Near-Optimal Tracking Control of Mobile Robots Via Receding-Horizon Dual Heuristic Programming.

PubMed

Lian, Chuanqiang; Xu, Xin; Chen, Hong; He, Haibo

2016-11-01

Trajectory tracking control of wheeled mobile robots (WMRs) has been an important research topic in control theory and robotics. Although various tracking control methods with stability have been developed for WMRs, it is still difficult to design optimal or near-optimal tracking controller under uncertainties and disturbances. In this paper, a near-optimal tracking control method is presented for WMRs based on receding-horizon dual heuristic programming (RHDHP). In the proposed method, a backstepping kinematic controller is designed to generate desired velocity profiles and the receding horizon strategy is used to decompose the infinite-horizon optimal control problem into a series of finite-horizon optimal control problems. In each horizon, a closed-loop tracking control policy is successively updated using a class of approximate dynamic programming algorithms called finite-horizon dual heuristic programming (DHP). The convergence property of the proposed method is analyzed and it is shown that the tracking control system based on RHDHP is asymptotically stable by using the Lyapunov approach. Simulation results on three tracking control problems demonstrate that the proposed method has improved control performance when compared with conventional model predictive control (MPC) and DHP. It is also illustrated that the proposed method has lower computational burden than conventional MPC, which is very beneficial for real-time tracking control.

Homography-based multiple-camera person-tracking

NASA Astrophysics Data System (ADS)

Turk, Matthew R.

2009-01-01

Multiple video cameras are cheaply installed overlooking an area of interest. While computerized single-camera tracking is well-developed, multiple-camera tracking is a relatively new problem. The main multi-camera problem is to give the same tracking label to all projections of a real-world target. This is called the consistent labelling problem. Khan and Shah (2003) introduced a method to use field of view lines to perform multiple-camera tracking. The method creates inter-camera meta-target associations when objects enter at the scene edges. They also said that a plane-induced homography could be used for tracking, but this method was not well described. Their homography-based system would not work if targets use only one side of a camera to enter the scene. This paper overcomes this limitation and fully describes a practical homography-based tracker. A new method to find the feet feature is introduced. The method works especially well if the camera is tilted, when using the bottom centre of the target's bounding-box would produce inaccurate results. The new method is more accurate than the bounding-box method even when the camera is not tilted. Next, a method is presented that uses a series of corresponding point pairs "dropped" by oblivious, live human targets to find a plane-induced homography. The point pairs are created by tracking the feet locations of moving targets that were associated using the field of view line method. Finally, a homography-based multiple-camera tracking algorithm is introduced. Rules governing when to create the homography are specified. The algorithm ensures that homography-based tracking only starts after a non-degenerate homography is found. The method works when not all four field of view lines are discoverable; only one line needs to be found to use the algorithm. To initialize the system, the operator must specify pairs of overlapping cameras. Aside from that, the algorithm is fully automatic and uses the natural movement of live targets for training. No calibration is required. Testing shows that the algorithm performs very well in real-world sequences. The consistent labelling problem is solved, even for targets that appear via in-scene entrances. Full occlusions are handled. Although implemented in Matlab, the multiple-camera tracking system runs at eight frames per second. A faster implementation would be suitable for real-world use at typical video frame rates.

A RSSI-based parameter tracking strategy for constrained position localization

NASA Astrophysics Data System (ADS)

Du, Jinze; Diouris, Jean-François; Wang, Yide

2017-12-01

In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

NASA Astrophysics Data System (ADS)

Khayat, Omid; Afarideh, Hossein

2013-04-01

Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

NASA Astrophysics Data System (ADS)

Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

2016-05-01

The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

Image-based tracking of the suturing needle during laparoscopic interventions

NASA Astrophysics Data System (ADS)

Speidel, S.; Kroehnert, A.; Bodenstedt, S.; Kenngott, H.; Müller-Stich, B.; Dillmann, R.

2015-03-01

One of the most complex and difficult tasks for surgeons during minimally invasive interventions is suturing. A prerequisite to assist the suturing process is the tracking of the needle. The endoscopic images provide a rich source of information which can be used for needle tracking. In this paper, we present an image-based method for markerless needle tracking. The method uses a color-based and geometry-based segmentation to detect the needle. Once an initial needle detection is obtained, a region of interest enclosing the extracted needle contour is passed on to a reduced segmentation. It is evaluated with in vivo images from da Vinci interventions.

Efficient physics-based tracking of heart surface motion for beating heart surgery robotic systems.

PubMed

Bogatyrenko, Evgeniya; Pompey, Pascal; Hanebeck, Uwe D

2011-05-01

Tracking of beating heart motion in a robotic surgery system is required for complex cardiovascular interventions. A heart surface motion tracking method is developed, including a stochastic physics-based heart surface model and an efficient reconstruction algorithm. The algorithm uses the constraints provided by the model that exploits the physical characteristics of the heart. The main advantage of the model is that it is more realistic than most standard heart models. Additionally, no explicit matching between the measurements and the model is required. The application of meshless methods significantly reduces the complexity of physics-based tracking. Based on the stochastic physical model of the heart surface, this approach considers the motion of the intervention area and is robust to occlusions and reflections. The tracking algorithm is evaluated in simulations and experiments on an artificial heart. Providing higher accuracy than the standard model-based methods, it successfully copes with occlusions and provides high performance even when all measurements are not available. Combining the physical and stochastic description of the heart surface motion ensures physically correct and accurate prediction. Automatic initialization of the physics-based cardiac motion tracking enables system evaluation in a clinical environment.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

Design of a real-time system of moving ship tracking on-board based on FPGA in remote sensing images

NASA Astrophysics Data System (ADS)

Yang, Tie-jun; Zhang, Shen; Zhou, Guo-qing; Jiang, Chuan-xian

2015-12-01

With the broad attention of countries in the areas of sea transportation and trade safety, the requirements of efficiency and accuracy of moving ship tracking are becoming higher. Therefore, a systematic design of moving ship tracking onboard based on FPGA is proposed, which uses the Adaptive Inter Frame Difference (AIFD) method to track a ship with different speed. For the Frame Difference method (FD) is simple but the amount of computation is very large, it is suitable for the use of FPGA to implement in parallel. But Frame Intervals (FIs) of the traditional FD method are fixed, and in remote sensing images, a ship looks very small (depicted by only dozens of pixels) and moves slowly. By applying invariant FIs, the accuracy of FD for moving ship tracking is not satisfactory and the calculation is highly redundant. So we use the adaptation of FD based on adaptive extraction of key frames for moving ship tracking. A FPGA development board of Xilinx Kintex-7 series is used for simulation. The experiments show that compared with the traditional FD method, the proposed one can achieve higher accuracy of moving ship tracking, and can meet the requirement of real-time tracking in high image resolution.

Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966

Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

A Novel Passive Tracking Scheme Exploiting Geometric and Intercept Theorems

PubMed Central

Zhou, Biao; Sun, Chao; Ahn, Deockhyeon; Kim, Youngok

2018-01-01

Passive tracking aims to track targets without assistant devices, that is, device-free targets. Passive tracking based on Radio Frequency (RF) Tomography in wireless sensor networks has recently been addressed as an emerging field. The passive tracking scheme using geometric theorems (GTs) is one of the most popular RF Tomography schemes, because the GT-based method can effectively mitigate the demand for a high density of wireless nodes. In the GT-based tracking scheme, the tracking scenario is considered as a two-dimensional geometric topology and then geometric theorems are applied to estimate crossing points (CPs) of the device-free target on line-of-sight links (LOSLs), which reveal the target’s trajectory information in a discrete form. In this paper, we review existing GT-based tracking schemes, and then propose a novel passive tracking scheme by exploiting the Intercept Theorem (IT). To create an IT-based CP estimation scheme available in the noisy non-parallel LOSL situation, we develop the equal-ratio traverse (ERT) method. Finally, we analyze properties of three GT-based tracking algorithms and the performance of these schemes is evaluated experimentally under various trajectories, node densities, and noisy topologies. Analysis of experimental results shows that tracking schemes exploiting geometric theorems can achieve remarkable positioning accuracy even under rather a low density of wireless nodes. Moreover, the proposed IT scheme can provide generally finer tracking accuracy under even lower node density and noisier topologies, in comparison to other schemes. PMID:29562621

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Real time markerless motion tracking using linked kinematic chains

DOEpatents

Luck, Jason P [Arvada, CO; Small, Daniel E [Albuquerque, NM

2007-08-14

A markerless method is described for tracking the motion of subjects in a three dimensional environment using a model based on linked kinematic chains. The invention is suitable for tracking robotic, animal or human subjects in real-time using a single computer with inexpensive video equipment, and does not require the use of markers or specialized clothing. A simple model of rigid linked segments is constructed of the subject and tracked using three dimensional volumetric data collected by a multiple camera video imaging system. A physics based method is then used to compute forces to align the model with subsequent volumetric data sets in real-time. The method is able to handle occlusion of segments and accommodates joint limits, velocity constraints, and collision constraints and provides for error recovery. The method further provides for elimination of singularities in Jacobian based calculations, which has been problematic in alternative methods.

Evaluation of the repeatability and reproducibility of a suite of qPCR based microbial source tracking methods

EPA Science Inventory

Many PCR-based methods for microbial source tracking (MST) have been developed and validated within individual research laboratories. Inter-laboratory validation of these methods, however, has been minimal, and the effects of protocol standardization regimes have not been thor...

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

PubMed

Zhao, Zijian; Voros, Sandrine; Weng, Ying; Chang, Faliang; Li, Ruijian

2017-12-01

Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

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

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less

Tri-linear interpolation-based cerebral white matter fiber imaging

PubMed Central

Jiang, Shan; Zhang, Pengfei; Han, Tong; Liu, Weihua; Liu, Meixia

2013-01-01

Diffusion tensor imaging is a unique method to visualize white matter fibers three-dimensionally, non-invasively and in vivo, and therefore it is an important tool for observing and researching neural regeneration. Different diffusion tensor imaging-based fiber tracking methods have been already investigated, but making the computing faster, fiber tracking longer and smoother and the details shown clearer are needed to be improved for clinical applications. This study proposed a new fiber tracking strategy based on tri-linear interpolation. We selected a patient with acute infarction of the right basal ganglia and designed experiments based on either the tri-linear interpolation algorithm or tensorline algorithm. Fiber tracking in the same regions of interest (genu of the corpus callosum) was performed separately. The validity of the tri-linear interpolation algorithm was verified by quantitative analysis, and its feasibility in clinical diagnosis was confirmed by the contrast between tracking results and the disease condition of the patient as well as the actual brain anatomy. Statistical results showed that the maximum length and average length of the white matter fibers tracked by the tri-linear interpolation algorithm were significantly longer. The tracking images of the fibers indicated that this method can obtain smoother tracked fibers, more obvious orientation and clearer details. Tracking fiber abnormalities are in good agreement with the actual condition of patients, and tracking displayed fibers that passed though the corpus callosum, which was consistent with the anatomical structures of the brain. Therefore, the tri-linear interpolation algorithm can achieve a clear, anatomically correct and reliable tracking result. PMID:25206524

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

PubMed

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

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

Rao, Nageswara S.; Liu, Qiang

We consider tracking of a target with elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the known ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in the lossy long-haul tracking environment.

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

PubMed Central

Qin, Lei; Snoussi, Hichem; Abdallah, Fahed

2014-01-01

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

A joint tracking method for NSCC based on WLS algorithm

NASA Astrophysics Data System (ADS)

Luo, Ruidan; Xu, Ying; Yuan, Hong

2017-12-01

Navigation signal based on compound carrier (NSCC), has the flexible multi-carrier scheme and various scheme parameters configuration, which enables it to possess significant efficiency of navigation augmentation in terms of spectral efficiency, tracking accuracy, multipath mitigation capability and anti-jamming reduction compared with legacy navigation signals. Meanwhile, the typical scheme characteristics can provide auxiliary information for signal synchronism algorithm design. This paper, based on the characteristics of NSCC, proposed a kind of joint tracking method utilizing Weighted Least Square (WLS) algorithm. In this method, the LS algorithm is employed to jointly estimate each sub-carrier frequency shift with the frequency-Doppler linear relationship, by utilizing the known sub-carrier frequency. Besides, the weighting matrix is set adaptively according to the sub-carrier power to ensure the estimation accuracy. Both the theory analysis and simulation results illustrate that the tracking accuracy and sensitivity of this method outperforms the single-carrier algorithm with lower SNR.

Towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study

NASA Astrophysics Data System (ADS)

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

2013-03-01

Automatic co-alignment of optical and virtual colonoscopy images can supplement traditional endoscopic procedures, by providing more complete information of clinical value to the gastroenterologist. In this work, we present a comparative analysis of our optical flow based technique for colonoscopy tracking, in relation to current state of the art methods, in terms of tracking accuracy, system stability, and computational efficiency. Our optical-flow based colonoscopy tracking algorithm starts with computing multi-scale dense and sparse optical flow fields to measure image displacements. Camera motion parameters are then determined from optical flow fields by employing a Focus of Expansion (FOE) constrained egomotion estimation scheme. We analyze the design choices involved in the three major components of our algorithm: dense optical flow, sparse optical flow, and egomotion estimation. Brox's optical flow method,1 due to its high accuracy, was used to compare and evaluate our multi-scale dense optical flow scheme. SIFT6 and Harris-affine features7 were used to assess the accuracy of the multi-scale sparse optical flow, because of their wide use in tracking applications; the FOE-constrained egomotion estimation was compared with collinear,2 image deformation10 and image derivative4 based egomotion estimation methods, to understand the stability of our tracking system. Two virtual colonoscopy (VC) image sequences were used in the study, since the exact camera parameters(for each frame) were known; dense optical flow results indicated that Brox's method was superior to multi-scale dense optical flow in estimating camera rotational velocities, but the final tracking errors were comparable, viz., 6mm vs. 8mm after the VC camera traveled 110mm. Our approach was computationally more efficient, averaging 7.2 sec. vs. 38 sec. per frame. SIFT and Harris affine features resulted in tracking errors of up to 70mm, while our sparse optical flow error was 6mm. The comparison among egomotion estimation algorithms showed that our FOE-constrained egomotion estimation method achieved the optimal balance between tracking accuracy and robustness. The comparative study demonstrated that our optical-flow based colonoscopy tracking algorithm maintains good accuracy and stability for routine use in clinical practice.

Comparison of probabilistic and deterministic fiber tracking of cranial nerves.

PubMed

Zolal, Amir; Sobottka, Stephan B; Podlesek, Dino; Linn, Jennifer; Rieger, Bernhard; Juratli, Tareq A; Schackert, Gabriele; Kitzler, Hagen H

2017-09-01

OBJECTIVE The depiction of cranial nerves (CNs) using diffusion tensor imaging (DTI) is of great interest in skull base tumor surgery and DTI used with deterministic tracking methods has been reported previously. However, there are still no good methods usable for the elimination of noise from the resulting depictions. The authors have hypothesized that probabilistic tracking could lead to more accurate results, because it more efficiently extracts information from the underlying data. Moreover, the authors have adapted a previously described technique for noise elimination using gradual threshold increases to probabilistic tracking. To evaluate the utility of this new approach, a comparison is provided with this work between the gradual threshold increase method in probabilistic and deterministic tracking of CNs. METHODS Both tracking methods were used to depict CNs II, III, V, and the VII+VIII bundle. Depiction of 240 CNs was attempted with each of the above methods in 30 healthy subjects, which were obtained from 2 public databases: the Kirby repository (KR) and Human Connectome Project (HCP). Elimination of erroneous fibers was attempted by gradually increasing the respective thresholds (fractional anisotropy [FA] and probabilistic index of connectivity [PICo]). The results were compared with predefined ground truth images based on corresponding anatomical scans. Two label overlap measures (false-positive error and Dice similarity coefficient) were used to evaluate the success of both methods in depicting the CN. Moreover, the differences between these parameters obtained from the KR and HCP (with higher angular resolution) databases were evaluated. Additionally, visualization of 10 CNs in 5 clinical cases was attempted with both methods and evaluated by comparing the depictions with intraoperative findings. RESULTS Maximum Dice similarity coefficients were significantly higher with probabilistic tracking (p < 0.001; Wilcoxon signed-rank test). The false-positive error of the last obtained depiction was also significantly lower in probabilistic than in deterministic tracking (p < 0.001). The HCP data yielded significantly better results in terms of the Dice coefficient in probabilistic tracking (p < 0.001, Mann-Whitney U-test) and in deterministic tracking (p = 0.02). The false-positive errors were smaller in HCP data in deterministic tracking (p < 0.001) and showed a strong trend toward significance in probabilistic tracking (p = 0.06). In the clinical cases, the probabilistic method visualized 7 of 10 attempted CNs accurately, compared with 3 correct depictions with deterministic tracking. CONCLUSIONS High angular resolution DTI scans are preferable for the DTI-based depiction of the cranial nerves. Probabilistic tracking with a gradual PICo threshold increase is more effective for this task than the previously described deterministic tracking with a gradual FA threshold increase and might represent a method that is useful for depicting cranial nerves with DTI since it eliminates the erroneous fibers without manual intervention.

