Ebrahim Soltani, Alireza
2016-01-01
Background: During anesthesia, continuous body temperature monitoring is essential, especially in children. Anesthesia can increase the risk of loss of body temperature by three to four times. Hypothermia in children results in increased morbidity and mortality. Since the measurement points of the core body temperature are not easily accessible, near core sites, like rectum, are used. Objectives: The purpose of this study was to measure skin temperature over the carotid artery and compare it with the rectum temperature, in order to propose a model for accurate estimation of near core body temperature. Patients and Methods: Totally, 124 patients within the age range of 2 - 6 years, undergoing elective surgery, were selected. Temperature of rectum and skin over the carotid artery was measured. Then, the patients were randomly divided into two groups (each including 62 subjects), namely modeling (MG) and validation groups (VG). First, in the modeling group, the average temperature of the rectum and skin over the carotid artery were measured separately. The appropriate model was determined, according to the significance of the model’s coefficients. The obtained model was used to predict the rectum temperature in the second group (VG group). Correlation of the predicted values with the real values (the measured rectum temperature) in the second group was investigated. Also, the difference in the average values of these two groups was examined in terms of significance. Results: In the modeling group, the average rectum and carotid temperatures were 36.47 ± 0.54°C and 35.45 ± 0.62°C, respectively. The final model was obtained, as follows: Carotid temperature × 0.561 + 16.583 = Rectum temperature. The predicted value was calculated based on the regression model and then compared with the measured rectum value, which showed no significant difference (P = 0.361). Conclusions: The present study was the first research, in which rectum temperature was compared with that
Plate Motion and Crustal Deformation Estimated with Geodetic Data from the Global Positioning System
NASA Technical Reports Server (NTRS)
Argus, Donald F.; Heflin, Michael B.
1995-01-01
We use geodetic data taken over four years with the Global Positioning System (GPS) to estimate: (1) motion between six major plates and (2) motion relative to these plates of ten sites in plate boundary zones. The degree of consistency between geodetic velocities and rigid plates requires the (one-dimensional) standard errors in horizontal velocities to be approx. 2 mm/yr. Each of the 15 angular velocities describing motion between plate pairs that we estimate with GPS differs insignificantly from the corresponding angular velocity in global plate motion model NUVEL-1A, which averages motion over the past 3 m.y. The motion of the Pacific plate relative to both the Eurasian and North American plates is observed to be faster than predicted by NUVEL-1A, supporting the inference from Very Long B ase- line Interferometry (VLBI) that motion of the Pacific plate has speed up over the past few m.y. The Eurasia-North America pole of rotation is estimated to be north of NUVEL-1A, consistent with the independent hypothesis that the pole has recently migrated northward across northeast Asia to near the Lena River delta. Victoria, which lies above the main thrust at the Cascadia subduction zone, moves relative to the interior of the overriding plate at 30% of the velocity of the subducting plate, reinforcing the conclusion that the thrust there is locked beneath the continental shelf and slope.
Fast Object Motion Estimation Based on Dynamic Stixels.
Morales, Néstor; Morell, Antonio; Toledo, Jonay; Acosta, Leopoldo
2016-01-01
The stixel world is a simplification of the world in which obstacles are represented as vertical instances, called stixels, standing on a surface assumed to be planar. In this paper, previous approaches for stixel tracking are extended using a two-level scheme. In the first level, stixels are tracked by matching them between frames using a bipartite graph in which edges represent a matching cost function. Then, stixels are clustered into sets representing objects in the environment. These objects are matched based on the number of stixels paired inside them. Furthermore, a faster, but less accurate approach is proposed in which only the second level is used. Several configurations of our method are compared to an existing state-of-the-art approach to show how our methodology outperforms it in several areas, including an improvement in the quality of the depth reconstruction. PMID:27483265
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.
Scatter to volume registration for model-free respiratory motion estimation from dynamic MRIs.
Miao, S; Wang, Z J; Pan, L; Butler, J; Moran, G; Liao, R
2016-09-01
Respiratory motion is one major complicating factor in many image acquisition applications and image-guided interventions. Existing respiratory motion estimation and compensation methods typically rely on breathing motion models learned from certain training data, and therefore may not be able to effectively handle intra-subject and/or inter-subject variations of respiratory motion. In this paper, we propose a respiratory motion compensation framework that directly recovers motion fields from sparsely spaced and efficiently acquired dynamic 2-D MRIs without using a learned respiratory motion model. We present a scatter-to-volume deformable registration algorithm to register dynamic 2-D MRIs with a static 3-D MRI to recover dense deformation fields. Practical considerations and approximations are provided to solve the scatter-to-volume registration problem efficiently. The performance of the proposed method was investigated on both synthetic and real MRI datasets, and the results showed significant improvements over the state-of-art respiratory motion modeling methods. We also demonstrated a potential application of the proposed method on MRI-based motion corrected PET imaging using hybrid PET/MRI. PMID:27180910
Crop area estimation based on remotely-sensed data with an accurate but costly subsample
NASA Technical Reports Server (NTRS)
Gunst, R. F.
1983-01-01
Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.
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.
Hidden Markov Modeling for Weigh-In-Motion Estimation
Abercrombie, Robert K; Ferragut, Erik M; Boone, Shane
2012-01-01
This paper describes a hidden Markov model to assist in the weight measurement error that arises from complex vehicle oscillations of a system of discrete masses. Present reduction of oscillations is by a smooth, flat, level approach and constant, slow speed in a straight line. The model uses this inherent variability to assist in determining the true total weight and individual axle weights of a vehicle. The weight distribution dynamics of a generic moving vehicle were simulated. The model estimation converged to within 1% of the true mass for simulated data. The computational demands of this method, while much greater than simple averages, took only seconds to run on a desktop computer.
Zhu, Meihua; Ashraf, Muhammad; Broberg, Craig S.; Sahn, David J.; Song, Xubo
2014-01-01
Purpose: Quantitative analysis of right ventricle (RV) motion is important for study of the mechanism of congenital and acquired diseases. Unlike left ventricle (LV), motion estimation of RV is more difficult because of its complex shape and thin myocardium. Although attempts of finite element models on MR images and speckle tracking on echocardiography have shown promising results on RV strain analysis, these methods can be improved since the temporal smoothness of the motion is not considered. Methods: The authors have proposed a temporally diffeomorphic motion estimation method in which a spatiotemporal transformation is estimated by optimization of a registration energy functional of the velocity field in their earlier work. The proposed motion estimation method is a fully automatic process for general image sequences. The authors apply the method by combining with a semiautomatic myocardium segmentation method to the RV strain analysis of three-dimensional (3D) echocardiographic sequences of five open-chest pigs under different steady states. Results: The authors compare the peak two-point strains derived by their method with those estimated from the sonomicrometry, the results show that they have high correlation. The motion of the right ventricular free wall is studied by using segmental strains. The baseline sequence results show that the segmental strains in their methods are consistent with results obtained by other image modalities such as MRI. The image sequences of pacing steady states show that segments with the largest strain variation coincide with the pacing sites. Conclusions: The high correlation of the peak two-point strains of their method and sonomicrometry under different steady states demonstrates that their RV motion estimation has high accuracy. The closeness of the segmental strain of their method to those from MRI shows the feasibility of their method in the study of RV function by using 3D echocardiography. The strain analysis of the
Cardiac motion estimation by joint alignment of tagged MRI sequences.
Oubel, E; De Craene, M; Hero, A O; Pourmorteza, A; Huguet, M; Avegliano, G; Bijnens, B H; Frangi, A F
2012-01-01
Image registration has been proposed as an automatic method for recovering cardiac displacement fields from tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the α-entropy (H(α)) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p<0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presents an interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging. PMID:22000567
Motion-induced phase error estimation and correction in 3D diffusion tensor imaging.
Van, Anh T; Hernando, Diego; Sutton, Bradley P
2011-11-01
A multishot data acquisition strategy is one way to mitigate B0 distortion and T2∗ blurring for high-resolution diffusion-weighted magnetic resonance imaging experiments. However, different object motions that take place during different shots cause phase inconsistencies in the data, leading to significant image artifacts. This work proposes a maximum likelihood estimation and k-space correction of motion-induced phase errors in 3D multishot diffusion tensor imaging. The proposed error estimation is robust, unbiased, and approaches the Cramer-Rao lower bound. For rigid body motion, the proposed correction effectively removes motion-induced phase errors regardless of the k-space trajectory used and gives comparable performance to the more computationally expensive 3D iterative nonlinear phase error correction method. The method has been extended to handle multichannel data collected using phased-array coils. Simulation and in vivo data are shown to demonstrate the performance of the method. PMID:21652284
Comparing C- and L-band SAR images for sea ice motion estimation
NASA Astrophysics Data System (ADS)
Lehtiranta, J.; Siiriä, S.; Karvonen, J.
2015-02-01
Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.
Self-reconfigurable approach for computation-intensive motion estimation algorithm in H.264/AVC
NASA Astrophysics Data System (ADS)
Lee, Jooheung; Ryu, Chul; Kim, Soontae
2012-04-01
The authors propose a self-reconfigurable approach to perform H.264/AVC variable block size motion estimation computation on field-programmable gate arrays. We use dynamic partial reconfiguration to change the hardware architecture of motion estimation during run-time. Hardware adaptation to meet the real-time computing requirements for the given video resolutions and frame rates is performed through self-reconfiguration. An embedded processor is used to control the reconfiguration of partial bitstreams of motion estimation adaptively. The partial bitstreams for different motion estimation computation arrays are compressed using LZSS algorithm. On-chip BlockRAM is used as a cache to pre-store the partial bitstreams so that run-time reconfiguration can be fully utilized. We designed a hardware module to fetch the pre-stored partial bitstream from BlockRAM to an internal configuration access port. Comparison results show that our motion estimation architecture improves toward data reuse, and the memory bandwidth overhead is reduced. Using our self-reconfigurable platform, the reconfiguration overhead can be removed and 367 MB/sec reconfiguration rate can be achieved. The experimental results show that the external memory accesses are reduced by 62.4% and it can operate at a frequency of 91.7 MHz.
Aagaard, B; Brocher, T; Dreger, D; Frankel, A; Graves, R; Harmsen, S; Hartzell, S; Larsen, S; McCandless, K; Nilsson, S; Petersson, N A; Rodgers, A; Sjogreen, B; Tkalcic, H; Zoback, M L
2007-02-09
We estimate the ground motions produced by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sites throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.
High-resolution Neogene and Quaternary estimates of Nubia-Eurasia-North America Plate motion
NASA Astrophysics Data System (ADS)
DeMets, C.; Iaffaldano, G.; Merkouriev, S.
2015-10-01
Reconstructions of the history of convergence between the Nubia and Eurasia plates constitute an important part of a broader framework for understanding deformation in the Mediterranean region and the closing of the Mediterranean Basin. Herein, we combine high-resolution reconstructions of Eurasia-North America and Nubia-North America Plate motions to determine rotations that describe Nubia-Eurasia Plate motion at ˜1 Myr intervals for the past 20 Myr. We apply trans-dimensional hierarchical Bayesian inference to the Eurasia-North America and Nubia-North America rotation sequences in order to reduce noise in the newly estimated Nubia-Eurasia rotations. The noise-reduced rotation sequences for the Eurasia-North America and Nubia-North America Plate pairs describe remarkably similar kinematic histories since 20 Ma, consisting of relatively steady seafloor spreading from 20 to 8 Ma, ˜20 per cent opening-rate slowdowns at 8-6.5 Ma, and steady plate motion from ˜7 Ma to the present. Our newly estimated Nubia-Eurasia rotations predict that convergence across the central Mediterranean Sea slowed by ˜50 per cent and rotated anticlockwise after ˜25 Ma until 13 Ma. Motion since 13 Ma has remained relatively steady. An absence of evidence for a significant change in motion immediately before or during the Messinian Salinity Crisis at 6.3-5.6 Ma argues against a change in plate motion as its causative factor. The detachment of the Arabian Peninsula from Africa at 30-24 Ma may have triggered the convergence rate slowdown before 13 Ma; however, published reconstructions of Nubia-Eurasia motion for times before 20 Ma are too widely spaced to determine with confidence whether the two are correlated. A significant discrepancy between our new estimates of Nubia-Eurasia motion during the past few Myr and geodetic estimates calls for further investigation.
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.