Online two-stage association method for robust multiple people tracking

NASA Astrophysics Data System (ADS)

Lv, Jingqin; Fang, Jiangxiong; Yang, Jie

2011-07-01

Robust multiple people tracking is very important for many applications. It is a challenging problem due to occlusion and interaction in crowded scenarios. This paper proposes an online two-stage association method for robust multiple people tracking. In the first stage, short tracklets generated by linking people detection responses grow longer by particle filter based tracking, with detection confidence embedded into the observation model. And, an examining scheme runs at each frame for the reliability of tracking. In the second stage, multiple people tracking is achieved by linking tracklets to generate trajectories. An online tracklet association method is proposed to solve the linking problem, which allows applications in time-critical scenarios. This method is evaluated on the popular CAVIAR dataset. The experimental results show that our two-stage method is robust.

Computer-aided target tracking in motion analysis studies

NASA Astrophysics Data System (ADS)

Burdick, Dominic C.; Marcuse, M. L.; Mislan, J. D.

1990-08-01

Motion analysis studies require the precise tracking of reference objects in sequential scenes. In a typical situation, events of interest are captured at high frame rates using special cameras, and selected objects or targets are tracked on a frame by frame basis to provide necessary data for motion reconstruction. Tracking is usually done using manual methods which are slow and prone to error. A computer based image analysis system has been developed that performs tracking automatically. The objective of this work was to eliminate the bottleneck due to manual methods in high volume tracking applications such as the analysis of crash test films for the automotive industry. The system has proven to be successful in tracking standard fiducial targets and other objects in crash test scenes. Over 95 percent of target positions which could be located using manual methods can be tracked by the system, with a significant improvement in throughput over manual methods. Future work will focus on the tracking of clusters of targets and on tracking deformable objects such as airbags.

Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

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

Ma Yingliang; Housden, R. James; Razavi, Reza

2013-07-15

Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction.Methods: In this paper, the authors presentmore » a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time.Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 {+-} 0.29, 0.92 {+-} 0.61, and 0.63 {+-} 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 {+-} 0.28, 0.64 {+-} 0.37, and 0.53 {+-} 0.38 mm and success rates increased to 100%, 99.2%, and 96.5% for the CS, ablation, and lasso catheters, respectively. Subjective clinical evaluation by three experienced electrophysiologists showed that the detection and tracking results were clinically acceptable.Conclusions: The proposed detection and tracking methods are automatic and can detect and track CS, ablation, and lasso catheters simultaneously and in real-time. The accuracy of the proposed methods is sub-mm and the methods are robust toward low-dose x-ray fluoroscopic images, which are mainly used during EP procedures to maintain low radiation dose.« less

Making Sense of Dinosaur Tracks

ERIC Educational Resources Information Center

MacKenzie, Ann Haley; McDowell, Brian

2012-01-01

What do paleontologists, dinosaur tracks, and the nature of science have in common? They're combined here in an inquiry activity where students use methods of observation and inference to devise evidence-based explanations for the data they collect about dinosaur tracks, much like the methods used by paleontologists. Students then debate the…

MOLECULAR TRACKING FECAL CONTAMINATION IN SURFACE WATERS: 16S RDNA VERSUS METAGENOMICS APPROACHES

EPA Science Inventory

Microbial source tracking methods need to be sensitive and exhibit temporal and geographic stability in order to provide meaningful data in field studies. The objective of this study was to use a combination of PCR-based methods to track cow fecal contamination in two watersheds....

Multi person detection and tracking based on hierarchical level-set method

NASA Astrophysics Data System (ADS)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

Electric vehicle chassis dynamometer test methods at JPL and their correlation to track tests

NASA Technical Reports Server (NTRS)

Marte, J.; Bryant, J.

1983-01-01

Early in its electric vehicle (EV) test program, JPL recognized that EV test procedures were too vague and too loosely defined to permit much meaningful data to be obtained from the testing. Therefore, JPL adopted more stringent test procedures and chose the chassis dynamometer rather than the track as its principal test technique. Through the years, test procedures continued to evolve towards a methodology based on chassis dynamometers which would exhibit good correlation with track testing. Based on comparative dynamometer and track test results on the ETV-1 vehicle, the test methods discussed in this report demonstrate a means by which excellent track-to-dynamometer correlation can be obtained.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking

DOE PAGES

Langford, Seth T.; Wiggins, Cody S.; Santos, Roque; ...

2017-07-06

A method for Positron Emission Particle Tracking (PEPT) based on optical feature point identification techniques is demonstrated for use in low activity tracking experiments. Furthermore, a population of yeast cells of approximately 125,000 members is activated to roughly 55 Bq/cell by 18F uptake. An in vitro particle tracking experiment is performed with nearly 20 of these cells after decay to 32 Bq/cell. These cells are successfully identified and tracked simultaneously in this experiment. Our work extends the applicability of PEPT as a cell tracking method by allowing a number of cells to be tracked together, and demonstrating tracking for verymore » low activity tracers.« less

Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking

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

Langford, Seth T.; Wiggins, Cody S.; Santos, Roque

A method for Positron Emission Particle Tracking (PEPT) based on optical feature point identification techniques is demonstrated for use in low activity tracking experiments. Furthermore, a population of yeast cells of approximately 125,000 members is activated to roughly 55 Bq/cell by 18F uptake. An in vitro particle tracking experiment is performed with nearly 20 of these cells after decay to 32 Bq/cell. These cells are successfully identified and tracked simultaneously in this experiment. Our work extends the applicability of PEPT as a cell tracking method by allowing a number of cells to be tracked together, and demonstrating tracking for verymore » low activity tracers.« less

Design and control of the precise tracking bed based on complex electromechanical design theory

NASA Astrophysics Data System (ADS)

Ren, Changzhi; Liu, Zhao; Wu, Liao; Chen, Ken

2010-05-01

The precise tracking technology is wide used in astronomical instruments, satellite tracking and aeronautic test bed. However, the precise ultra low speed tracking drive system is one high integrated electromechanical system, which one complexly electromechanical design method is adopted to improve the efficiency, reliability and quality of the system during the design and manufacture circle. The precise Tracking Bed is one ultra-exact, ultra-low speed, high precision and huge inertial instrument, which some kind of mechanism and environment of the ultra low speed is different from general technology. This paper explores the design process based on complex electromechanical optimizing design theory, one non-PID with a CMAC forward feedback control method is used in the servo system of the precise tracking bed and some simulation results are discussed.

Kinect based real-time position calibration for nasal endoscopic surgical navigation system

NASA Astrophysics Data System (ADS)

Fan, Jingfan; Yang, Jian; Chu, Yakui; Ma, Shaodong; Wang, Yongtian

2016-03-01

Unanticipated, reactive motion of the patient during skull based tumor resective surgery is the source of the consequence that the nasal endoscopic tracking system is compelled to be recalibrated. To accommodate the calibration process with patient's movement, this paper developed a Kinect based Real-time positional calibration method for nasal endoscopic surgical navigation system. In this method, a Kinect scanner was employed as the acquisition part of the point cloud volumetric reconstruction of the patient's head during surgery. Then, a convex hull based registration algorithm aligned the real-time image of the patient head with a model built upon the CT scans performed in the preoperative preparation to dynamically calibrate the tracking system if a movement was detected. Experimental results confirmed the robustness of the proposed method, presenting a total tracking error within 1 mm under the circumstance of relatively violent motions. These results point out the tracking accuracy can be retained stably and the potential to expedite the calibration of the tracking system against strong interfering conditions, demonstrating high suitability for a wide range of surgical applications.

Novel method based on video tracking system for simultaneous measurement of kinematics and flow in the wake of a freely swimming fish

NASA Astrophysics Data System (ADS)

Wu, Guanhao; Yang, Yan; Zeng, Lijiang

2006-11-01

A novel method based on video tracking system for simultaneous measurement of kinematics and flow in the wake of a freely swimming fish is described. Spontaneous and continuous swimming behaviors of a variegated carp (Cyprinus carpio) are recorded by two cameras mounted on a translation stage which is controlled to track the fish. By processing the images recorded during tracking, the detailed kinematics based on calculated midlines and quantitative analysis of the flow in the wake during a low-speed turn and burst-and-coast swimming are revealed. We also draw the trajectory of the fish during a continuous swimming bout containing several moderate maneuvers. The results prove that our method is effective for studying maneuvers of fish both from kinematic and hydrodynamic viewpoints.

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

NASA Astrophysics Data System (ADS)

Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.

2009-03-01

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

A precise integration method for solving coupled vehicle-track dynamics with nonlinear wheel-rail contact

NASA Astrophysics Data System (ADS)

Zhang, J.; Gao, Q.; Tan, S. J.; Zhong, W. X.

2012-10-01

A new method is proposed as a solution for the large-scale coupled vehicle-track dynamic model with nonlinear wheel-rail contact. The vehicle is simplified as a multi-rigid-body model, and the track is treated as a three-layer beam model. In the track model, the rail is assumed to be an Euler-Bernoulli beam supported by discrete sleepers. The vehicle model and the track model are coupled using Hertzian nonlinear contact theory, and the contact forces of the vehicle subsystem and the track subsystem are approximated by the Lagrange interpolation polynomial. The response of the large-scale coupled vehicle-track model is calculated using the precise integration method. A more efficient algorithm based on the periodic property of the track is applied to calculate the exponential matrix and certain matrices related to the solution of the track subsystem. Numerical examples demonstrate the computational accuracy and efficiency of the proposed method.

Video-based eye tracking for neuropsychiatric assessment.

PubMed

Adhikari, Sam; Stark, David E

2017-01-01

This paper presents a video-based eye-tracking method, ideally deployed via a mobile device or laptop-based webcam, as a tool for measuring brain function. Eye movements and pupillary motility are tightly regulated by brain circuits, are subtly perturbed by many disease states, and are measurable using video-based methods. Quantitative measurement of eye movement by readily available webcams may enable early detection and diagnosis, as well as remote/serial monitoring, of neurological and neuropsychiatric disorders. We successfully extracted computational and semantic features for 14 testing sessions, comprising 42 individual video blocks and approximately 17,000 image frames generated across several days of testing. Here, we demonstrate the feasibility of collecting video-based eye-tracking data from a standard webcam in order to assess psychomotor function. Furthermore, we were able to demonstrate through systematic analysis of this data set that eye-tracking features (in particular, radial and tangential variance on a circular visual-tracking paradigm) predict performance on well-validated psychomotor tests. © 2017 New York Academy of Sciences.

Track-based event recognition in a realistic crowded environment

NASA Astrophysics Data System (ADS)

van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

2014-10-01

Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

Comparison of different detection methods for persistent multiple hypothesis tracking in wide area motion imagery

NASA Astrophysics Data System (ADS)

Hartung, Christine; Spraul, Raphael; Schuchert, Tobias

2017-10-01

Wide area motion imagery (WAMI) acquired by an airborne multicamera sensor enables continuous monitoring of large urban areas. Each image can cover regions of several square kilometers and contain thousands of vehicles. Reliable vehicle tracking in this imagery is an important prerequisite for surveillance tasks, but remains challenging due to low frame rate and small object size. Most WAMI tracking approaches rely on moving object detections generated by frame differencing or background subtraction. These detection methods fail when objects slow down or stop. Recent approaches for persistent tracking compensate for missing motion detections by combining a detection-based tracker with a second tracker based on appearance or local context. In order to avoid the additional complexity introduced by combining two trackers, we employ an alternative single tracker framework that is based on multiple hypothesis tracking and recovers missing motion detections with a classifierbased detector. We integrate an appearance-based similarity measure, merge handling, vehicle-collision tests, and clutter handling to adapt the approach to the specific context of WAMI tracking. We apply the tracking framework on a region of interest of the publicly available WPAFB 2009 dataset for quantitative evaluation; a comparison to other persistent WAMI trackers demonstrates state of the art performance of the proposed approach. Furthermore, we analyze in detail the impact of different object detection methods and detector settings on the quality of the output tracking results. For this purpose, we choose four different motion-based detection methods that vary in detection performance and computation time to generate the input detections. As detector parameters can be adjusted to achieve different precision and recall performance, we combine each detection method with different detector settings that yield (1) high precision and low recall, (2) high recall and low precision, and (3) best f-score. Comparing the tracking performance achieved with all generated sets of input detections allows us to quantify the sensitivity of the tracker to different types of detector errors and to derive recommendations for detector and parameter choice.

A comparison of gantry-mounted x-ray-based real-time target tracking methods.

PubMed

Montanaro, Tim; Nguyen, Doan Trang; Keall, Paul J; Booth, Jeremy; Caillet, Vincent; Eade, Thomas; Haddad, Carol; Shieh, Chun-Chien

2018-03-01

Most modern radiotherapy machines are built with a 2D kV imaging system. Combining this imaging system with a 2D-3D inference method would allow for a ready-made option for real-time 3D tumor tracking. This work investigates and compares the accuracy of four existing 2D-3D inference methods using both motion traces inferred from external surrogates and measured internally from implanted beacons. Tumor motion data from 160 fractions (46 thoracic/abdominal patients) of Synchrony traces (inferred traces), and 28 fractions (7 lung patients) of Calypso traces (internal traces) from the LIGHT SABR trial (NCT02514512) were used in this study. The motion traces were used as the ground truth. The ground truth trajectories were used in silico to generate 2D positions projected on the kV detector. These 2D traces were then passed to the 2D-3D inference methods: interdimensional correlation, Gaussian probability density function (PDF), arbitrary-shape PDF, and the Kalman filter. The inferred 3D positions were compared with the ground truth to determine tracking errors. The relationships between tracking error and motion magnitude, interdimensional correlation, and breathing periodicity index (BPI) were also investigated. Larger tracking errors were observed from the Calypso traces, with RMS and 95th percentile 3D errors of 0.84-1.25 mm and 1.72-2.64 mm, compared to 0.45-0.68 mm and 0.74-1.13 mm from the Synchrony traces. The Gaussian PDF method was found to be the most accurate, followed by the Kalman filter, the interdimensional correlation method, and the arbitrary-shape PDF method. Tracking error was found to strongly and positively correlate with motion magnitude for both the Synchrony and Calypso traces and for all four methods. Interdimensional correlation and BPI were found to negatively correlate with tracking error only for the Synchrony traces. The Synchrony traces exhibited higher interdimensional correlation than the Calypso traces especially in the anterior-posterior direction. Inferred traces often exhibit higher interdimensional correlation, which are not true representation of thoracic/abdominal motion and may underestimate kV-based tracking errors. The use of internal traces acquired from systems such as Calypso is advised for future kV-based tracking studies. The Gaussian PDF method is the most accurate 2D-3D inference method for tracking thoracic/abdominal targets. Motion magnitude has significant impact on 2D-3D inference error, and should be considered when estimating kV-based tracking error. © 2018 American Association of Physicists in Medicine.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope.