NASA Astrophysics Data System (ADS)
McClelland, Jamie
It is often difficult or impossible to directly monitor the respiratory motion of the tumour and other internal anatomy during RT treatment. Implanted markers can be used, but this involves an invasive procedure and has a number of other associated risks and problems. An alternative option is to use a correspondence model. This models the relationship between a respiratory surrogate signal(s), such as spirometry or the displacement of the skin surface, and the motion of the internal anatomy. Such a model allows the internal motion to be estimated from the surrogate signal(s), which can be easily monitored during RT treatment. The correspondence model is constructed prior to RT treatment. Imaging data is simultaneously acquired with the surrogate signal(s), and the internal motion is measured from the imaging data, e.g. using deformable image registration. A correspondence model is then fit relating the internal motion to the surrogate signal(s). This can then be used during treatment to estimate the internal motion from the surrogate signal(s). This chapter reviews the most popular correspondence models that have been used in the literature, as well as the different surrogate signals, types of imaging data used to measure the internal motion, and fitting methods used to fit the correspondence model to the data.
Motion estimation and compensation based on region-constrained warping prediction
NASA Astrophysics Data System (ADS)
Chang, Dong-Il; Sung, Joon H.; Kim, Jeong K.; Lee, ChoongWoong
1998-01-01
The visually annoying artifacts resulting form block matching algorithm (BMA), blocky artifacts, become noticeable in applications for low bit rates. Warping prediction (WP) based schemes can remove the blocky artifacts of BMA successfully, but they also produce severe prediction errors around the boundaries of moving objects. Since the errors around the boundaries of objects are visually sensitive, they may sometimes look more annoying than blocky artifacts. The lack of ability of modeling motion discontinuities is the major reason of the errors from WP. Motion discontinuities usually exist in practical video sequences, so that it is required to develop a more reliable motion estimation and usually exist in practical video sequences, so that it is required to develop a more reliable motion estimation and compensation scheme for low bit rate applications. In this paper, we propose a new WP scheme, named region constrained warping prediction (RCWP), which places motion discontinuities according to the segmentation results. In RCWP, there is mutual dependency between estimated motion field and segmentation mask. Because of the mutual dependency, an iterative refinement process is also introduced. Experimental results have shown that the proposed algorithm can provide much better subjective and objective performance than the BMA and the conventional warping prediction.
Edge preserving motion estimation with occlusions correction for assisted 2D to 3D conversion
NASA Astrophysics Data System (ADS)
Pohl, Petr; Sirotenko, Michael; Tolstaya, Ekaterina; Bucha, Victor
2014-02-01
In this article we propose high quality motion estimation based on variational optical flow formulation with non-local regularization term. To improve motion in occlusion areas we introduce occlusion motion inpainting based on 3-frame motion clustering. Variational formulation of optical flow proved itself to be very successful, however a global optimization of cost function can be time consuming. To achieve acceptable computation times we adapted the algorithm that optimizes convex function in coarse-to-fine pyramid strategy and is suitable for modern GPU hardware implementation. We also introduced two simplifications of cost function that significantly decrease computation time with acceptable decrease of quality. For motion clustering based motion inpaitning in occlusion areas we introduce effective method of occlusion aware joint 3-frame motion clustering using RANSAC algorithm. Occlusion areas are inpainted by motion model taken from cluster that shows consistency in opposite direction. We tested our algorithm on Middlebury optical flow benchmark, where we scored around 20th position, but being one of the fastest method near the top. We also successfully used this algorithm in semi-automatic 2D to 3D conversion tool for spatio-temporal background inpainting, automatic adaptive key frame detection and key points tracking.
Probabilistic estimates of the seismic ground-motion hazard in western Saudi Arabia
Thenhaus, P.C.; Algermissen, S.T.; Perkins, D.M.; Hanson, S.L.; Diment, W.H.
1989-01-01
Estimates of seismic horizontal ground acceleration and velocity having a 90 percent probability of nonexceedance in 100 yr in western Saudi Arabia indicate the highest relative levels of ground motion are expected in regions neighboring the Gulf of Aqaba and North Yemen. Estimated ground motions within the Arabia Shield are relatively low; whereas the central and northern coastal plan regions are characterized by intermediate-level ground-motion values that are governed by far-field effects of earthquakes in the central Red Sea Rift. The seismic hazard estimates were derived from regional seismic source zones that are based on interpretation relating potential seismic activity to the Precambrian through Tertiary structural framework of the region.
Improvement of sub-pixel global motion estimation in UAV image stabilization
NASA Astrophysics Data System (ADS)
Li, Yingjuan; Ji, Ming; He, Junfeng; Zhen, Kang; Yang, Yizhou; Chen, Ying
2016-01-01
Global motion estimation within frames is very important in the UAV(unmanned aerial vehicle) image stabilization system. A fast algorithm based on phase correlation and image down-sampling in sub-pixel was proposed. First, down-sampling of the two frames to quantitatively reduce calculate data. Then, take the method based of phase correlation to realize the global motion estimation in integer-pixel. When it calculated out, chooses the overlapped area of the two frames and interpolated them with zero, then adopts the method based on phase correlation to achieve the global motion estimation in sub-pixel. At last, weighted calculate the result in integer-pixel and the result in sub-pixel, the global motion displacement in sub-pixel of the two images will be calculated out. Experimental results show that, using the proposed algorithm can not only achieve good robustness to the influence of noise, illumination and partially sheltered but also improve the accuracy of motion estimation and efficiency of computing significantly.
NASA Astrophysics Data System (ADS)
Baumgartner, Stefan V.; Krieger, Gerhard
2013-03-01
In the paper ship position and motion parameter estimation results obtained with the German TerraSARX/ TanDEM-X radar satellite formation are presented. For processing a novel ground moving target indication (GMTI) algorithm applicable for dual-platform SAR systems separated by a large along-track baseline is used [1]. This algorithm enables high accurate estimation of the true geographical positions, the velocities and moving directions of the detected ships and land moving targets without the need of a priori knowledge. The algorithm is verified and evaluated using SAR data and ground truth reference data acquired during the commissioning phase of TanDEMX in 2010. We have already presented the first results in [2][3]. The current paper is an extension.
NASA Astrophysics Data System (ADS)
Hosseinyalamdary, S.; Yilmaz, A.
2014-11-01
In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas-Kanade optical flow estimation. The same approach has been used in the KLT tracker and it has been shown that using epipolar geometry constraint can improve the KLT tracker. It is recommended that the epipolar geometry constraint is used in advanced variational optical flow estimation methods.
Head motion during MRI acquisition reduces gray matter volume and thickness estimates.
Reuter, Martin; Tisdall, M Dylan; Qureshi, Abid; Buckner, Randy L; van der Kouwe, André J W; Fischl, Bruce
2015-02-15
Imaging biomarkers derived from magnetic resonance imaging (MRI) data are used to quantify normal development, disease, and the effects of disease-modifying therapies. However, motion during image acquisition introduces image artifacts that, in turn, affect derived markers. A systematic effect can be problematic since factors of interest like age, disease, and treatment are often correlated with both a structural change and the amount of head motion in the scanner, confounding the ability to distinguish biology from artifact. Here we evaluate the effect of head motion during image acquisition on morphometric estimates of structures in the human brain using several popular image analysis software packages (FreeSurfer 5.3, VBM8 SPM, and FSL Siena 5.0.7). Within-session repeated T1-weighted MRIs were collected on 12 healthy volunteers while performing different motion tasks, including two still scans. We show that volume and thickness estimates of the cortical gray matter are biased by head motion with an average apparent volume loss of roughly 0.7%/mm/min of subject motion. Effects vary across regions and remain significant after excluding scans that fail a rigorous quality check. In view of these results, the interpretation of reported morphometric effects of movement disorders or other conditions with increased motion tendency may need to be revisited: effects may be overestimated when not controlling for head motion. Furthermore, drug studies with hypnotic, sedative, tranquilizing, or neuromuscular-blocking substances may contain spurious "effects" of reduced atrophy or brain growth simply because they affect motion distinct from true effects of the disease or therapeutic process. PMID:25498430
Head Motion during MRI Acquisition Reduces Gray Matter Volume and Thickness Estimates
Reuter, Martin; Tisdall, M. Dylan; Qureshi, Abid; Buckner, Randy L.; van der Kouwe, André J. W.; Fischl, Bruce
2014-01-01
Imaging biomarkers derived from magnetic resonance imaging (MRI) data are used to quantify normal development, disease, and the effects of disease-modifying therapies. However, motion during image acquisition introduces image artifacts that, in turn, affect derived markers. A systematic effect can be problematic since factors of interest like age, disease, and treatment are often correlated with both a structural change and the amount of head motion in the scanner, confounding the ability to distinguish biology from artifact. Here we evaluate the effect of head motion during image acquisition on morphometric estimates of structures in the human brain using several popular image analysis software packages (FreeSurfer 5.3, VBM8 SPM, and FSL Siena 5.0.7). Within-session repeated T1-weighted MRIs were collected on 12 healthy volunteers while performing different motion tasks, including two still scans. We show that volume and thickness estimates of the cortical gray matter are biased by head motion with an average apparent volume loss of roughly 0.7%/mm/min of subject motion. Effects vary across regions and remain significant after excluding scans that fail a rigorous quality check. In view of these results, the interpretation of reported morphometric effects of movement disorders or other conditions with increased motion tendency may need to be revisited: effects may be overestimated when not controlling for head motion. Furthermore, drug studies with hypnotic, sedative, tranquillizing, or neuromuscular-blocking substances may contain spurious “effects” of reduced atrophy or brain growth simply because they affect motion distinct from true effects of the disease or therapeutic process. PMID:25498430
Dynamics of subjective discomfort in motion sickness as measured with a magnitude estimation method
NASA Technical Reports Server (NTRS)
Bock, O. L.; Oman, C. M.
1982-01-01
Eight subjects, wearing left-right vision reversing goggles, executed sequences of controlled active head movements to provoke motion sickness. Head movement sequences were interspaced with periods of eye closure and no head movement to permit partial remission of symptoms between sequences. Subjects reported the level of discomfort experienced by using a magnitude estimation technique derived from Stevens' (1957) ratio scaling method. Using this approach, we demonstrated that the time course of subjective discomfort exhibits a profile, similar in all our subjects, characterized by both fast and slow response components. The potential usefulness of magnitude estimation for research on the dynamic properties of the mechanism generating motion sickness symptoms is discussed.
NASA Astrophysics Data System (ADS)
Chung, Vera Y. Y.; Bergmann, Neil W.
1998-12-01
This paper presents how to implement the block-matching motion estimation algorithm efficiently by Field Programmable Gate Arrays (FPGAs) based Custom Computer Machine (CCM) for video compression. The SPACE2 Custom Computer board consists of up to eight Xilinx XC6216 fine- grain, sea-of-gate FPGA chips. The results show that two Xilinx XC6216 FPGA can perform at 960 MOPs, hence the real- time full-search motion estimation encoder can be easily implemented by our SPACE2 CCM system.
NASA Astrophysics Data System (ADS)
Grasso, Robert J.; Russo, Leonard P.; Barrett, John L.; Odhner, Jefferson E.; Egbert, Paul I.
2007-09-01
BAE Systems presents the results of a program to model the performance of Raman LIDAR systems for the remote detection of atmospheric gases, air polluting hydrocarbons, chemical and biological weapons, and other molecular species of interest. Our model, which integrates remote Raman spectroscopy, 2D and 3D LADAR, and USAF atmospheric propagation codes permits accurate determination of the performance of a Raman LIDAR system. The very high predictive performance accuracy of our model is due to the very accurate calculation of the differential scattering cross section for the specie of interest at user selected wavelengths. We show excellent correlation of our calculated cross section data, used in our model, with experimental data obtained from both laboratory measurements and the published literature. In addition, the use of standard USAF atmospheric models provides very accurate determination of the atmospheric extinction at both the excitation and Raman shifted wavelengths.
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%. PMID:24808604
Shared Sensory Estimates for Human Motion Perception and Pursuit Eye Movements
Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio
2015-01-01
Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. PMID:26041919
Shared sensory estimates for human motion perception and pursuit eye movements.
Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio; Osborne, Leslie C
2015-06-01
Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. PMID:26041919
On-line 3D motion estimation using low resolution MRI
NASA Astrophysics Data System (ADS)
Glitzner, M.; de Senneville, B. Denis; Lagendijk, J. J. W.; Raaymakers, B. W.; Crijns, S. P. M.
2015-08-01
Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible. MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information. In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated. Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with {{≤ft(2.5 \\text{mm}\\right)}3} voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. {{≤ft(5 \\text{mm}\\right)}3} . In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality.