PubMed

Liu, C; Liu, Y-L; Perillo, E P; Jiang, N; Dunn, A K; Yeh, H-C

2015-10-12

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we have precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico . Our method can be generally applied to other 3D single-particle tracking techniques.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope

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

Liu, C.; Liu, Y.-L.; Perillo, E. P.

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we havemore » precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico. Our method can be generally applied to other 3D single-particle tracking techniques.« less

Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

PubMed Central

Tian, Yuan; Guan, Tao; Wang, Cheng

2010-01-01

To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

A Hybrid Maximum Power Point Tracking Method for Automobile Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Quan, Rui; Zhou, Wei; Yang, Guangyou; Quan, Shuhai

2017-05-01

To make full use of the maximum output power of automobile exhaust thermoelectric generator (AETEG) based on Bi2Te3 thermoelectric modules (TEMs), taking into account the advantages and disadvantages of existing maximum power point tracking methods, and according to the output characteristics of TEMs, a hybrid maximum power point tracking method combining perturb and observe (P&O) algorithm, quadratic interpolation and constant voltage tracking method was put forward in this paper. Firstly, it searched the maximum power point with P&O algorithms and a quadratic interpolation method, then, it forced the AETEG to work at its maximum power point with constant voltage tracking. A synchronous buck converter and controller were implemented in the electric bus of the AETEG applied in a military sports utility vehicle, and the whole system was modeled and simulated with a MATLAB/Simulink environment. Simulation results demonstrate that the maximum output power of the AETEG based on the proposed hybrid method is increased by about 3.0% and 3.7% compared with that using only the P&O algorithm and the quadratic interpolation method, respectively. The shorter tracking time is only 1.4 s, which is reduced by half compared with that of the P&O algorithm and quadratic interpolation method, respectively. The experimental results demonstrate that the tracked maximum power is approximately equal to the real value using the proposed hybrid method,and it can preferentially deal with the voltage fluctuation of the AETEG with only P&O algorithm, and resolve the issue that its working point can barely be adjusted only with constant voltage tracking when the operation conditions change.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

Wavelet-based tracking of bacteria in unreconstructed off-axis holograms.

PubMed

Marin, Zach; Wallace, J Kent; Nadeau, Jay; Khalil, Andre

2018-03-01

We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holograms to provide rough estimates of the presence of motion and particle trajectories in digital holographic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low-particle-density time series, based on a preliminary analysis of both living and dead Serratia marcescens, and for rapidly providing a single-bit answer to whether a sample chamber contains living or dead microbes or is empty. Copyright © 2017 Elsevier Inc. All rights reserved.

Research on infrared small-target tracking technology under complex background

NASA Astrophysics Data System (ADS)

Liu, Lei; Wang, Xin; Chen, Jilu; Pan, Tao

2012-10-01

In this paper, some basic principles and the implementing flow charts of a series of algorithms for target tracking are described. On the foundation of above works, a moving target tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of tracking algorithms are integrated in this software. These two tracking algorithms are Kalman Filter tracking method and Camshift tracking method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target tracking technology.

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

NASA Astrophysics Data System (ADS)

Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Robust Target Tracking with Multi-Static Sensors under Insufficient TDOA Information.

PubMed

Shin, Hyunhak; Ku, Bonhwa; Nelson, Jill K; Ko, Hanseok

2018-05-08

This paper focuses on underwater target tracking based on a multi-static sonar network composed of passive sonobuoys and an active ping. In the multi-static sonar network, the location of the target can be estimated using TDOA (Time Difference of Arrival) measurements. However, since the sensor network may obtain insufficient and inaccurate TDOA measurements due to ambient noise and other harsh underwater conditions, target tracking performance can be significantly degraded. We propose a robust target tracking algorithm designed to operate in such a scenario. First, track management with track splitting is applied to reduce performance degradation caused by insufficient measurements. Second, a target location is estimated by a fusion of multiple TDOA measurements using a Gaussian Mixture Model (GMM). In addition, the target trajectory is refined by conducting a stack-based data association method based on multiple-frames measurements in order to more accurately estimate target trajectory. The effectiveness of the proposed method is verified through simulations.

3-D rigid body tracking using vision and depth sensors.

PubMed

Gedik, O Serdar; Alatan, A Aydn

2013-10-01

In robotics and augmented reality applications, model-based 3-D tracking of rigid objects is generally required. With the help of accurate pose estimates, it is required to increase reliability and decrease jitter in total. Among many solutions of pose estimation in the literature, pure vision-based 3-D trackers require either manual initializations or offline training stages. On the other hand, trackers relying on pure depth sensors are not suitable for AR applications. An automated 3-D tracking algorithm, which is based on fusion of vision and depth sensors via extended Kalman filter, is proposed in this paper. A novel measurement-tracking scheme, which is based on estimation of optical flow using intensity and shape index map data of 3-D point cloud, increases 2-D, as well as 3-D, tracking performance significantly. The proposed method requires neither manual initialization of pose nor offline training, while enabling highly accurate 3-D tracking. The accuracy of the proposed method is tested against a number of conventional techniques, and a superior performance is clearly observed in terms of both objectively via error metrics and subjectively for the rendered scenes.

Object-oriented feature-tracking algorithms for SAR images of the marginal ice zone

NASA Technical Reports Server (NTRS)

Daida, Jason; Samadani, Ramin; Vesecky, John F.

1990-01-01

An unsupervised method that chooses and applies the most appropriate tracking algorithm from among different sea-ice tracking algorithms is reported. In contrast to current unsupervised methods, this method chooses and applies an algorithm by partially examining a sequential image pair to draw inferences about what was examined. Based on these inferences the reported method subsequently chooses which algorithm to apply to specific areas of the image pair where that algorithm should work best.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

A data processing method based on tracking light spot for the laser differential confocal component parameters measurement system

NASA Astrophysics Data System (ADS)

Shao, Rongjun; Qiu, Lirong; Yang, Jiamiao; Zhao, Weiqian; Zhang, Xin

2013-12-01

We have proposed the component parameters measuring method based on the differential confocal focusing theory. In order to improve the positioning precision of the laser differential confocal component parameters measurement system (LDDCPMS), the paper provides a data processing method based on tracking light spot. To reduce the error caused by the light point moving in collecting the axial intensity signal, the image centroiding algorithm is used to find and track the center of Airy disk of the images collected by the laser differential confocal system. For weakening the influence of higher harmonic noises during the measurement, Gaussian filter is used to process the axial intensity signal. Ultimately the zero point corresponding to the focus of the objective in a differential confocal system is achieved by linear fitting for the differential confocal axial intensity data. Preliminary experiments indicate that the method based on tracking light spot can accurately collect the axial intensity response signal of the virtual pinhole, and improve the anti-interference ability of system. Thus it improves the system positioning accuracy.

Method for targetless tracking subpixel in-plane movements.

PubMed

Espinosa, Julian; Perez, Jorge; Ferrer, Belen; Mas, David

2015-09-01

We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a lab experiment consisting of a vibrating object that was recorded with a high-speed camera working at 1000 fps. We managed to track displacements with an accuracy of hundredths of pixel or even of thousandths of pixel in the case of tracking harmonic vibrations. The method is widely applicable because it can be used for distance measuring amplitude and frequency of vibrations with a vision system.

Star tracking method based on multiexposure imaging for intensified star trackers.

PubMed

Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

2017-07-20

The requirements for the dynamic performance of star trackers are rapidly increasing with the development of space exploration technologies. However, insufficient knowledge of the angular acceleration has largely decreased the performance of the existing star tracking methods, and star trackers may even fail to track under highly dynamic conditions. This study proposes a star tracking method based on multiexposure imaging for intensified star trackers. The accurate estimation model of the complete motion parameters, including the angular velocity and angular acceleration, is established according to the working characteristic of multiexposure imaging. The estimation of the complete motion parameters is utilized to generate the predictive star image accurately. Therefore, the correct matching and tracking between stars in the real and predictive star images can be reliably accomplished under highly dynamic conditions. Simulations with specific dynamic conditions are conducted to verify the feasibility and effectiveness of the proposed method. Experiments with real starry night sky observation are also conducted for further verification. Simulations and experiments demonstrate that the proposed method is effective and shows excellent performance under highly dynamic conditions.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Machine vision application in animal trajectory tracking.

PubMed

Koniar, Dušan; Hargaš, Libor; Loncová, Zuzana; Duchoň, František; Beňo, Peter

2016-04-01

This article was motivated by the doctors' demand to make a technical support in pathologies of gastrointestinal tract research [10], which would be based on machine vision tools. Proposed solution should be less expensive alternative to already existing RF (radio frequency) methods. The objective of whole experiment was to evaluate the amount of animal motion dependent on degree of pathology (gastric ulcer). In the theoretical part of the article, several methods of animal trajectory tracking are presented: two differential methods based on background subtraction, the thresholding methods based on global and local threshold and the last method used for animal tracking was the color matching with a chosen template containing a searched spectrum of colors. The methods were tested offline on five video samples. Each sample contained situation with moving guinea pig locked in a cage under various lighting conditions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Identification of characteristic frequencies of damaged railway tracks using field hammer test measurements

NASA Astrophysics Data System (ADS)

Oregui, M.; Li, Z.; Dollevoet, R.

2015-03-01

In this paper, the feasibility of the Frequency Response Function (FRF)-based statistical method to identify the characteristic frequencies of railway track defects is studied. The method compares a damaged track state to a healthy state based on non-destructive field hammer test measurements. First, a study is carried out to investigate the repeatability of hammer tests in railway tracks. By changing the excitation and measurement locations it is shown that the variability introduced by the test process is negligible. Second, following the concepts of control charts employed in process monitoring, a method to define an approximate healthy state is introduced by using hammer test measurements at locations without visual damage. Then, the feasibility study includes an investigation into squats (i.e. a major type of rail surface defect) of varying severity. The identified frequency ranges related to squats agree with those found in an extensively validated vehicle-borne detection system. Therefore, the FRF-based statistical method in combination with the non-destructive hammer test measurements has the potential to be employed to identify the characteristic frequencies of damaged conditions in railway tracks in the frequency range of 300-3000 Hz.

Joint Transform Correlation for face tracking: elderly fall detection application

NASA Astrophysics Data System (ADS)

Katz, Philippe; Aron, Michael; Alfalou, Ayman

2013-03-01

In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

Tracking and people counting using Particle Filter Method

NASA Astrophysics Data System (ADS)

Sulistyaningrum, D. R.; Setiyono, B.; Rizky, M. S.

2018-03-01

In recent years, technology has developed quite rapidly, especially in the field of object tracking. Moreover, if the object under study is a person and the number of people a lot. The purpose of this research is to apply Particle Filter method for tracking and counting people in certain area. Tracking people will be rather difficult if there are some obstacles, one of which is occlusion. The stages of tracking and people counting scheme in this study include pre-processing, segmentation using Gaussian Mixture Model (GMM), tracking using particle filter, and counting based on centroid. The Particle Filter method uses the estimated motion included in the model used. The test results show that the tracking and people counting can be done well with an average accuracy of 89.33% and 77.33% respectively from six videos test data. In the process of tracking people, the results are good if there is partial occlusion and no occlusion

On-Demand Calibration and Evaluation for Electromagnetically Tracked Laparoscope in Augmented Reality Visualization

PubMed Central

Liu, Xinyang; Plishker, William; Zaki, George; Kang, Sukryool; Kane, Timothy D.; Shekhar, Raj

2017-01-01

Purpose Common camera calibration methods employed in current laparoscopic augmented reality systems require the acquisition of multiple images of an entire checkerboard pattern from various poses. This lengthy procedure prevents performing laparoscope calibration in the operating room (OR). The purpose of this work was to develop a fast calibration method for electromagnetically (EM) tracked laparoscopes, such that calibration can be performed in the OR on demand. Methods We designed a mechanical tracking mount to uniquely and snugly position an EM sensor to an appropriate location on a conventional laparoscope. A tool named fCalib was developed to calibrate intrinsic camera parameters, distortion coefficients, and extrinsic parameters (transformation between the scope lens coordinate system and the EM sensor coordinate system) using a single image that shows an arbitrary portion of a special target pattern. For quick evaluation of calibration result in the OR, we integrated a tube phantom with fCalib and overlaid a virtual representation of the tube on the live video scene. Results We compared spatial target registration error between the common OpenCV method and the fCalib method in a laboratory setting. In addition, we compared the calibration re-projection error between the EM tracking-based fCalib and the optical tracking-based fCalib in a clinical setting. Our results suggested that the proposed method is comparable to the OpenCV method. However, changing the environment, e.g., inserting or removing surgical tools, would affect re-projection accuracy for the EM tracking-based approach. Computational time of the fCalib method averaged 14.0 s (range 3.5 s – 22.7 s). Conclusions We developed and validated a prototype for fast calibration and evaluation of EM tracked conventional (forward viewing) laparoscopes. The calibration method achieved acceptable accuracy and was relatively fast and easy to be performed in the OR on demand. PMID:27250853

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

An estimation of distribution method for infrared target detection based on Copulas

NASA Astrophysics Data System (ADS)

Wang, Shuo; Zhang, Yiqun

2015-10-01

Track-before-detect (TBD) based target detection involves a hypothesis test of merit functions which measure each track as a possible target track. Its accuracy depends on the precision of the distribution of merit functions, which determines the threshold for a test. Generally, merit functions are regarded Gaussian, and on this basis the distribution is estimated, which is true for most methods such as the multiple hypothesis tracking (MHT). However, merit functions for some other methods such as the dynamic programming algorithm (DPA) are non-Guassian and cross-correlated. Since existing methods cannot reasonably measure the correlation, the exact distribution can hardly be estimated. If merit functions are assumed Guassian and independent, the error between an actual distribution and its approximation may occasionally over 30 percent, and is divergent by propagation. Hence, in this paper, we propose a novel estimation of distribution method based on Copulas, by which the distribution can be estimated precisely, where the error is less than 1 percent without propagation. Moreover, the estimation merely depends on the form of merit functions and the structure of a tracking algorithm, and is invariant to measurements. Thus, the distribution can be estimated in advance, greatly reducing the demand for real-time calculation of distribution functions.

Discriminative detection of deposited radon daughters on CR-39 track detectors using TRIAC II code

NASA Astrophysics Data System (ADS)

Patiris, D. L.; Ioannides, K. G.

2009-07-01

A method for detecting deposited 218Po and 214Po by a spectrometric study of CR-39 solid state nuclear track detectors is described. The method is based on the application of software imposed selection criteria, concerning the geometrical and optical properties of the tracks, which correspond to tracks created by alpha particles of specific energy falling on the detector at given angles of incidence. The selection criteria were based on a preliminary study of tracks' parameters (major and minor axes and mean value of brightness), using the TRIAC II code. Since no linear relation was found between the energy and the geometric characteristics of the tracks (major and minor axes), we resorted to the use of an additional parameter in order to classify the tracks according to the particles' energy. Since the brightness of tracks is associated with the tracks' depth, the mean value of brightness was chosen as the parameter of choice. To reduce the energy of the particles, which are emitted by deposited 218Po and 214Po into a quantifiable range, the detectors were covered with an aluminum absorber material. In this way, the discrimination of radon's daughters was finally accomplished by properly selecting amongst all registered tracks. This method could be applied as a low cost tool for the study of the radon's daughters behavior in air.

Model-based control strategies for systems with constraints of the program type

NASA Astrophysics Data System (ADS)

Jarzębowska, Elżbieta

2006-08-01

The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.

PubMed

Brandes, Susanne; Mokhtari, Zeinab; Essig, Fabian; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-02-01

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points. Copyright © 2014 Elsevier B.V. All rights reserved.