Bi-fluorescence imaging for estimating accurately the nuclear condition of Rhizoctonia spp.
Technology Transfer Automated Retrieval System (TEKTRAN)
Aims: To simplify the determination of the nuclear condition of the pathogenic Rhizoctonia, which currently needs to be performed either using two fluorescent dyes, thus is more costly and time-consuming, or using only one fluorescent dye, and thus less accurate. Methods and Results: A red primary ...
Shen, Yan; Lou, Shuqin; Wang, Xin
2014-03-20
The evaluation accuracy of real optical properties of photonic crystal fibers (PCFs) is determined by the accurate extraction of air hole edges from microscope images of cross sections of practical PCFs. A novel estimation method of point spread function (PSF) based on Kalman filter is presented to rebuild the micrograph image of the PCF cross-section and thus evaluate real optical properties for practical PCFs. Through tests on both artificially degraded images and microscope images of cross sections of practical PCFs, we prove that the proposed method can achieve more accurate PSF estimation and lower PSF variance than the traditional Bayesian estimation method, and thus also reduce the defocus effect. With this method, we rebuild the microscope images of two kinds of commercial PCFs produced by Crystal Fiber and analyze the real optical properties of these PCFs. Numerical results are in accord with the product parameters. PMID:24663461
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.
Technical note: tree truthing: how accurate are substrate estimates in primate field studies?
Bezanson, Michelle; Watts, Sean M; Jobin, Matthew J
2012-04-01
Field studies of primate positional behavior typically rely on ground-level estimates of substrate size, angle, and canopy location. These estimates potentially influence the identification of positional modes by the observer recording behaviors. In this study we aim to test ground-level estimates against direct measurements of support angles, diameters, and canopy heights in trees at La Suerte Biological Research Station in Costa Rica. After reviewing methods that have been used by past researchers, we provide data collected within trees that are compared to estimates obtained from the ground. We climbed five trees and measured 20 supports. Four observers collected measurements of each support from different locations on the ground. Diameter estimates varied from the direct tree measures by 0-28 cm (Mean: 5.44 ± 4.55). Substrate angles varied by 1-55° (Mean: 14.76 ± 14.02). Height in the tree was best estimated using a clinometer as estimates with a two-meter reference placed by the tree varied by 3-11 meters (Mean: 5.31 ± 2.44). We determined that the best support size estimates were those generated relative to the size of the focal animal and divided into broader categories. Support angles were best estimated in 5° increments and then checked using a Haglöf clinometer in combination with a laser pointer. We conclude that three major factors should be addressed when estimating support features: observer error (e.g., experience and distance from the target), support deformity, and how support size and angle influence the positional mode selected by a primate individual. individual. PMID:22371099
Heaton, T.H.; Hartzell, S.H.
1989-01-01
Strong ground motions are estimated for the Pacific Northwest assuming that large shallow earthquakes, similar to those experienced in southern Chile, southwestern Japan, and Colombia, may also occur on the Cascadia subduction zone. Fifty-six strong motion recordings for twenty-five subduction earthquakes of Ms???7.0 are used to estimate the response spectra that may result from earthquakes Mw<81/4. Large variations in observed ground motion levels are noted for a given site distance and earthquake magnitude. When compared with motions that have been observed in the western United States, large subduction zone earthquakes produce relatively large ground motions at surprisingly large distances. An earthquake similar to the 22 May 1960 Chilean earthquake (Mw 9.5) is the largest event that is considered to be plausible for the Cascadia subduction zone. This event has a moment which is two orders of magnitude larger than the largest earthquake for which we have strong motion records. The empirical Green's function technique is used to synthesize strong ground motions for such giant earthquakes. Observed teleseismic P-waveforms from giant earthquakes are also modeled using the empirical Green's function technique in order to constrain model parameters. The teleseismic modeling in the period range of 1.0 to 50 sec strongly suggests that fewer Green's functions should be randomly summed than is required to match the long-period moments of giant earthquakes. It appears that a large portion of the moment associated with giant earthquakes occurs at very long periods that are outside the frequency band of interest for strong ground motions. Nevertheless, the occurrence of a giant earthquake in the Pacific Northwest may produce quite strong shaking over a very large region. ?? 1989 Birkha??user Verlag.
NASA Technical Reports Server (NTRS)
Lichten, S. M.
1991-01-01
Data from the Global Positioning System (GPS) were used to determine precise polar motion estimates. Conservatively calculated formal errors of the GPS least squares solution are approx. 10 cm. The GPS estimates agree with independently determined polar motion values from very long baseline interferometry (VLBI) at the 5 cm level. The data were obtained from a partial constellation of GPS satellites and from a sparse worldwide distribution of ground stations. The accuracy of the GPS estimates should continue to improve as more satellites and ground receivers become operational, and eventually a near real time GPS capability should be available. Because the GPS data are obtained and processed independently from the large radio antennas at the Deep Space Network (DSN), GPS estimation could provide very precise measurements of Earth orientation for calibration of deep space tracking data and could significantly relieve the ever growing burden on the DSN radio telescopes to provide Earth platform calibrations.
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
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
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
NASA Astrophysics Data System (ADS)
Dhou, S.; Hurwitz, M.; Mishra, P.; Cai, W.; Rottmann, J.; Li, R.; Williams, C.; Wagar, M.; Berbeco, R.; Ionascu, D.; Lewis, J. H.
2015-05-01
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 developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based 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.
Pan, Xiaochang; Liu, Ke; Shao, Jinghua; Gao, Jing; Huang, Lingyun; Bai, Jing; Luo, Jianwen
2015-11-01
Tissue motion estimation is widely used in many ultrasound techniques. Rigid-model-based and nonrigid-modelbased methods are two main groups of space-domain methods of tissue motion estimation. The affine model is one of the commonly used nonrigid models. The performances of the rigid model and affine model have not been compared on ultrasound RF signals, which have been demonstrated to obtain higher accuracy, precision, and resolution in motion estimation compared with B-mode images. In this study, three methods, i.e., the normalized cross-correlation method with rigid model (NCC), the optical flow method with rigid model (OFRM), and the optical flow method with affine model (OFAM), are compared using ultrasound RF signals, rather than the B-mode images used in previous studies. Simulations, phantom, and in vivo experiments are conducted to make the comparison. In the simulations, the root-mean-square errors (RMSEs) of axial and lateral displacements and strains are used to assess the accuracy of motion estimation, and the elastographic signal-tonoise ratio (SNRe) and contrast-to-noise ratio (CNRe) are used to evaluate the quality of axial strain images. In the phantom experiments, the registration error between the pre- and postdeformation RF signals, as well as the SNRe and CNRe of axial strain images, are utilized as the evaluation criteria. In the in vivo experiments, the registration error is used to evaluate the estimation performance. The results show that the affinemodel- based method (i.e., OFAM) obtains the lowest RMSE or registration error and the highest SNRe and CNRe among all the methods. The affine model is demonstrated to be superior to the rigid model in motion estimation based on RF signals. PMID:26559623
NASA Astrophysics Data System (ADS)
Wang, Chao; Ji, Ming; Zhang, Ying; Jiang, Wentao; Lu, Xiaoyan; Wang, Jiaoying; Yang, Heng
2016-01-01
The electronic image stabilization technology based on improved optical-flow motion vector estimation technique can effectively improve the non normal shift, such as jitter, rotation and so on. Firstly, the ORB features are extracted from the image, a set of regions are built on these features; Secondly, the optical-flow vector is computed in the feature regions, in order to reduce the computational complexity, the multi resolution strategy of Pyramid is used to calculate the motion vector of the frame; Finally, qualitative and quantitative analysis of the effect of the algorithm is carried out. The results show that the proposed algorithm has better stability compared with image stabilization based on the traditional optical-flow motion vector estimation method.
NASA Astrophysics Data System (ADS)
Faccioli, E.; Lagomarsino, S.; Demartinos, K.; Smerzini, C.; Stuppazzini, M.; Vanini, M.; Villani, M.; Smolka, A.; Allmann, A.
2010-05-01
In this contribution we investigate the advantages and/or limitations of integrating standard approaches for damage and loss estimation procedures with synthetic data from 3D large scale numerical simulations, capable to reproduce the coupling of near-fault conditions, including the focal mechanism of the source and directivity effects, and complex geological configurations, such as deep alluvial basins or irregular topographic profiles. As a matter of fact, the largest portion of damage and losses during a major earthquake occur in near-field conditions, where earthquake ground motion is typically poorly constrained based on standard attenuation relationships, that may not be based on a sufficiently detailed description both of the seismic source and of the local geological conditions. As a case study we decided to use a scenario earthquake of Mw 6.4 occurring in the town of Sulmona, Italy along the active Mount Morrone fault. The area, located only 40 km south of l'Aquila, was selected in the frame of the Italian Project S2 (DPC-INGV 2007-2009) thanks to the amount of geological and seismological information that allowed on one hand to perform near-fault 3D earthquake ground motion simulations, and, on the other side, a reliable quantification of the potential damage thanks to the accurate data characterizing the building stocks. The 3D simulations have been carried out through a high performance Spectral Elements tool, namely GeoELSE (http://geoelse.stru.polimi.it), designed to study linear, non-linear viscoelastic and viscoplastic wave propagation analyses in large-scale earth models, including the seismic source, the propagation path, the local near-surface geology, and, if needed, the interaction with man-made structures . The parallel implementation of the code GeoELSE ensures a reasonable computer time to resolve tens of million of degrees of freedom up to 2.5 Hz. Damage and loss evaluations based on the results of numerical simulations are compared with
Automatic motion estimation using flow parameters for dynamic contrast-enhanced ultrasound
NASA Astrophysics Data System (ADS)
Barrois, Guillaume; Coron, Alain; Lucidarme, Olivier; Bridal, S. Lori
2015-03-01
Dynamic contrast-enhanced ultrasound (DCE-US) sequences are subject to motion which can disturb functional flow quantification. This can make estimated parameters more variable or unreliable. Methods that compensate for motion are therefore desirable. The most commonly used motion correction techniques in DCE-US register the images in the sequence with respect to a user-selected reference image. However, this image may not include all features that are representative of the whole sequence. Moreover, image-based registration neglects pertinent, functional-flow information contained in the DCE-US sequence. An operator-free method is proposed that combines the motion estimation and flow-parameter quantification (M/Q method) in a single mathematical framework. This method is based on a realistic multiplicative model of the DCE-US noise. By computing likelihood in this model, motion and flow parameters are both estimated iteratively. First, the maximization is accomplished by estimating functional and motion parameters. Then, a final registration based on a non-parametric temporal smoothing of the sequence is performed. This method is compared to a conventional (mutual information) registration method where all the images of the sequence are registered with respect to a reference image chosen by an expert. The two methods are evaluated on simulated sequences and DCE-US sequences acquired in patients (N = 15). The M/Q method demonstrates significantly (p < 0.05) lower Dice coefficients and Hausdorff distance than the conventional method on the simulated data sets. On the in vivo sequences analysed, the M/Q methods outperformed the conventional method in terms of mean Dice and Hausdorff distance on 80% of the sequences, and in terms of standard deviation of Dice and Hausdorff distance on 87% of the sequences.
NASA Astrophysics Data System (ADS)
Lim, Seng Hooi; Nisar, Humaira; Yap, Vooi Voon; Shim, Seong-O.
2015-11-01
Electroencephalography (EEG) is the signal generated by electrical activity in the human brain. EEG topographic maps (topo-maps) give an idea of brain activation. Functional connectivity helps to find functionally integrated relationship between spatially separated brain regions. Brain connectivity can be measured by several methods. The classical methods calculate the coherence and correlation of the signal. We have developed an algorithm to map functional neural connectivity in the brain by using a full search block matching motion estimation algorithm. We have used oddball paradigm to examine the flow of activation across brain lobes for a specific activity. In the first step, the EEG signal is converted into topo-maps. The flow of activation between consecutive frames is tracked using full search block motion estimation, which appears in the form of motion vectors. In the second step, vector median filtering is used to obtain a smooth motion field by removing the unwanted noise. For each topo-map, several activation paths are tracked across various brain lobes. We have also developed correlation activity maps by following the correlation coefficient paths between electrodes. These paths are selected when the correlation coefficient between electrodes is >70%. We have compared the motion estimation path with the correlation coefficient activation maps. The tracked paths obtained by using motion estimation and correlation give very similar results. The inter-subject comparison shows that four out of five subjects tracked path involves all four (occipital, temporal, parietal, frontal) brain lobes for the same stimuli. The intra-subject analysis shows that three out of five subjects show different tracked lobes for different stimuli.
Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery
Rottmann, Joerg; Berbeco, Ross; Keall, Paul
2013-09-15
Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient.Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps.Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm.Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.
Predictive-based cross line for fast motion estimation in MPEG-4 videos
NASA Astrophysics Data System (ADS)
Fang, Hui; Jiang, Jianmin
2004-05-01
Block-based motion estimation is widely used in the field of video compression due to its feature of high processing speed and competitive compression efficiency. In the chain of compression operations, however, motion estimation still remains to be the most time-consuming process. As a result, any improvement in fast motion estimation will enable practical applications of MPEG techniques more efficient and more sustainable in terms of both processing speed and computing cost. To meet the requirements of real-time compression of videos and image sequences, such as video conferencing, remote video surveillance and video phones etc., we propose a new search algorithm and achieve fast motion estimation for MPEG compression standards based on existing algorithm developments. To evaluate the proposed algorithm, we adopted MPEG-4 and the prediction line search algorithm as the benchmarks to design the experiments. Their performances are measured by: (i) reconstructed video quality; (ii) processing time. The results reveal that the proposed algorithm provides a competitive alternative to the existing prediction line search algorithm. In comparison with MPEG-4, the proposed algorithm illustrates significant advantages in terms of processing speed and video quality.
Accurate state estimation for a hydraulic actuator via a SDRE nonlinear filter
NASA Astrophysics Data System (ADS)
Strano, Salvatore; Terzo, Mario
2016-06-01
The state estimation in hydraulic actuators is a fundamental tool for the detection of faults or a valid alternative to the installation of sensors. Due to the hard nonlinearities that characterize the hydraulic actuators, the performances of the linear/linearization based techniques for the state estimation are strongly limited. In order to overcome these limits, this paper focuses on an alternative nonlinear estimation method based on the State-Dependent-Riccati-Equation (SDRE). The technique is able to fully take into account the system nonlinearities and the measurement noise. A fifth order nonlinear model is derived and employed for the synthesis of the estimator. Simulations and experimental tests have been conducted and comparisons with the largely used Extended Kalman Filter (EKF) are illustrated. The results show the effectiveness of the SDRE based technique for applications characterized by not negligible nonlinearities such as dead zone and frictions.
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
Archuleta, R.; Bonilla, F.; Doroudian, M.; Elgamal, A.; Hueze, F.
2000-06-06
This is the second report on the UC/CLC Campus Earthquake Program (CEP), concerning the estimation of exposure of the U.C. Santa Barbara campus to strong earthquake motions (Phase 2 study). The main results of Phase 1 are summarized in the current report. This document describes the studies which resulted in site-specific strong motion estimates for the Engineering I site, and discusses the potential impact of these motions on the building. The main elements of Phase 2 are: (1) determining that a M 6.8 earthquake on the North Channel-Pitas Point (NCPP) fault is the largest threat to the campus. Its recurrence interval is estimated at 350 to 525 years; (2) recording earthquakes from that fault on March 23, 1998 (M 3.2) and May 14, 1999 (M 3.2) at the new UCSB seismic station; (3) using these recordings as empirical Green's functions (EGF) in scenario earthquake simulations which provided strong motion estimates (seismic syntheses) at a depth of 74 m under the Engineering I site; 240 such simulations were performed, each with the same seismic moment, but giving a broad range of motions that were analyzed for their mean and standard deviation; (4) laboratory testing, at U.C. Berkeley and U.C. Los Angeles, of soil samples obtained from drilling at the UCSB station site, to determine their response to earthquake-type loading; (5) performing nonlinear soil dynamic calculations, using the soil properties determined in-situ and in the laboratory, to calculate the surface strong motions resulting from the seismic syntheses at depth; (6) comparing these CEP-generated strong motion estimates to acceleration spectra based on the application of state-of-practice methods - the IBC 2000 code, UBC 97 code and Probabilistic Seismic Hazard Analysis (PSHA), this comparison will be used to formulate design-basis spectra for future buildings and retrofits at UCSB; and (7) comparing the response of the Engineering I building to the CEP ground motion estimates and to the design
FAST TRACK COMMUNICATION Accurate estimate of α variation and isotope shift parameters in Na and Mg+
NASA Astrophysics Data System (ADS)
Sahoo, B. K.
2010-12-01
We present accurate calculations of fine-structure constant variation coefficients and isotope shifts in Na and Mg+ using the relativistic coupled-cluster method. In our approach, we are able to discover the roles of various correlation effects explicitly to all orders in these calculations. Most of the results, especially for the excited states, are reported for the first time. It is possible to ascertain suitable anchor and probe lines for the studies of possible variation in the fine-structure constant by using the above results in the considered systems.
Accurate State Estimation and Tracking of a Non-Cooperative Target Vehicle
NASA Technical Reports Server (NTRS)
Thienel, Julie K.; Sanner, Robert M.
2006-01-01
Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.
Precision Pointing Control to and Accurate Target Estimation of a Non-Cooperative Vehicle
NASA Technical Reports Server (NTRS)
VanEepoel, John; Thienel, Julie; Sanner, Robert M.
2006-01-01
In 2004, NASA began investigating a robotic servicing mission for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates in order to achieve capture by the proposed Hubble Robotic Vehicle (HRV), but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST. To generalize the situation, HST is the target vehicle and HRV is the chaser. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a control scheme. Non-cooperative in this context relates to the target vehicle no longer having the ability to maintain attitude control or transmit attitude knowledge.
A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system
Metcalf, Jessica L; Wegener Parfrey, Laura; Gonzalez, Antonio; Lauber, Christian L; Knights, Dan; Ackermann, Gail; Humphrey, Gregory C; Gebert, Matthew J; Van Treuren, Will; Berg-Lyons, Donna; Keepers, Kyle; Guo, Yan; Bullard, James; Fierer, Noah; Carter, David O; Knight, Rob
2013-01-01
Establishing the time since death is critical in every death investigation, yet existing techniques are susceptible to a range of errors and biases. For example, forensic entomology is widely used to assess the postmortem interval (PMI), but errors can range from days to months. Microbes may provide a novel method for estimating PMI that avoids many of these limitations. Here we show that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days. Our results provide a detailed understanding of bacterial and microbial eukaryotic ecology within a decomposing corpse system and suggest that microbial community data can be developed into a forensic tool for estimating PMI. DOI: http://dx.doi.org/10.7554/eLife.01104.001 PMID:24137541
Strong Earthquake Motion Estimates for Three Sites on the U.C. Riverside Campus
Archuleta, R.; Elgamal, A.; Heuze, F.; Lai, T.; Lavalle, D.; Lawrence, B.; Liu, P.C.; Matesic, L.; Park, S.; Riemar, M.; Steidl, J.; Vucetic, M.; Wagoner, J.; Yang, Z.