Investigation on microfluidic particles manipulation by holographic 3D tracking strategies

NASA Astrophysics Data System (ADS)

Cacace, Teresa; Paturzo, Melania; Memmolo, Pasquale; Vassalli, Massimo; Fraldi, Massimiliano; Mensitieri, Giuseppe; Ferraro, Pietro

2017-06-01

We demonstrate a 3D holographic tracking method to investigate particles motion in a microfluidic channel while unperturbed while inducing their migration through microfluidic manipulation. Digital holography (DH) in microscopy is a full-field, label-free imaging technique able to provide quantitative phase-contrast. The employed 3D tracking method is articulated in steps. First, the displacements along the optical axis are assessed by numerical refocusing criteria. In particular, an automatic refocusing method to recover the particles axial position is implemented employing a contrast-based refocusing criterion. Then, the transverse position of the in-focus object is evaluated through quantitative phase map segmentation methods and centroid-based 2D tracking strategy. The introduction of DH is thus suggested as a powerful approach for control of particles and biological samples manipulation, as well as a possible aid to precise design and implementation of advanced lab-on-chip microfluidic devices.

Model-Free Optimal Tracking Control via Critic-Only Q-Learning.

PubMed

Luo, Biao; Liu, Derong; Huang, Tingwen; Wang, Ding

2016-10-01

Model-free control is an important and promising topic in control fields, which has attracted extensive attention in the past few years. In this paper, we aim to solve the model-free optimal tracking control problem of nonaffine nonlinear discrete-time systems. A critic-only Q-learning (CoQL) method is developed, which learns the optimal tracking control from real system data, and thus avoids solving the tracking Hamilton-Jacobi-Bellman equation. First, the Q-learning algorithm is proposed based on the augmented system, and its convergence is established. Using only one neural network for approximating the Q-function, the CoQL method is developed to implement the Q-learning algorithm. Furthermore, the convergence of the CoQL method is proved with the consideration of neural network approximation error. With the convergent Q-function obtained from the CoQL method, the adaptive optimal tracking control is designed based on the gradient descent scheme. Finally, the effectiveness of the developed CoQL method is demonstrated through simulation studies. The developed CoQL method learns with off-policy data and implements with a critic-only structure, thus it is easy to realize and overcome the inadequate exploration problem.

Research on SaaS and Web Service Based Order Tracking

NASA Astrophysics Data System (ADS)

Jiang, Jianhua; Sheng, Buyun; Gong, Lixiong; Yang, Mingzhong

To solve the order tracking of across enterprises in Dynamic Virtual Enterprise (DVE), a SaaS and web service based order tracking solution was designed by analyzing the order management process in DVE. To achieve the system, the SaaS based architecture of data management on order tasks manufacturing states was constructed, and the encapsulation method of transforming application system into web service was researched. Then the process of order tracking in the system was given out. Finally, the feasibility of this study was verified by the development of a prototype system.

Validation of a method for real time foot position and orientation tracking with Microsoft Kinect technology for use in virtual reality and treadmill based gait training programs.

PubMed

Paolini, Gabriele; Peruzzi, Agnese; Mirelman, Anat; Cereatti, Andrea; Gaukrodger, Stephen; Hausdorff, Jeffrey M; Della Croce, Ugo

2014-09-01

The use of virtual reality for the provision of motor-cognitive gait training has been shown to be effective for a variety of patient populations. The interaction between the user and the virtual environment is achieved by tracking the motion of the body parts and replicating it in the virtual environment in real time. In this paper, we present the validation of a novel method for tracking foot position and orientation in real time, based on the Microsoft Kinect technology, to be used for gait training combined with virtual reality. The validation of the motion tracking method was performed by comparing the tracking performance of the new system against a stereo-photogrammetric system used as gold standard. Foot position errors were in the order of a few millimeters (average RMSD from 4.9 to 12.1 mm in the medio-lateral and vertical directions, from 19.4 to 26.5 mm in the anterior-posterior direction); the foot orientation errors were also small (average %RMSD from 5.6% to 8.8% in the medio-lateral and vertical directions, from 15.5% to 18.6% in the anterior-posterior direction). The results suggest that the proposed method can be effectively used to track feet motion in virtual reality and treadmill-based gait training programs.

A novel infrared small moving target detection method based on tracking interest points under complicated background

NASA Astrophysics Data System (ADS)

Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

2014-07-01

Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

On-demand calibration and evaluation for electromagnetically tracked laparoscope in augmented reality visualization.

PubMed

Liu, Xinyang; Plishker, William; Zaki, George; Kang, Sukryool; Kane, Timothy D; Shekhar, Raj

2016-06-01

Common camera calibration methods employed in current laparoscopic augmented reality systems require the acquisition of multiple images of an entire checkerboard pattern from various poses. This lengthy procedure prevents performing laparoscope calibration in the operating room (OR). The purpose of this work was to develop a fast calibration method for electromagnetically (EM) tracked laparoscopes, such that the calibration can be performed in the OR on demand. We designed a mechanical tracking mount to uniquely and snugly position an EM sensor to an appropriate location on a conventional laparoscope. A tool named fCalib was developed to calibrate intrinsic camera parameters, distortion coefficients, and extrinsic parameters (transformation between the scope lens coordinate system and the EM sensor coordinate system) using a single image that shows an arbitrary portion of a special target pattern. For quick evaluation of calibration results in the OR, we integrated a tube phantom with fCalib prototype and overlaid a virtual representation of the tube on the live video scene. We compared spatial target registration error between the common OpenCV method and the fCalib method in a laboratory setting. In addition, we compared the calibration re-projection error between the EM tracking-based fCalib and the optical tracking-based fCalib in a clinical setting. Our results suggest that the proposed method is comparable to the OpenCV method. However, changing the environment, e.g., inserting or removing surgical tools, might affect re-projection accuracy for the EM tracking-based approach. Computational time of the fCalib method averaged 14.0 s (range 3.5 s-22.7 s). We developed and validated a prototype for fast calibration and evaluation of EM tracked conventional (forward viewing) laparoscopes. The calibration method achieved acceptable accuracy and was relatively fast and easy to be performed in the OR on demand.

Tracking tumor boundary in MV-EPID images without implanted markers: A feasibility study

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

Zhang, Xiaoyong, E-mail: xiaoyong@ieee.org; Homma, Noriyasu, E-mail: homma@ieee.org; Ichiji, Kei, E-mail: ichiji@yoshizawa.ecei.tohoku.ac.jp

2015-05-15

Purpose: To develop a markerless tracking algorithm to track the tumor boundary in megavoltage (MV)-electronic portal imaging device (EPID) images for image-guided radiation therapy. Methods: A level set method (LSM)-based algorithm is developed to track tumor boundary in EPID image sequences. Given an EPID image sequence, an initial curve is manually specified in the first frame. Driven by a region-scalable energy fitting function, the initial curve automatically evolves toward the tumor boundary and stops on the desired boundary while the energy function reaches its minimum. For the subsequent frames, the tracking algorithm updates the initial curve by using the trackingmore » result in the previous frame and reuses the LSM to detect the tumor boundary in the subsequent frame so that the tracking processing can be continued without user intervention. The tracking algorithm is tested on three image datasets, including a 4-D phantom EPID image sequence, four digitally deformable phantom image sequences with different noise levels, and four clinical EPID image sequences acquired in lung cancer treatment. The tracking accuracy is evaluated based on two metrics: centroid localization error (CLE) and volume overlap index (VOI) between the tracking result and the ground truth. Results: For the 4-D phantom image sequence, the CLE is 0.23 ± 0.20 mm, and VOI is 95.6% ± 0.2%. For the digital phantom image sequences, the total CLE and VOI are 0.11 ± 0.08 mm and 96.7% ± 0.7%, respectively. In addition, for the clinical EPID image sequences, the proposed algorithm achieves 0.32 ± 0.77 mm in the CLE and 72.1% ± 5.5% in the VOI. These results demonstrate the effectiveness of the authors’ proposed method both in tumor localization and boundary tracking in EPID images. In addition, compared with two existing tracking algorithms, the proposed method achieves a higher accuracy in tumor localization. Conclusions: In this paper, the authors presented a feasibility study of tracking tumor boundary in EPID images by using a LSM-based algorithm. Experimental results conducted on phantom and clinical EPID images demonstrated the effectiveness of the tracking algorithm for visible tumor target. Compared with previous tracking methods, the authors’ algorithm has the potential to improve the tracking accuracy in radiation therapy. In addition, real-time tumor boundary information within the irradiation field will be potentially useful for further applications, such as adaptive beam delivery, dose evaluation.« less

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

Yan, H; Chen, Z; Nath, R

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

Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking

PubMed Central

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods. PMID:23843739

Memory-based multiagent coevolution modeling for robust moving object tracking.

PubMed

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods.

Fuzzy observer-based control for maximum power-point tracking of a photovoltaic system

NASA Astrophysics Data System (ADS)

Allouche, M.; Dahech, K.; Chaabane, M.; Mehdi, D.

2018-04-01

This paper presents a novel fuzzy control design method for maximum power-point tracking (MPPT) via a Takagi and Sugeno (TS) fuzzy model-based approach. A knowledge-dynamic model of the PV system is first developed leading to a TS representation by a simple convex polytopic transformation. Then, based on this exact fuzzy representation, a H∞ observer-based fuzzy controller is proposed to achieve MPPT even when we consider varying climatic conditions. A specified TS reference model is designed to generate the optimum trajectory which must be tracked to ensure maximum power operation. The controller and observer gains are obtained in a one-step procedure by solving a set of linear matrix inequalities (LMIs). The proposed method has been compared with some classical MPPT techniques taking into account convergence speed and tracking accuracy. Finally, various simulation and experimental tests have been carried out to illustrate the effectiveness of the proposed TS fuzzy MPPT strategy.

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.

Control strategy of grid-connected photovoltaic generation system based on GMPPT method

NASA Astrophysics Data System (ADS)

Wang, Zhongfeng; Zhang, Xuyang; Hu, Bo; Liu, Jun; Li, Ligang; Gu, Yongqiang; Zhou, Bowen

2018-02-01

There are multiple local maximum power points when photovoltaic (PV) array runs under partial shading condition (PSC).However, the traditional maximum power point tracking (MPPT) algorithm might be easily trapped in local maximum power points (MPPs) and cannot find the global maximum power point (GMPP). To solve such problem, a global maximum power point tracking method (GMPPT) is improved, combined with traditional MPPT method and particle swarm optimization (PSO) algorithm. Under different operating conditions of PV cells, different tracking algorithms are used. When the environment changes, the improved PSO algorithm is adopted to realize the global optimal search, and the variable step incremental conductance (INC) method is adopted to achieve MPPT in optimal local location. Based on the simulation model of the PV grid system built in Matlab/Simulink, comparative analysis of the tracking effect of MPPT by the proposed control algorithm and the traditional MPPT method under the uniform solar condition and PSC, validate the correctness, feasibility and effectiveness of the proposed control strategy.

Improvement of Hand Movement on Visual Target Tracking by Assistant Force of Model-Based Compensator

NASA Astrophysics Data System (ADS)

Ide, Junko; Sugi, Takenao; Nakamura, Masatoshi; Shibasaki, Hiroshi

Human motor control is achieved by the appropriate motor commands generating from the central nerve system. A test of visual target tracking is one of the effective methods for analyzing the human motor functions. We have previously examined a possibility for improving the hand movement on visual target tracking by additional assistant force through a simulation study. In this study, a method for compensating the human hand movement on visual target tracking by adding an assistant force was proposed. Effectiveness of the compensation method was investigated through the experiment for four healthy adults. The proposed compensator precisely improved the reaction time, the position error and the variability of the velocity of the human hand. The model-based compensator proposed in this study is constructed by using the measurement data on visual target tracking for each subject. The properties of the hand movement for different subjects can be reflected in the structure of the compensator. Therefore, the proposed method has possibility to adjust the individual properties of patients with various movement disorders caused from brain dysfunctions.

Improved relocatable over-the-horizon radar detection and tracking using the maximum likelihood adaptive neural system algorithm

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Webb, Virgil H.; Bradley, Scott R.; Hansen, Christopher A.

1998-07-01

An advanced detection and tracking system is being developed for the U.S. Navy's Relocatable Over-the-Horizon Radar (ROTHR) to provide improved tracking performance against small aircraft typically used in drug-smuggling activities. The development is based on the Maximum Likelihood Adaptive Neural System (MLANS), a model-based neural network that combines advantages of neural network and model-based algorithmic approaches. The objective of the MLANS tracker development effort is to address user requirements for increased detection and tracking capability in clutter and improved track position, heading, and speed accuracy. The MLANS tracker is expected to outperform other approaches to detection and tracking for the following reasons. It incorporates adaptive internal models of target return signals, target tracks and maneuvers, and clutter signals, which leads to concurrent clutter suppression, detection, and tracking (track-before-detect). It is not combinatorial and thus does not require any thresholding or peak picking and can track in low signal-to-noise conditions. It incorporates superresolution spectrum estimation techniques exceeding the performance of conventional maximum likelihood and maximum entropy methods. The unique spectrum estimation method is based on the Einsteinian interpretation of the ROTHR received energy spectrum as a probability density of signal frequency. The MLANS neural architecture and learning mechanism are founded on spectrum models and maximization of the "Einsteinian" likelihood, allowing knowledge of the physical behavior of both targets and clutter to be injected into the tracker algorithms. The paper describes the addressed requirements and expected improvements, theoretical foundations, engineering methodology, and results of the development effort to date.

Good Features to Correlate for Visual Tracking

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Alatan, A. Aydin

2018-05-01

During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.

On use of characteristic wavelengths of track irregularities to predict track portions with deteriorated wheel/rail forces

NASA Astrophysics Data System (ADS)

Xu, Lei; Zhai, Wanming; Chen, Zhaowei

2018-05-01

The dynamic performance of the railway vehicles and the guiding tracks is mainly governed by the wheel-rail interactions, particularly in cases of track irregularities. In this work, a united model was developed to investigate the track portions subject to violent wheel/rail forces triggered by track irregularities at middle-low frequencies. In the modeling procedures, a time-frequency unification method combining wavelet transform and Wigner-Ville distribution for characterizing time-frequency characteristics of track irregularities and a three-dimensional nonlinear model for describing vehicle-track interaction signatures were developed and coupled, based on which the method for predicting track portions subject to deteriorated wheel/rail forces was proposed. The theoretical models developed in this paper were comprehensively validated by numerical investigations. The significance of this present study mainly lies on offering a new path to establish correlation and realize mutual prediction between track irregularity and railway system dynamics.

FIRE: an open-software suite for real-time 2D/3D image registration for image guided radiotherapy research

NASA Astrophysics Data System (ADS)

Furtado, H.; Gendrin, C.; Spoerk, J.; Steiner, E.; Underwood, T.; Kuenzler, T.; Georg, D.; Birkfellner, W.

2016-03-01

Radiotherapy treatments have changed at a tremendously rapid pace. Dose delivered to the tumor has escalated while organs at risk (OARs) are better spared. The impact of moving tumors during dose delivery has become higher due to very steep dose gradients. Intra-fractional tumor motion has to be managed adequately to reduce errors in dose delivery. For tumors with large motion such as tumors in the lung, tracking is an approach that can reduce position uncertainty. Tumor tracking approaches range from purely image intensity based techniques to motion estimation based on surrogate tracking. Research efforts are often based on custom designed software platforms which take too much time and effort to develop. To address this challenge we have developed an open software platform especially focusing on tumor motion management. FLIRT is a freely available open-source software platform. The core method for tumor tracking is purely intensity based 2D/3D registration. The platform is written in C++ using the Qt framework for the user interface. The performance critical methods are implemented on the graphics processor using the CUDA extension. One registration can be as fast as 90ms (11Hz). This is suitable to track tumors moving due to respiration (~0.3Hz) or heartbeat (~1Hz). Apart from focusing on high performance, the platform is designed to be flexible and easy to use. Current use cases range from tracking feasibility studies, patient positioning and method validation. Such a framework has the potential of enabling the research community to rapidly perform patient studies or try new methods.

Simultaneous Monitoring of Ballistocardiogram and Photoplethysmogram Using Camera

PubMed Central

Shao, Dangdang; Tsow, Francis; Liu, Chenbin; Yang, Yuting; Tao, Nongjian

2017-01-01

We present a noncontact method to measure Ballistocardiogram (BCG) and Photoplethysmogram (PPG) simultaneously using a single camera. The method tracks the motion of facial features to determine displacement BCG, and extracts the corresponding velocity and acceleration BCGs by taking first and second temporal derivatives from the displacement BCG, respectively. The measured BCG waveforms are consistent with those reported in literature and also with those recorded with an accelerometer-based reference method. The method also tracks PPG based on the reflected light from the same facial region, which makes it possible to track both BCG and PPG with the same optics. We verify the robustness and reproducibility of the noncontact method with a small pilot study with 23 subjects. The presented method is the first demonstration of simultaneous BCG and PPG monitoring without wearing any extra equipment or marker by the subject. PMID:27362754

Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection

NASA Astrophysics Data System (ADS)

Li, Gang; McDonald, Geoff L.; Zhao, Qing

2017-01-01

This paper presents a novel Sinusoidal Synthesis Based Adaptive Tracking (SSBAT) technique for vibration-based rotating machinery fault detection. The proposed SSBAT algorithm is an adaptive time series technique that makes use of both frequency and time domain information of vibration signals. Such information is incorporated in a time varying dynamic model. Signal tracking is then realized by applying adaptive sinusoidal synthesis to the vibration signal. A modified Least-Squares (LS) method is adopted to estimate the model parameters. In addition to tracking, the proposed vibration synthesis model is mainly used as a linear time-varying predictor. The health condition of the rotating machine is monitored by checking the residual between the predicted and measured signal. The SSBAT method takes advantage of the sinusoidal nature of vibration signals and transfers the nonlinear problem into a linear adaptive problem in the time domain based on a state-space realization. It has low computation burden and does not need a priori knowledge of the machine under the no-fault condition which makes the algorithm ideal for on-line fault detection. The method is validated using both numerical simulation and practical application data. Meanwhile, the fault detection results are compared with the commonly adopted autoregressive (AR) and autoregressive Minimum Entropy Deconvolution (ARMED) method to verify the feasibility and performance of the SSBAT method.

Colonoscope navigation system using colonoscope tracking method based on line registration

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kondo, Hiroaki; Kitasaka, Takayuki; Furukawa, Kazuhiro; Miyahara, Ryoji; Hirooka, Yoshiki; Goto, Hidemi; Navab, Nassir; Mori, Kensaku

2014-03-01

This paper presents a new colonoscope navigation system. CT colonography is utilized for colon diagnosis based on CT images. If polyps are found while CT colonography, colonoscopic polypectomy can be performed to remove them. While performing a colonoscopic examination, a physician controls colonoscope based on his/her experience. Inexperienced physicians may occur complications such as colon perforation while colonoscopic examinations. To reduce complications, a navigation system of colonoscope while performing the colonoscopic examinations is necessary. We propose a colonoscope navigation system. This system has a new colonoscope tracking method. This method obtains a colon centerline from a CT volume of a patient. A curved line (colonoscope line) representing the shape of colonoscope inserted to the colon is obtained by using electromagnetic sensors. A coordinate system registration process that employs the ICP algorithm is performed to register the CT and sensor coordinate systems. The colon centerline and colonoscope line are registered by using a line registration method. The position of the colonoscope tip in the colon is obtained from the line registration result. Our colonoscope navigation system displays virtual colonoscopic views generated from the CT volumes. A viewpoint of the virtual colonoscopic view is a point on the centerline that corresponds to the colonoscope tip. Experimental results using a colon phantom showed that the proposed colonoscope tracking method can track the colonoscope tip with small tracking errors.

Tracking Multiple Video Targets with an Improved GM-PHD Tracker

PubMed Central

Zhou, Xiaolong; Yu, Hui; Liu, Honghai; Li, Youfu

2015-01-01

Tracking multiple moving targets from a video plays an important role in many vision-based robotic applications. In this paper, we propose an improved Gaussian mixture probability hypothesis density (GM-PHD) tracker with weight penalization to effectively and accurately track multiple moving targets from a video. First, an entropy-based birth intensity estimation method is incorporated to eliminate the false positives caused by noisy video data. Then, a weight-penalized method with multi-feature fusion is proposed to accurately track the targets in close movement. For targets without occlusion, a weight matrix that contains all updated weights between the predicted target states and the measurements is constructed, and a simple, but effective method based on total weight and predicted target state is proposed to search the ambiguous weights in the weight matrix. The ambiguous weights are then penalized according to the fused target features that include spatial-colour appearance, histogram of oriented gradient and target area and further re-normalized to form a new weight matrix. With this new weight matrix, the tracker can correctly track the targets in close movement without occlusion. For targets with occlusion, a robust game-theoretical method is used. Finally, the experiments conducted on various video scenarios validate the effectiveness of the proposed penalization method and show the superior performance of our tracker over the state of the art. PMID:26633422

Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress

PubMed Central

Fu, Longwen; Liu, Zuoyi

2018-01-01

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented. PMID:29849612

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

Catheter tracking in an interventional photoacoustic surgical system

NASA Astrophysics Data System (ADS)

Cheng, Alexis; Itsarachaiyot, Yuttana; Kim, Younsu; Zhang, Haichong K.; Taylor, Russell H.; Boctor, Emad M.

2017-03-01

In laparoscopic medical procedures, accurate tracking of interventional tools such as catheters are necessary. Current practice for tracking catheters often involve using fluoroscopy, which is best avoided to minimize radiation dose to the patient and the surgical team. Photoacoustic imaging is an emerging imaging modality that can be used for this purpose and does not currently have a general tool tracking solution. Photoacoustic-based catheter tracking would increase its attractiveness, by providing both an imaging and tracking solution. We present a catheter tracking method based on the photoacoustic effect. Photoacoustic markers are simultaneously observed by a stereo camera as well as a piezoelectric element attached to the tip of a catheter. The signals received by the piezoelectric element can be used to compute its position relative to the photoacoustic markers using multilateration. This combined information can be processed to localize the position of the piezoelectric element with respect to the stereo camera system. We presented the methods to enable this work and demonstrated precisions of 1-3mm and a relative accuracy of less than 4% in four independent locations, which are comparable to conventional systems. In addition, we also showed in another experiment a reconstruction precision up to 0.4mm and an estimated accuracy up to 0.5mm. Future work will include simulations to better evaluate this method and its challenges and the development of concurrent photoacoustic marker projection and its associated methods.

Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid

PubMed Central

Byambasuren, Bat-erdene; Kim, Donghan; Oyun-Erdene, Mandakh; Bold, Chinguun; Yura, Jargalbaatar

2016-01-01

Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results. PMID:26907274

Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid.

PubMed

Byambasuren, Bat-Erdene; Kim, Donghan; Oyun-Erdene, Mandakh; Bold, Chinguun; Yura, Jargalbaatar

2016-02-19

Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results.

Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

PubMed Central

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-01-01

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

Preceding vehicle detection and tracking adaptive to illumination variation in night traffic scenes based on relevance analysis.

PubMed

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-08-19

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation.

Tracking tumor boundary in MV-EPID images without implanted markers: A feasibility study.

PubMed

Zhang, Xiaoyong; Homma, Noriyasu; Ichiji, Kei; Takai, Yoshihiro; Yoshizawa, Makoto

2015-05-01

To develop a markerless tracking algorithm to track the tumor boundary in megavoltage (MV)-electronic portal imaging device (EPID) images for image-guided radiation therapy. A level set method (LSM)-based algorithm is developed to track tumor boundary in EPID image sequences. Given an EPID image sequence, an initial curve is manually specified in the first frame. Driven by a region-scalable energy fitting function, the initial curve automatically evolves toward the tumor boundary and stops on the desired boundary while the energy function reaches its minimum. For the subsequent frames, the tracking algorithm updates the initial curve by using the tracking result in the previous frame and reuses the LSM to detect the tumor boundary in the subsequent frame so that the tracking processing can be continued without user intervention. The tracking algorithm is tested on three image datasets, including a 4-D phantom EPID image sequence, four digitally deformable phantom image sequences with different noise levels, and four clinical EPID image sequences acquired in lung cancer treatment. The tracking accuracy is evaluated based on two metrics: centroid localization error (CLE) and volume overlap index (VOI) between the tracking result and the ground truth. For the 4-D phantom image sequence, the CLE is 0.23 ± 0.20 mm, and VOI is 95.6% ± 0.2%. For the digital phantom image sequences, the total CLE and VOI are 0.11 ± 0.08 mm and 96.7% ± 0.7%, respectively. In addition, for the clinical EPID image sequences, the proposed algorithm achieves 0.32 ± 0.77 mm in the CLE and 72.1% ± 5.5% in the VOI. These results demonstrate the effectiveness of the authors' proposed method both in tumor localization and boundary tracking in EPID images. In addition, compared with two existing tracking algorithms, the proposed method achieves a higher accuracy in tumor localization. In this paper, the authors presented a feasibility study of tracking tumor boundary in EPID images by using a LSM-based algorithm. Experimental results conducted on phantom and clinical EPID images demonstrated the effectiveness of the tracking algorithm for visible tumor target. Compared with previous tracking methods, the authors' algorithm has the potential to improve the tracking accuracy in radiation therapy. In addition, real-time tumor boundary information within the irradiation field will be potentially useful for further applications, such as adaptive beam delivery, dose evaluation.

Hand-eye calibration for rigid laparoscopes using an invariant point.

PubMed

Thompson, Stephen; Stoyanov, Danail; Schneider, Crispin; Gurusamy, Kurinchi; Ourselin, Sébastien; Davidson, Brian; Hawkes, David; Clarkson, Matthew J

2016-06-01

Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet it can be difficult due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but one current challenge is in accurate "hand-eye" calibration, which determines the position and orientation of the laparoscope camera relative to the tracking markers. In this paper, we propose a simple and clinically feasible calibration method based on a single invariant point. The method requires no additional hardware, can be constructed by theatre staff during surgical setup, requires minimal image processing and can be visualised in real time. Real-time visualisation allows the surgical team to assess the calibration accuracy before use in surgery. In addition, in the laboratory, we have developed a laparoscope with an electromagnetic tracking sensor attached to the camera end and an optical tracking marker attached to the distal end. This enables a comparison of tracking performance. We have evaluated our method in the laboratory and compared it to two widely used methods, "Tsai's method" and "direct" calibration. The new method is of comparable accuracy to existing methods, and we show RMS projected error due to calibration of 1.95 mm for optical tracking and 0.85 mm for EM tracking, versus 4.13 and 1.00 mm respectively, using existing methods. The new method has also been shown to be workable under sterile conditions in the operating room. We have proposed a new method of hand-eye calibration, based on a single invariant point. Initial experience has shown that the method provides visual feedback, satisfactory accuracy and can be performed during surgery. We also show that an EM sensor placed near the camera would provide significantly improved image overlay accuracy.

Method and system for detecting polygon boundaries of structures in images as particle tracks through fields of corners and pixel gradients

DOEpatents

Paglieroni, David W [Pleasanton, CA; Manay, Siddharth [Livermore, CA

2011-12-20

A stochastic method and system for detecting polygon structures in images, by detecting a set of best matching corners of predetermined acuteness .alpha. of a polygon model from a set of similarity scores based on GDM features of corners, and tracking polygon boundaries as particle tracks using a sequential Monte Carlo approach. The tracking involves initializing polygon boundary tracking by selecting pairs of corners from the set of best matching corners to define a first side of a corresponding polygon boundary; tracking all intermediate sides of the polygon boundaries using a particle filter, and terminating polygon boundary tracking by determining the last side of the tracked polygon boundaries to close the polygon boundaries. The particle tracks are then blended to determine polygon matches, which may be made available, such as to a user, for ranking and inspection.

In vivo MRI cell tracking using perfluorocarbon probes and fluorine-19 detection

PubMed Central

Ahrens, Eric T.; Zhong, Jia

2013-01-01

This article is a brief survey of preclinical in vivo cell tracking methods and applications using perfluorocarbon (PFC) probes and fluorine-19 (19F) MRI detection. Detection of the 19F signal offers high cell specificity and quantification abilities in spin-density weighted MR images. We discuss the compositions of matter, methods, and applications of PFC-based cell tracking using ex vivo and in situ PFC labeling in preclinical studies of inflammation and cellular therapeutics. We will also address potential applicability of 19F cell tracking to clinical trials. PMID:23606473

Label free cell-tracking and division detection based on 2D time-lapse images for lineage analysis of early embryo development.

PubMed

Cicconet, Marcelo; Gutwein, Michelle; Gunsalus, Kristin C; Geiger, Davi

2014-08-01

In this paper we report a database and a series of techniques related to the problem of tracking cells, and detecting their divisions, in time-lapse movies of mammalian embryos. Our contributions are (1) a method for counting embryos in a well, and cropping each individual embryo across frames, to create individual movies for cell tracking; (2) a semi-automated method for cell tracking that works up to the 8-cell stage, along with a software implementation available to the public (this software was used to build the reported database); (3) an algorithm for automatic tracking up to the 4-cell stage, based on histograms of mirror symmetry coefficients captured using wavelets; (4) a cell-tracking database containing 100 annotated examples of mammalian embryos up to the 8-cell stage; and (5) statistical analysis of various timing distributions obtained from those examples. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

PubMed Central

Rosser, Gabriel; Fletcher, Alexander G.; Wilkinson, David A.; de Beyer, Jennifer A.; Yates, Christian A.; Armitage, Judith P.; Maini, Philip K.; Baker, Ruth E.

2013-01-01

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species. PMID:24204227

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

PubMed Central

Qu, Shiru

2016-01-01

Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710

Laser Spot Tracking Based on Modified Circular Hough Transform and Motion Pattern Analysis

PubMed Central

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-01-01

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas–Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development. PMID:25350502

Laser spot tracking based on modified circular Hough transform and motion pattern analysis.

PubMed

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-10-27

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas-Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

New Performance Metrics for Quantitative Polymerase Chain Reaction-Based Microbial Source Tracking Methods

EPA Science Inventory

Binary sensitivity and specificity metrics are not adequate to describe the performance of quantitative microbial source tracking methods because the estimates depend on the amount of material tested and limit of detection. We introduce a new framework to compare the performance ...

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

2018-04-01

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Graph-based geometric-iconic guide-wire tracking.

PubMed

Honnorat, Nicolas; Vaillant, Régis; Paragios, Nikos

2011-01-01

In this paper we introduce a novel hybrid graph-based approach for Guide-wire tracking. The image support is captured by steerable filters and improved through tensor voting. Then, a graphical model is considered that represents guide-wire extraction/tracking through a B-spline control-point model. Points with strong geometric interest (landmarks) are automatically determined and anchored to such a representation. Tracking is then performed through discrete MRFs that optimize the spatio-temporal positions of the control points while establishing landmark temporal correspondences. Promising results demonstrate the potentials of our method.

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

An improved KCF tracking algorithm based on multi-feature and multi-scale

NASA Astrophysics Data System (ADS)

Wu, Wei; Wang, Ding; Luo, Xin; Su, Yang; Tian, Weiye

2018-02-01

The purpose of visual tracking is to associate the target object in a continuous video frame. In recent years, the method based on the kernel correlation filter has become the research hotspot. However, the algorithm still has some problems such as video capture equipment fast jitter, tracking scale transformation. In order to improve the ability of scale transformation and feature description, this paper has carried an innovative algorithm based on the multi feature fusion and multi-scale transform. The experimental results show that our method solves the problem that the target model update when is blocked or its scale transforms. The accuracy of the evaluation (OPE) is 77.0%, 75.4% and the success rate is 69.7%, 66.4% on the VOT and OTB datasets. Compared with the optimal one of the existing target-based tracking algorithms, the accuracy of the algorithm is improved by 6.7% and 6.3% respectively. The success rates are improved by 13.7% and 14.2% respectively.

Enabling freehand lateral scanning of optical coherence tomography needle probes with a magnetic tracking system

PubMed Central

Yeo, Boon Y.; McLaughlin, Robert A.; Kirk, Rodney W.; Sampson, David D.