2000-11-01
The approach of the Campus Earthquake Program (CEP) is to combine the substantial expertise that exists within the UC system in geology, seismology, and geotechnical engineering, to estimate the earthquake strong motion exposure of UC facilities. These estimates draw upon recent advances in hazard assessment, seismic wave propagation modeling in rocks and soils, and dynamic soil testing. The UC campuses currently chosen for application of our integrated methodology are Riverside, San Diego, and Santa Barbara. The procedure starts with the identification of possible earthquake sources in the region and the determination of the most critical fault(s) related to earthquake exposure of the campus. Combined geological, geophysical, and geotechnical studies are then conducted to characterize each campus with specific focus on the location of particular target buildings of special interest to the campus administrators. We drill and geophysically log deep boreholes next to the target structure, to provide direct in-situ measurements of subsurface material properties, and to install uphole and downhole 3-component seismic sensors capable of recording both weak and strong motions. The boreholes provide access below the soil layers, to deeper materials that have relatively high seismic shear-wave velocities. Analyses of conjugate downhole and uphole records provide a basis for optimizing the representation of the low-strain response of the sites. Earthquake rupture scenarios of identified causative faults are combined with the earthquake records and with nonlinear soil models to provide site-specific estimates of strong motions at the selected target locations. The predicted ground motions are shared with the UC consultants, so that they can be used as input to the dynamic analysis of the buildings. Thus, for each campus targeted by the CEP project, the strong motion studies consist of two phases, Phase 1--initial source and site characterization, drilling, geophysical
Strong earthquake motion estimates for three sites on the U.C. San Diego campus
Day, S; Doroudian, M; Elgamal, A; Gonzales, S; Heuze, F; Lai, T; Minster, B; Oglesby, D; Riemer, M; Vernon, F; Vucetic, M; Wagoner, J; Yang, Z
2002-05-07
The approach of the Campus Earthquake Program (CEP) is to combine the substantial expertise that exists within the UC system in geology, seismology, and geotechnical engineering, to estimate the earthquake strong motion exposure of UC facilities. These estimates draw upon recent advances in hazard assessment, seismic wave propagation modeling in rocks and soils, and dynamic soil testing. The UC campuses currently chosen for application of our integrated methodology are Riverside, San Diego, and Santa Barbara. The procedure starts with the identification of possible earthquake sources in the region and the determination of the most critical fault(s) related to earthquake exposure of the campus. Combined geological, geophysical, and geotechnical studies are then conducted to characterize each campus with specific focus on the location of particular target buildings of special interest to the campus administrators. We drill, sample, and geophysically log deep boreholes next to the target structure, to provide direct in-situ measurements of subsurface material properties, and to install uphole and downhole 3-component seismic sensors capable of recording both weak and strong motions. The boreholes provide access below the soil layers, to deeper materials that have relatively high seismic shear-wave velocities. Analyses of conjugate downhole and uphole records provide a basis for optimizing the representation of the low-strain response of the sites. Earthquake rupture scenarios of identified causative faults are combined with the earthquake records and with nonlinear soil models to provide site-specific estimates of strong motions at the selected target locations. The predicted ground motions are shared with the UC consultants, so that they can be used as input to the dynamic analysis of the buildings. Thus, for each campus targeted by the CEP project, the strong motion studies consist of two phases, Phase 1--initial source and site characterization, drilling
Fast and accurate probability density estimation in large high dimensional astronomical datasets
NASA Astrophysics Data System (ADS)
Gupta, Pramod; Connolly, Andrew J.; Gardner, Jeffrey P.
2015-01-01
Astronomical surveys will generate measurements of hundreds of attributes (e.g. color, size, shape) on hundreds of millions of sources. Analyzing these large, high dimensional data sets will require efficient algorithms for data analysis. An example of this is probability density estimation that is at the heart of many classification problems such as the separation of stars and quasars based on their colors. Popular density estimation techniques use binning or kernel density estimation. Kernel density estimation has a small memory footprint but often requires large computational resources. Binning has small computational requirements but usually binning is implemented with multi-dimensional arrays which leads to memory requirements which scale exponentially with the number of dimensions. Hence both techniques do not scale well to large data sets in high dimensions. We present an alternative approach of binning implemented with hash tables (BASH tables). This approach uses the sparseness of data in the high dimensional space to ensure that the memory requirements are small. However hashing requires some extra computation so a priori it is not clear if the reduction in memory requirements will lead to increased computational requirements. Through an implementation of BASH tables in C++ we show that the additional computational requirements of hashing are negligible. Hence this approach has small memory and computational requirements. We apply our density estimation technique to photometric selection of quasars using non-parametric Bayesian classification and show that the accuracy of the classification is same as the accuracy of earlier approaches. Since the BASH table approach is one to three orders of magnitude faster than the earlier approaches it may be useful in various other applications of density estimation in astrostatistics.
Volcanic explosion clouds - Density, temperature, and particle content estimates from cloud motion
NASA Technical Reports Server (NTRS)
Wilson, L.; Self, S.
1980-01-01
Photographic records of 10 vulcanian eruption clouds produced during the 1978 eruption of Fuego Volcano in Guatemala have been analyzed to determine cloud velocity and acceleration at successive stages of expansion. Cloud motion is controlled by air drag (dominant during early, high-speed motion) and buoyancy (dominant during late motion when the cloud is convecting slowly). Cloud densities in the range 0.6 to 1.2 times that of the surrounding atmosphere were obtained by fitting equations of motion for two common cloud shapes (spheres and vertical cylinders) to the observed motions. Analysis of the heat budget of a cloud permits an estimate of cloud temperature and particle weight fraction to be made from the density. Model results suggest that clouds generally reached temperatures within 10 K of that of the surrounding air within 10 seconds of formation and that dense particle weight fractions were less than 2% by this time. The maximum sizes of dense particles supported by motion in the convecting clouds range from 140 to 1700 microns.