2012-01-01

We present a high-resolution three-dimensional position tracking method that allows an optical coherence tomography (OCT) needle probe to be scanned laterally by hand, providing the high degree of flexibility and freedom required in clinical usage. The method is based on a magnetic tracking system, which is augmented by cross-correlation-based resampling and a two-stage moving window average algorithm to improve upon the tracker's limited intrinsic spatial resolution, achieving 18 µm RMS position accuracy. A proof-of-principle system was developed, with successful image reconstruction demonstrated on phantoms and on ex vivo human breast tissue validated against histology. This freehand scanning method could contribute toward clinical implementation of OCT needle imaging. PMID:22808429

Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.

Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging

NASA Astrophysics Data System (ADS)

Lin, Bingxiong; Sun, Yu; Qian, Xiaoning

2013-03-01

Robust feature point matching for images with large view angle changes in Minimally Invasive Surgery (MIS) is a challenging task due to low texture and specular reflections in these images. This paper presents a new approach that can improve feature matching performance by exploiting the inherent geometric property of the organ surfaces. Recently, intensity based template image tracking using a Thin Plate Spline (TPS) model has been extended for 3D surface tracking with stereo cameras. The intensity based tracking is also used here for 3D reconstruction of internal organ surfaces. To overcome the small displacement requirement of intensity based tracking, feature point correspondences are used for proper initialization of the nonlinear optimization in the intensity based method. Second, we generate simulated images from the reconstructed 3D surfaces under all potential view positions and orientations, and then extract feature points from these simulated images. The obtained feature points are then filtered and re-projected to the common reference image. The descriptors of the feature points under different view angles are stored to ensure that the proposed method can tolerate a large range of view angles. We evaluate the proposed method with silicon phantoms and in vivo images. The experimental results show that our method is much more robust with respect to the view angle changes than other state-of-the-art methods.

The Co-simulation of Humanoid Robot Based on Solidworks, ADAMS and Simulink

NASA Astrophysics Data System (ADS)

Song, Dalei; Zheng, Lidan; Wang, Li; Qi, Weiwei; Li, Yanli

A simulation method of adaptive controller is proposed for the humanoid robot system based on co-simulation of Solidworks, ADAMS and Simulink. A complex mathematical modeling process is avoided by this method, and the real time dynamic simulating function of Simulink would be exerted adequately. This method could be generalized to other complicated control system. This method is adopted to build and analyse the model of humanoid robot. The trajectory tracking and adaptive controller design also proceed based on it. The effect of trajectory tracking is evaluated by fitting-curve theory of least squares method. The anti-interference capability of the robot is improved a lot through comparative analysis.

Real-Time Radar-Based Tracking and State Estimation of Multiple Non-Conformant Aircraft

NASA Technical Reports Server (NTRS)

Cook, Brandon; Arnett, Timothy; Macmann, Owen; Kumar, Manish

2017-01-01

In this study, a novel solution for automated tracking of multiple unknown aircraft is proposed. Many current methods use transponders to self-report state information and augment track identification. While conformant aircraft typically report transponder information to alert surrounding aircraft of its state, vehicles may exist in the airspace that are non-compliant and need to be accurately tracked using alternative methods. In this study, a multi-agent tracking solution is presented that solely utilizes primary surveillance radar data to estimate aircraft state information. Main research challenges include state estimation, track management, data association, and establishing persistent track validity. In an effort to realize these challenges, techniques such as Maximum a Posteriori estimation, Kalman filtering, degree of membership data association, and Nearest Neighbor Spanning Tree clustering are implemented for this application.

Particle tracking in drug and gene delivery research: State-of-the-art applications and methods.

PubMed

Schuster, Benjamin S; Ensign, Laura M; Allan, Daniel B; Suk, Jung Soo; Hanes, Justin

2015-08-30

Particle tracking is a powerful microscopy technique to quantify the motion of individual particles at high spatial and temporal resolution in complex fluids and biological specimens. Particle tracking's applications and impact in drug and gene delivery research have greatly increased during the last decade. Thanks to advances in hardware and software, this technique is now more accessible than ever, and can be reliably automated to enable rapid processing of large data sets, thereby further enhancing the role that particle tracking will play in drug and gene delivery studies in the future. We begin this review by discussing particle tracking-based advances in characterizing extracellular and cellular barriers to therapeutic nanoparticles and in characterizing nanoparticle size and stability. To facilitate wider adoption of the technique, we then present a user-friendly review of state-of-the-art automated particle tracking algorithms and methods of analysis. We conclude by reviewing technological developments for next-generation particle tracking methods, and we survey future research directions in drug and gene delivery where particle tracking may be useful. Copyright © 2015 Elsevier B.V. All rights reserved.

A new method for motion capture of the scapula using an optoelectronic tracking device: a feasibility study.

PubMed

Šenk, Miroslav; Chèze, Laurence

2010-06-01

Optoelectronic tracking systems are rarely used in 3D studies examining shoulder movements including the scapula. Among the reasons is the important slippage of skin markers with respect to scapula. Methods using electromagnetic tracking devices are validated and frequently applied. Thus, the aim of this study was to develop a new method for in vivo optoelectronic scapular capture dealing with the accepted accuracy issues of validated methods. Eleven arm positions in three anatomical planes were examined using five subjects in static mode. The method was based on local optimisation, and recalculation procedures were made using a set of five scapular surface markers. The scapular rotations derived from the recalculation-based method yielded RMS errors comparable with the frequently used electromagnetic scapular methods (RMS up to 12.6° for 150° arm elevation). The results indicate that the present method can be used under careful considerations for 3D kinematical studies examining different shoulder movements.

CASPER: computer-aided segmentation of imperceptible motion-a learning-based tracking of an invisible needle in ultrasound.

PubMed

Beigi, Parmida; Rohling, Robert; Salcudean, Septimiu E; Ng, Gary C

2017-11-01

This paper presents a new micro-motion-based approach to track a needle in ultrasound images captured by a handheld transducer. We propose a novel learning-based framework to track a handheld needle by detecting microscale variations of motion dynamics over time. The current state of the art on using motion analysis for needle detection uses absolute motion and hence work well only when the transducer is static. We have introduced and evaluated novel spatiotemporal and spectral features, obtained from the phase image, in a self-supervised tracking framework to improve the detection accuracy in the subsequent frames using incremental training. Our proposed tracking method involves volumetric feature selection and differential flow analysis to incorporate the neighboring pixels and mitigate the effects of the subtle tremor motion of a handheld transducer. To evaluate the detection accuracy, the method is tested on porcine tissue in-vivo, during the needle insertion in the biceps femoris muscle. Experimental results show the mean, standard deviation and root-mean-square errors of [Formula: see text], [Formula: see text] and [Formula: see text] in the insertion angle, and 0.82, 1.21, 1.47 mm, in the needle tip, respectively. Compared to the appearance-based detection approaches, the proposed method is especially suitable for needles with ultrasonic characteristics that are imperceptible in the static image and to the naked eye.

Sensor management in RADAR/IRST track fusion

NASA Astrophysics Data System (ADS)

Hu, Shi-qiang; Jing, Zhong-liang

2004-07-01

In this paper, a novel radar management strategy technique suitable for RADAR/IRST track fusion, which is based on Fisher Information Matrix (FIM) and fuzzy stochastic decision approach, is put forward. Firstly, optimal radar measurements' scheduling is obtained by the method of maximizing determinant of the Fisher information matrix of radar and IRST measurements, which is managed by the expert system. Then, suggested a "pseudo sensor" to predict the possible target position using the polynomial method based on the radar and IRST measurements, using "pseudo sensor" model to estimate the target position even if the radar is turned off. At last, based on the tracking performance and the state of target maneuver, fuzzy stochastic decision is used to adjust the optimal radar scheduling and retrieve the module parameter of "pseudo sensor". The experiment result indicates that the algorithm can not only limit Radar activity effectively but also keep the tracking accuracy of active/passive system well. And this algorithm eliminates the drawback of traditional Radar management methods that the Radar activity is fixed and not easy to control and protect.

Visual tracking using neuromorphic asynchronous event-based cameras.

PubMed

Ni, Zhenjiang; Ieng, Sio-Hoi; Posch, Christoph; Régnier, Stéphane; Benosman, Ryad

2015-04-01

This letter presents a novel computationally efficient and robust pattern tracking method based on a time-encoded, frame-free visual data. Recent interdisciplinary developments, combining inputs from engineering and biology, have yielded a novel type of camera that encodes visual information into a continuous stream of asynchronous, temporal events. These events encode temporal contrast and intensity locally in space and time. We show that the sparse yet accurately timed information is well suited as a computational input for object tracking. In this letter, visual data processing is performed for each incoming event at the time it arrives. The method provides a continuous and iterative estimation of the geometric transformation between the model and the events representing the tracked object. It can handle isometry, similarities, and affine distortions and allows for unprecedented real-time performance at equivalent frame rates in the kilohertz range on a standard PC. Furthermore, by using the dimension of time that is currently underexploited by most artificial vision systems, the method we present is able to solve ambiguous cases of object occlusions that classical frame-based techniques handle poorly.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started

Vehicle response-based track geometry assessment using multi-body simulation

NASA Astrophysics Data System (ADS)

Kraft, Sönke; Causse, Julien; Coudert, Frédéric

2018-02-01

The assessment of the geometry of railway tracks is an indispensable requirement for safe rail traffic. Defects which represent a risk for the safety of the train have to be identified and the necessary measures taken. According to current standards, amplitude thresholds are applied to the track geometry parameters measured by recording cars. This geometry-based assessment has proved its value but suffers from the low correlation between the geometry parameters and the vehicle reactions. Experience shows that some defects leading to critical vehicle reactions are underestimated by this approach. The use of vehicle responses in the track geometry assessment process allows identifying critical defects and improving the maintenance operations. This work presents a vehicle response-based assessment method using multi-body simulation. The choice of the relevant operation conditions and the estimation of the simulation uncertainty are outlined. The defects are identified from exceedances of track geometry and vehicle response parameters. They are then classified using clustering methods and the correlation with vehicle response is analysed. The use of vehicle responses allows the detection of critical defects which are not identified from geometry parameters.

Discriminating between intentional and unintentional gaze fixation using multimodal-based fuzzy logic algorithm for gaze tracking system with NIR camera sensor

NASA Astrophysics Data System (ADS)

Naqvi, Rizwan Ali; Park, Kang Ryoung

2016-06-01

Gaze tracking systems are widely used in human-computer interfaces, interfaces for the disabled, game interfaces, and for controlling home appliances. Most studies on gaze detection have focused on enhancing its accuracy, whereas few have considered the discrimination of intentional gaze fixation (looking at a target to activate or select it) from unintentional fixation while using gaze detection systems. Previous research methods based on the use of a keyboard or mouse button, eye blinking, and the dwell time of gaze position have various limitations. Therefore, we propose a method for discriminating between intentional and unintentional gaze fixation using a multimodal fuzzy logic algorithm applied to a gaze tracking system with a near-infrared camera sensor. Experimental results show that the proposed method outperforms the conventional method for determining gaze fixation.

Automatic tracking of red blood cells in micro channels using OpenCV

NASA Astrophysics Data System (ADS)

Rodrigues, Vânia; Rodrigues, Pedro J.; Pereira, Ana I.; Lima, Rui

2013-10-01

The present study aims to developan automatic method able to track red blood cells (RBCs) trajectories flowing through a microchannel using the Open Source Computer Vision (OpenCV). The developed method is based on optical flux calculation assisted by the maximization of the template-matching product. The experimental results show a good functional performance of this method.

Identifying and Tracking Solar Photospheric Bright Points Based on Three-dimensional Segmentation Technology

NASA Astrophysics Data System (ADS)

Xiong, J. P.; Zhang, A. L.; Ji, K. F.; Feng, S.; Deng, H.; Yang, Y. F.

2016-01-01

Photospheric bright points (PBPs) are tiny and short-lived phenomena which can be seen within dark inter-granular lanes. In this paper, we develop a new method to identify and track the PBPs in the three-dimensional data cube. Different from the previous way such as Detection-Before-Tracking, this method is based on the Tracking-While-Detection. Using this method, the whole lifetime of a PBP can be accurately measured while this PBP is possibly separated into several with Laplacian and morphological dilation (LMD) method due to its weak intensity sometimes. With consideration of the G-band PBPs observed by Hinode/SOT (Solar Optical Telescope) for more than two hours, we find that the isolated PBPs have an average lifetime of 3 minutes, and the longest one is up to 27 minutes, which are greater than the values detected by the previous LMD method. Furthermore, we also find that the mean intensity of PBPs is 1.02 times of the mean photospheric intensity, which is less than the values detected by LMD method, and the intensity of PBPs presents a period of oscillation with 2-3 minutes during the whole lifetime.

Simulations in the Analysis of Experimental Data Measured by BM@N Drift Chambers

NASA Astrophysics Data System (ADS)

Fedorišin, Ján

2018-02-01

The drift chambers (DCH's) are an important part of the tracking system of the BM@N experiment designed to study the production of baryonic matter at the Nuclotron energies. The method of particle hit and track reconstruction in the drift chambers has been already proposed and tested on the BM@N deuteron beam data. In this study the DCH's are first locally and globally aligned, and subsequently the consistency of the track reconstruction chain is tested by two methods. The first one is based on the backward extrapolation of the DCH reconstructed deuteron beam to a position where its deflection in the BM@N magnetic field begins. The second method reconstructs the deuteron beam momentum through its deflection angle. Both methods confirm correctness of the track reconstruction algorithm.

A geometric method for computing ocular kinematics and classifying gaze events using monocular remote eye tracking in a robotic environment.

PubMed

Singh, Tarkeshwar; Perry, Christopher M; Herter, Troy M

2016-01-26

Robotic and virtual-reality systems offer tremendous potential for improving assessment and rehabilitation of neurological disorders affecting the upper extremity. A key feature of these systems is that visual stimuli are often presented within the same workspace as the hands (i.e., peripersonal space). Integrating video-based remote eye tracking with robotic and virtual-reality systems can provide an additional tool for investigating how cognitive processes influence visuomotor learning and rehabilitation of the upper extremity. However, remote eye tracking systems typically compute ocular kinematics by assuming eye movements are made in a plane with constant depth (e.g. frontal plane). When visual stimuli are presented at variable depths (e.g. transverse plane), eye movements have a vergence component that may influence reliable detection of gaze events (fixations, smooth pursuits and saccades). To our knowledge, there are no available methods to classify gaze events in the transverse plane for monocular remote eye tracking systems. Here we present a geometrical method to compute ocular kinematics from a monocular remote eye tracking system when visual stimuli are presented in the transverse plane. We then use the obtained kinematics to compute velocity-based thresholds that allow us to accurately identify onsets and offsets of fixations, saccades and smooth pursuits. Finally, we validate our algorithm by comparing the gaze events computed by the algorithm with those obtained from the eye-tracking software and manual digitization. Within the transverse plane, our algorithm reliably differentiates saccades from fixations (static visual stimuli) and smooth pursuits from saccades and fixations when visual stimuli are dynamic. The proposed methods provide advancements for examining eye movements in robotic and virtual-reality systems. Our methods can also be used with other video-based or tablet-based systems in which eye movements are performed in a peripersonal plane with variable depth.

Dynamic electronic collimation method for 3-D catheter tracking on a scanning-beam digital x-ray system

PubMed Central

Dunkerley, David A. P.; Slagowski, Jordan M.; Funk, Tobias; Speidel, Michael A.

2017-01-01

Abstract. Scanning-beam digital x-ray (SBDX) is an inverse geometry x-ray fluoroscopy system capable of tomosynthesis-based 3-D catheter tracking. This work proposes a method of dose-reduced 3-D catheter tracking using dynamic electronic collimation (DEC) of the SBDX scanning x-ray tube. This is achieved through the selective deactivation of focal spot positions not needed for the catheter tracking task. The technique was retrospectively evaluated with SBDX detector data recorded during a phantom study. DEC imaging of a catheter tip at isocenter required 340 active focal spots per frame versus 4473 spots in full field-of-view (FOV) mode. The dose-area product (DAP) and peak skin dose (PSD) for DEC versus full FOV scanning were calculated using an SBDX Monte Carlo simulation code. The average DAP was reduced to 7.8% of the full FOV value, consistent with the relative number of active focal spots (7.6%). For image sequences with a moving catheter, PSD was 33.6% to 34.8% of the full FOV value. The root-mean-squared-deviation between DEC-based 3-D tracking coordinates and full FOV 3-D tracking coordinates was less than 0.1 mm. The 3-D distance between the tracked tip and the sheath centerline averaged 0.75 mm. DEC is a feasible method for dose reduction during SBDX 3-D catheter tracking. PMID:28439521

Dual-color multiple-particle tracking at 50-nm localization and over 100-µm range in 3D with temporal focusing two-photon microscopy

PubMed Central

Ding, Yu; Li, Chunqiang

2016-01-01

Nanoscale particle tracking in three dimensions is crucial to directly observe dynamics of molecules and nanoparticles in living cells. Here we present a three-dimensional particle tracking method based on temporally focused two-photon excitation. Multiple particles are imaged at 30 frames/s in volume up to 180 × 180 × 100 µm3. The spatial localization precision can reach 50 nm. We demonstrate its capability of tracking fast swimming microbes at speed of ~200 µm/s. Two-photon dual-color tracking is achieved by simultaneously exciting two kinds of fluorescent beads at 800 nm to demonstrate its potential in molecular interaction studies. Our method provides a simple wide-field fluorescence imaging approach for deep multiple-particle tracking. PMID:27867724

An object tracking method based on guided filter for night fusion image

NASA Astrophysics Data System (ADS)

Qian, Xiaoyan; Wang, Yuedong; Han, Lei

2016-01-01

Online object tracking is a challenging problem as it entails learning an effective model to account for appearance change caused by intrinsic and extrinsic factors. In this paper, we propose a novel online object tracking with guided image filter for accurate and robust night fusion image tracking. Firstly, frame difference is applied to produce the coarse target, which helps to generate observation models. Under the restriction of these models and local source image, guided filter generates sufficient and accurate foreground target. Then accurate boundaries of the target can be extracted from detection results. Finally timely updating for observation models help to avoid tracking shift. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-art methods.

Fast object reconstruction in block-based compressive low-light-level imaging

NASA Astrophysics Data System (ADS)

Ke, Jun; Sui, Dong; Wei, Ping

2014-11-01

In this paper we propose a simply yet effective and efficient method for long-term object tracking. Different from traditional visual tracking method which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion problem. To summarize, our algorithm can be roughly decomposed in a initialization stage and a tracking stage. In the initialization stage, an offline classifier is trained to get the object appearance information in category level. When the video stream is coming, the pre-trained offline classifier is used for detecting the potential target and initializing the tracking stage. In the tracking stage, it consists of three parts which are online tracking part, offline tracking part and confidence judgment part. Online tracking part captures the specific target appearance information while detection part localizes the object based on the pre-trained offline classifier. Since there is no data dependence between online tracking and offline detection, these two parts are running in parallel to significantly improve the processing speed. A confidence selection mechanism is proposed to optimize the object location. Besides, we also propose a simple mechanism to judge the absence of the object. If the target is lost, the pre-trained offline classifier is utilized to re-initialize the whole algorithm as long as the target is re-located. During experiment, we evaluate our method on several challenging video sequences and demonstrate competitive results.

Real-time seam tracking control system based on line laser visions

NASA Astrophysics Data System (ADS)

Zou, Yanbiao; Wang, Yanbo; Zhou, Weilin; Chen, Xiangzhi

2018-07-01

A set of six-degree-of-freedom robotic welding automatic tracking platform was designed in this study to realize the real-time tracking of weld seams. Moreover, the feature point tracking method and the adaptive fuzzy control algorithm in the welding process were studied and analyzed. A laser vision sensor and its measuring principle were designed and studied, respectively. Before welding, the initial coordinate values of the feature points were obtained using morphological methods. After welding, the target tracking method based on Gaussian kernel was used to extract the real-time feature points of the weld. An adaptive fuzzy controller was designed to input the deviation value of the feature points and the change rate of the deviation into the controller. The quantization factors, scale factor, and weight function were adjusted in real time. The input and output domains, fuzzy rules, and membership functions were constantly updated to generate a series of smooth bias robot voltage. Three groups of experiments were conducted on different types of curve welds in a strong arc and splash noise environment using the welding current of 120 A short-circuit Metal Active Gas (MAG) Arc Welding. The tracking error was less than 0.32 mm and the sensor's metrical frequency can be up to 20 Hz. The end of the torch run smooth during welding. Weld trajectory can be tracked accurately, thereby satisfying the requirements of welding applications.

Autonomous antenna tracking system for mobile symphonie ground stations

NASA Technical Reports Server (NTRS)

Ernsberger, K.; Lorch, G.; Waffenschmidt, E.

1982-01-01

The implementation of a satellite tracking and antenna control system is described. Due to the loss of inclination control for the symphonie satellites, it became necessary to equip the parabolic antennas of the mobile Symphonie ground station with tracking facilities. For the relatively low required tracking accuracy of 0.5 dB, a low cost, step track system was selected. The step track system developed for this purpose and tested over a long period of time in 7 ground stations is based on a search step method with subsequent parabola interpolation. As compared with the real search step method, the system has the advantage of a higher pointing angle resolution, and thus a higher tracking accuracy. When the pilot signal has been switched off for a long period of time, as for instance after the eclipse, the antenna is repointed towards the satellite by an automatically initiated spiral search scan. The function and design of the tracking system are detailed, while easy handling and tracking results.

QUO VADIS SOURCE TRACKING? TOWARDS A STRATEGIC FRAMEWORK FOR ENVIRONMENTAL MONITORING OF FECAL POLLUTION

EPA Science Inventory

Advances in microbial source tracking (MST) have largely been driven by the need to comply with water quality standards based on traditional indicator bacteria. Recently, a number of PCR-based, culture- and library-independent methods have been gaining popularity among source tra...

Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

NASA Astrophysics Data System (ADS)

Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

2008-02-01

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

The efficacy of obtaining genetic-based identifications from putative wolverine snow tracks

Treesearch

Todd J. Ulizio; John R. Squires; Daniel H. Pletscher; Michael K. Schwartz; James J. Claar; Leonard F. Ruggiero

2006-01-01

Snow-track surveys to detect rare carnivores require unequivocal species identification because of management and political ramifications associated with the presence of such species. Collecting noninvasive genetic samples from putative wolverine (Gulo gulo) snow tracks is an effective method for providing definitive species identification for use in presence-...

A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking

PubMed Central

Shafiee, Mohammad Javad; Azimifar, Zohreh; Wong, Alexander

2015-01-01

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering. PMID:26313943

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

PubMed

Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

2015-01-01

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

Robust visual tracking via multiscale deep sparse networks

NASA Astrophysics Data System (ADS)

Wang, Xin; Hou, Zhiqiang; Yu, Wangsheng; Xue, Yang; Jin, Zefenfen; Dai, Bo

2017-04-01

In visual tracking, deep learning with offline pretraining can extract more intrinsic and robust features. It has significant success solving the tracking drift in a complicated environment. However, offline pretraining requires numerous auxiliary training datasets and is considerably time-consuming for tracking tasks. To solve these problems, a multiscale sparse networks-based tracker (MSNT) under the particle filter framework is proposed. Based on the stacked sparse autoencoders and rectifier linear unit, the tracker has a flexible and adjustable architecture without the offline pretraining process and exploits the robust and powerful features effectively only through online training of limited labeled data. Meanwhile, the tracker builds four deep sparse networks of different scales, according to the target's profile type. During tracking, the tracker selects the matched tracking network adaptively in accordance with the initial target's profile type. It preserves the inherent structural information more efficiently than the single-scale networks. Additionally, a corresponding update strategy is proposed to improve the robustness of the tracker. Extensive experimental results on a large scale benchmark dataset show that the proposed method performs favorably against state-of-the-art methods in challenging environments.

High-speed autofocusing of a cell using diffraction pattern

NASA Astrophysics Data System (ADS)

Oku, Hiromasa; Ishikawa, Masatoshi; Theodorus; Hashimoto, Koichi

2006-05-01

This paper proposes a new autofocusing method for observing cells under a transmission illumination. The focusing method uses a quick and simple focus estimation technique termed “depth from diffraction,” which is based on a diffraction pattern in a defocused image of a biological specimen. Since this method can estimate the focal position of the specimen from only a single defocused image, it can easily realize high-speed autofocusing. To demonstrate the method, it was applied to continuous focus tracking of a swimming paramecium, in combination with two-dimensional position tracking. Three-dimensional tracking of the paramecium for 70 s was successfully demonstrated.

Relative Displacement Method for Track-Structure Interaction

PubMed Central

Ramos, Óscar Ramón; Pantaleón, Marcos J.

2014-01-01

The track-structure interaction effects are usually analysed with conventional FEM programs, where it is difficult to implement the complex track-structure connection behaviour, which is nonlinear, elastic-plastic and depends on the vertical load. The authors developed an alternative analysis method, which they call the relative displacement method. It is based on the calculation of deformation states in single DOF element models that satisfy the boundary conditions. For its solution, an iterative optimisation algorithm is used. This method can be implemented in any programming language or analysis software. A comparison with ABAQUS calculations shows a very good result correlation and compliance with the standard's specifications. PMID:24634610

Electromagnetic tracking for abdominal interventions in computer aided surgery

PubMed Central

Zhang, Hui; Banovac, Filip; Lin, Ralph; Glossop, Neil; Wood, Bradford J.; Lindisch, David; Levy, Elliot; Cleary, Kevin

2014-01-01

Electromagnetic tracking has great potential for assisting physicians in precision placement of instruments during minimally invasive interventions in the abdomen, since electromagnetic tracking is not limited by the line-of-sight restrictions of optical tracking. A new generation of electromagnetic tracking has recently become available, with sensors small enough to be included in the tips of instruments. To fully exploit the potential of this technology, our research group has been developing a computer aided, image-guided system that uses electromagnetic tracking for visualization of the internal anatomy during abdominal interventions. As registration is a critical component in developing an accurate image-guided system, we present three registration techniques: 1) enhanced paired-point registration (time-stamp match registration and dynamic registration); 2) orientation-based registration; and 3) needle shape-based registration. Respiration compensation is another important issue, particularly in the abdomen, where respiratory motion can make precise targeting difficult. To address this problem, we propose reference tracking and affine transformation methods. Finally, we present our prototype navigation system, which integrates the registration, segmentation, path-planning and navigation functions to provide real-time image guidance in the clinical environment. The methods presented here have been tested with a respiratory phantom specially designed by our group and in swine animal studies under approved protocols. Based on these tests, we conclude that our system can provide quick and accurate localization of tracked instruments in abdominal interventions, and that it offers a user friendly display for the physician. PMID:16829506

Automatic electronic fish tracking system

NASA Technical Reports Server (NTRS)

Osborne, P. W.; Hoffman, E.; Merriner, J. V.; Richards, C. E.; Lovelady, R. W.

1976-01-01

A newly developed electronic fish tracking system to automatically monitor the movements and migratory habits of fish is reported. The system is aimed particularly at studies of effects on fish life of industrial facilities which use rivers or lakes to dump their effluents. Location of fish is acquired by means of acoustic links from the fish to underwater Listening Stations, and by radio links which relay tracking information to a shore-based Data Base. Fish over 4 inches long may be tracked over a 5 x 5 mile area. The electronic fish tracking system provides the marine scientist with electronics which permit studies that were not practical in the past and which are cost-effective compared to manual methods.

[Evaluation of PAE and AE for identifying generalized tracks using snakes in Hidalgo, Mexico].

PubMed

Montiel-Canales, Gustavo; Mayer-Goyenechea, Irene Goyenechea; Fernández Badillo, Leonardo; Castillo Cerón, Jesús M

2016-12-01

One of the most important concepts in Panbiogeography is the generalized track, which represents an ancestral biota fragmented by geological events that can be recovered through several methods, including Parsimony analysis of endemicity (PAE) and endemicity analysis (EA). PAE has been frequently used to identify generalized tracks, while EA is primarily designed to find areas of endemicity, but has been recently proposed for identifying generalized tracks as well. In this study we evaluated these methods to find generalized tracks using the distribution of the 84 snake species of Hidalgo. PAE found one generalized track from three individual tracks (Agkistrodon taylori, Crotalus totonacus and Pliocercus elapoides), supported by 89 % of Bootstrap, and EA identified two generalized tracks, with endemicity index values of 2.71-2.96 and 2.84-3.09, respectively. Those areas were transformed to generalized tracks. The first generalized track was retrieved from three individual tracks (Micrurus bernadi, Rhadinaea marcellae and R. quinquelineata), and the second was recovered from two individual tracks (Geophis mutitorques and Thamnophis sumichrasti). These generalized tracks can be considered a unique distribution pattern, because they resembled each other and agreed in shape. When comparing both methods, we noted that both are useful for identifying generalized tracks, and although they can be used independently, we suggest their complementary use. Nevertheless, to obtain accurate results, it is useful to consider theoretical bases of both methods, along with an appropriate choice of the size of the area. Results using small-grid size in EA are ideal for searching biogeographical patterns within geopolitical limits. Furthermore, they can be used for conservation proposals at state level where endemic species become irreplaceable, and where losing them would imply the extinction of unique lineages.

Terminal Sliding Mode Tracking Controller Design for Automatic Guided Vehicle

NASA Astrophysics Data System (ADS)

Chen, Hongbin

2018-03-01

Based on sliding mode variable structure control theory, the path tracking problem of automatic guided vehicle is studied, proposed a controller design method based on the terminal sliding mode. First of all, through analyzing the characteristics of the automatic guided vehicle movement, the kinematics model is presented. Then to improve the traditional expression of terminal sliding mode, design a nonlinear sliding mode which the convergence speed is faster than the former, verified by theoretical analysis, the design of sliding mode is steady and fast convergence in the limited time. Finally combining Lyapunov method to design the tracking control law of automatic guided vehicle, the controller can make the automatic guided vehicle track the desired trajectory in the global sense as well as in finite time. The simulation results verify the correctness and effectiveness of the control law.

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Visual tracking of da Vinci instruments for laparoscopic surgery

NASA Astrophysics Data System (ADS)

Speidel, S.; Kuhn, E.; Bodenstedt, S.; Röhl, S.; Kenngott, H.; Müller-Stich, B.; Dillmann, R.

2014-03-01

Intraoperative tracking of laparoscopic instruments is a prerequisite to realize further assistance functions. Since endoscopic images are always available, this sensor input can be used to localize the instruments without special devices or robot kinematics. In this paper, we present an image-based markerless 3D tracking of different da Vinci instruments in near real-time without an explicit model. The method is based on different visual cues to segment the instrument tip, calculates a tip point and uses a multiple object particle filter for tracking. The accuracy and robustness is evaluated with in vivo data.

Online Object Tracking, Learning and Parsing with And-Or Graphs.

PubMed

Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

2017-12-01

This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

Locomotive track detection for underground

NASA Astrophysics Data System (ADS)

Ma, Zhonglei; Lang, Wenhui; Li, Xiaoming; Wei, Xing

2017-08-01

In order to improve the PC-based track detection system, this paper proposes a method to detect linear track for underground locomotive based on DSP + FPGA. Firstly, the analog signal outputted from the camera is sampled by A / D chip. Then the collected digital signal is preprocessed by FPGA. Secondly, the output signal of FPGA is transmitted to DSP via EMIF port. Subsequently, the adaptive threshold edge detection, polar angle and radius constrain based Hough transform are implemented by DSP. Lastly, the detected track information is transmitted to host computer through Ethernet interface. The experimental results show that the system can not only meet the requirements of real-time detection, but also has good robustness.

[A review of progress of real-time tumor tracking radiotherapy technology based on dynamic multi-leaf collimator].

PubMed

Liu, Fubo; Li, Guangjun; Shen, Jiuling; Li, Ligin; Bai, Sen

2017-02-01

While radiation treatment to patients with tumors in thorax and abdomen is being performed, further improvement of radiation accuracy is restricted by the tumor intra-fractional motion due to respiration. Real-time tumor tracking radiation is an optimal solution to tumor intra-fractional motion. A review of the progress of real-time dynamic multi-leaf collimator(DMLC) tracking is provided in the present review, including DMLC tracking method, time lag of DMLC tracking system, and dosimetric verification.

Calibration-free gaze tracking for automatic measurement of visual acuity in human infants.

PubMed

Xiong, Chunshui; Huang, Lei; Liu, Changping

2014-01-01

Most existing vision-based methods for gaze tracking need a tedious calibration process. In this process, subjects are required to fixate on a specific point or several specific points in space. However, it is hard to cooperate, especially for children and human infants. In this paper, a new calibration-free gaze tracking system and method is presented for automatic measurement of visual acuity in human infants. As far as I know, it is the first time to apply the vision-based gaze tracking in the measurement of visual acuity. Firstly, a polynomial of pupil center-cornea reflections (PCCR) vector is presented to be used as the gaze feature. Then, Gaussian mixture models (GMM) is employed for gaze behavior classification, which is trained offline using labeled data from subjects with healthy eyes. Experimental results on several subjects show that the proposed method is accurate, robust and sufficient for the application of measurement of visual acuity in human infants.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

2010-04-01

In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

Emitter signal separation method based on multi-level digital channelization

NASA Astrophysics Data System (ADS)

Han, Xun; Ping, Yifan; Wang, Sujun; Feng, Ying; Kuang, Yin; Yang, Xinquan

2018-02-01

To solve the problem of emitter separation under complex electromagnetic environment, a signal separation method based on multi-level digital channelization is proposed in this paper. A two-level structure which can divide signal into different channel is designed first, after that, the peaks of different channels are tracked using the track filter and the coincident signals in time domain are separated in time-frequency domain. Finally, the time domain waveforms of different signals are acquired by reverse transformation. The validness of the proposed method is proved by experiment.

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments.

PubMed

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-13

Tracking people's behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people's access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people's access behaviors can be correctly tracked within a one-second delay.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments

PubMed Central

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-01

Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people’s access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people’s access behaviors can be correctly tracked within a one-second delay. PMID:28098772

Sliding mode output feedback control based on tracking error observer with disturbance estimator.

PubMed

Xiao, Lingfei; Zhu, Yue

2014-07-01

For a class of systems who suffers from disturbances, an original output feedback sliding mode control method is presented based on a novel tracking error observer with disturbance estimator. The mathematical models of the systems are not required to be with high accuracy, and the disturbances can be vanishing or nonvanishing, while the bounds of disturbances are unknown. By constructing a differential sliding surface and employing reaching law approach, a sliding mode controller is obtained. On the basis of an extended disturbance estimator, a creative tracking error observer is produced. By using the observation of tracking error and the estimation of disturbance, the sliding mode controller is implementable. It is proved that the disturbance estimation error and tracking observation error are bounded, the sliding surface is reachable and the closed-loop system is robustly stable. The simulations on a servomotor positioning system and a five-degree-of-freedom active magnetic bearings system verify the effect of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

More than just tracking time: Complex measures of user engagement with an internet-based health promotion intervention.

PubMed

Baltierra, Nina B; Muessig, Kathryn E; Pike, Emily C; LeGrand, Sara; Bull, Sheana S; Hightow-Weidman, Lisa B

2016-02-01

There has been a rise in internet-based health interventions without a concomitant focus on new methods to measure user engagement and its effect on outcomes. We describe current user tracking methods for internet-based health interventions and offer suggestions for improvement based on the design and pilot testing of healthMpowerment.org (HMP). HMP is a multi-component online intervention for young Black men and transgender women who have sex with men (YBMSM/TW) to reduce risky sexual behaviors, promote healthy living and build social support. The intervention is non-directive, incorporates interactive features, and utilizes a point-based reward system. Fifteen YBMSM/TW (age 20-30) participated in a one-month pilot study to test the usability and efficacy of HMP. Engagement with the intervention was tracked using a customized data capture system and validated with Google Analytics. Usage was measured in time spent (total and across sections) and points earned. Average total time spent on HMP was five hours per person (range 0-13). Total time spent was correlated with total points earned and overall site satisfaction. Measuring engagement in internet-based interventions is crucial to determining efficacy. Multiple methods of tracking helped derive more comprehensive user profiles. Results highlighted the limitations of measures to capture user activity and the elusiveness of the concept of engagement. Copyright © 2016 Elsevier Inc. All rights reserved.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

Visual tracking is an active research topic in the field of computer vision and has been well studied in the last decades. The method based on multiple instance learning (MIL) was recently introduced into the tracking task, which can solve the problem that template drift well. However, MIL method has relatively poor performance in running efficiency and accuracy, due to its strong classifiers updating strategy is complicated, and the speed of the classifiers update is not always same with the change of the targets' appearance. In this paper, we present a novel online effective MIL (EMIL) tracker. A new update strategy for strong classifier was proposed to improve the running efficiency of MIL method. In addition, to improve the t racking accuracy and stability of the MIL method, a new dynamic mechanism for learning rate renewal of the classifier and variable search window were proposed. Experimental results show that our method performs good performance under the complex scenes, with strong stability and high efficiency.

Development and applications of single particle orientation and rotational tracking in dynamic systems

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

Chen, Kuangcai

The goal of this study is to help with future data analysis and experiment designs in rotational dynamics research using DIC-based SPORT technique. Most of the current studies using DIC-based SPORT techniques are technical demonstrations. Understanding the mechanisms behind the observed rotational behaviors of the imaging probes should be the focus of the future SPORT studies. More efforts are still needed in the development of new imaging probes, particle tracking methods, instrumentations, and advanced data analysis methods to further extend the potential of DIC-based SPORT technique.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Lin, Tong; Cerviño, Laura I.; Tang, Xiaoli; Vasconcelos, Nuno; Jiang, Steve B.

2009-02-01

Accurate lung tumor tracking in real time is a keystone to image-guided radiotherapy of lung cancers. Existing lung tumor tracking approaches can be roughly grouped into three categories: (1) deriving tumor position from external surrogates; (2) tracking implanted fiducial markers fluoroscopically or electromagnetically; (3) fluoroscopically tracking lung tumor without implanted fiducial markers. The first approach suffers from insufficient accuracy, while the second may not be widely accepted due to the risk of pneumothorax. Previous studies in fluoroscopic markerless tracking are mainly based on template matching methods, which may fail when the tumor boundary is unclear in fluoroscopic images. In this paper we propose a novel markerless tumor tracking algorithm, which employs the correlation between the tumor position and surrogate anatomic features in the image. The positions of the surrogate features are not directly tracked; instead, we use principal component analysis of regions of interest containing them to obtain parametric representations of their motion patterns. Then, the tumor position can be predicted from the parametric representations of surrogates through regression. Four regression methods were tested in this study: linear and two-degree polynomial regression, artificial neural network (ANN) and support vector machine (SVM). The experimental results based on fluoroscopic sequences of ten lung cancer patients demonstrate a mean tracking error of 2.1 pixels and a maximum error at a 95% confidence level of 4.6 pixels (pixel size is about 0.5 mm) for the proposed tracking algorithm.

Tracking quasi-stationary flow of weak fluorescent signals by adaptive multi-frame correlation.

PubMed

Ji, L; Danuser, G

2005-12-01

We have developed a novel cross-correlation technique to probe quasi-stationary flow of fluorescent signals in live cells at a spatial resolution that is close to single particle tracking. By correlating image blocks between pairs of consecutive frames and integrating their correlation scores over multiple frame pairs, uncertainty in identifying a globally significant maximum in the correlation score function has been greatly reduced as compared with conventional correlation-based tracking using the signal of only two consecutive frames. This approach proves robust and very effective in analysing images with a weak, noise-perturbed signal contrast where texture characteristics cannot be matched between only a pair of frames. It can also be applied to images that lack prominent features that could be utilized for particle tracking or feature-based template matching. Furthermore, owing to the integration of correlation scores over multiple frames, the method can handle signals with substantial frame-to-frame intensity variation where conventional correlation-based tracking fails. We tested the performance of the method by tracking polymer flow in actin and microtubule cytoskeleton structures labelled at various fluorophore densities providing imagery with a broad range of signal modulation and noise. In applications to fluorescent speckle microscopy (FSM), where the fluorophore density is sufficiently low to reveal patterns of discrete fluorescent marks referred to as speckles, we combined the multi-frame correlation approach proposed above with particle tracking. This hybrid approach allowed us to follow single speckles robustly in areas of high speckle density and fast flow, where previously published FSM analysis methods were unsuccessful. Thus, we can now probe cytoskeleton polymer dynamics in living cells at an entirely new level of complexity and with unprecedented detail.

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

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

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

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

A linear complementarity method for the solution of vertical vehicle-track interaction

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gao, Qiang; Wu, Feng; Zhong, Wan-Xie

2018-02-01

A new method is proposed for the solution of the vertical vehicle-track interaction including a separation between wheel and rail. The vehicle is modelled as a multi-body system using rigid bodies, and the track is treated as a three-layer beam model in which the rail is considered as an Euler-Bernoulli beam and both the sleepers and the ballast are represented by lumped masses. A linear complementarity formulation is directly established using a combination of the wheel-rail normal contact condition and the generalised-α method. This linear complementarity problem is solved using the Lemke algorithm, and the wheel-rail contact force can be obtained. Then the dynamic responses of the vehicle and the track are solved without iteration based on the generalised-α method. The same equations of motion for the vehicle and track are adopted at the different wheel-rail contact situations. This method can remove some restrictions, that is, time-dependent mass, damping and stiffness matrices of the coupled system, multiple equations of motion for the different contact situations and the effect of the contact stiffness. Numerical results demonstrate that the proposed method is effective for simulating the vehicle-track interaction including a separation between wheel and rail.

An algorithm to track laboratory zebrafish shoals.

PubMed

Feijó, Gregory de Oliveira; Sangalli, Vicenzo Abichequer; da Silva, Isaac Newton Lima; Pinho, Márcio Sarroglia

2018-05-01

In this paper, a semi-automatic multi-object tracking method to track a group of unmarked zebrafish is proposed. This method can handle partial occlusion cases, maintaining the correct identity of each individual. For every object, we extracted a set of geometric features to be used in the two main stages of the algorithm. The first stage selected the best candidate, based both on the blobs identified in the image and the estimate generated by a Kalman Filter instance. In the second stage, if the same candidate-blob is selected by two or more instances, a blob-partitioning algorithm takes place in order to split this blob and reestablish the instances' identities. If the algorithm cannot determine the identity of a blob, a manual intervention is required. This procedure was compared against a manual labeled ground truth on four video sequences with different numbers of fish and spatial resolution. The performance of the proposed method is then compared against two well-known zebrafish tracking methods found in the literature: one that treats occlusion scenarios and one that only track fish that are not in occlusion. Based on the data set used, the proposed method outperforms the first method in correctly separating fish in occlusion, increasing its efficiency by at least 8.15% of the cases. As for the second, the proposed method's overall performance outperformed the second in some of the tested videos, especially those with lower image quality, because the second method requires high-spatial resolution images, which is not a requirement for the proposed method. Yet, the proposed method was able to separate fish involved in occlusion and correctly assign its identity in up to 87.85% of the cases, without accounting for user intervention. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative study of performance of neutral axis tracking based damage detection

NASA Astrophysics Data System (ADS)

Soman, R.; Malinowski, P.; Ostachowicz, W.

2015-07-01

This paper presents a comparative study of a novel SHM technique for damage isolation. The performance of the Neutral Axis (NA) tracking based damage detection strategy is compared to other popularly used vibration based damage detection methods viz. ECOMAC, Mode Shape Curvature Method and Strain Flexibility Index Method. The sensitivity of the novel method is compared under changing ambient temperature conditions and in the presence of measurement noise. Finite Element Analysis (FEA) of the DTU 10 MW Wind Turbine was conducted to compare the local damage identification capability of each method and the results are presented. Under the conditions examined, the proposed method was found to be robust to ambient condition changes and measurement noise. The damage identification in some is either at par with the methods mentioned in the literature or better under the investigated damage scenarios.

Exploiting target amplitude information to improve multi-target tracking

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Blair, W. Dale

2006-05-01

Closely-spaced (but resolved) targets pose a challenge for measurement-to-track data association algorithms. Since the Mahalanobis distances between measurements collected on closely-spaced targets and tracks are similar, several elements of the corresponding kinematic measurement-to-track cost matrix are also similar. Lacking any other information on which to base assignments, it is not surprising that data association algorithms make mistakes. One ad hoc approach for mitigating this problem is to multiply the kinematic measurement-to-track likelihoods by amplitude likelihoods. However, this can actually be detrimental to the measurement-to-track association process. With that in mind, this paper pursues a rigorous treatment of the hypothesis probabilities for kinematic measurements and features. Three simple scenarios are used to demonstrate the impact of basing data association decisions on these hypothesis probabilities for Rayleigh, fixed-amplitude, and Rician targets. The first scenario assumes that the tracker carries two tracks but only one measurement is collected. This provides insight into more complex scenarios in which there are fewer measurements than tracks. The second scenario includes two measurements and one track. This extends naturally to the case with more measurements than tracks. Two measurements and two tracks are present in the third scenario, which provides insight into the performance of this method when the number of measurements equals the number of tracks. In all cases, basing data association decisions on the hypothesis probabilities leads to good results.

Parameterization-based tracking for the P2 experiment

NASA Astrophysics Data System (ADS)

Sorokin, Iurii

2017-08-01

The P2 experiment in Mainz aims to determine the weak mixing angle θW at low momentum transfer by measuring the parity-violating asymmetry of elastic electronproton scattering. In order to achieve the intended precision of Δ(sin2 θW)/sin2θW = 0:13% within the planned 10 000 hours of running the experiment has to operate at the rate of 1011 detected electrons per second. Although it is not required to measure the kinematic parameters of each individual electron, every attempt is made to achieve the highest possible throughput in the track reconstruction chain. In the present work a parameterization-based track reconstruction method is described. It is a variation of track following, where the results of the computation-heavy steps, namely the propagation of a track to the further detector plane, and the fitting, are pre-calculated, and expressed in terms of parametric analytic functions. This makes the algorithm extremely fast, and well-suited for an implementation on an FPGA. The method also takes implicitly into account the actual phase space distribution of the tracks already at the stage of candidate construction. Compared to a simple algorithm, that does not use such information, this allows reducing the combinatorial background by many orders of magnitude, down to O(1) background candidate per one signal track. The method is developed specifically for the P2 experiment in Mainz, and the presented implementation is tightly coupled to the experimental conditions.

Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors

PubMed Central

2017-01-01

Fiber Bragg Grating (FBG) sensors are among the most popular elements for fiber optic sensor networks used for the direct measurement of temperature and strain. Modern FBG interrogation setups measure the FBG spectrum in real-time, and determine the shift of the Bragg wavelength of the FBG in order to estimate the physical parameters. The problem of determining the peak wavelength of the FBG from a spectral measurement limited in resolution and noise, is referred as the peak-tracking problem. In this work, the several peak-tracking approaches are reviewed and classified, outlining their algorithmic implementations: the methods based on direct estimation, interpolation, correlation, resampling, transforms, and optimization are discussed in all their proposed implementations. Then, a simulation based on coupled-mode theory compares the performance of the main peak-tracking methods, in terms of accuracy and signal to noise ratio resilience. PMID:29039804

New color-based tracking algorithm for joints of the upper extremities

NASA Astrophysics Data System (ADS)

Wu, Xiangping; Chow, Daniel H. K.; Zheng, Xiaoxiang

2007-11-01

To track the joints of the upper limb of stroke sufferers for rehabilitation assessment, a new tracking algorithm which utilizes a developed color-based particle filter and a novel strategy for handling occlusions is proposed in this paper. Objects are represented by their color histogram models and particle filter is introduced to track the objects within a probability framework. Kalman filter, as a local optimizer, is integrated into the sampling stage of the particle filter that steers samples to a region with high likelihood and therefore fewer samples is required. A color clustering method and anatomic constraints are used in dealing with occlusion problem. Compared with the general basic particle filtering method, the experimental results show that the new algorithm has reduced the number of samples and hence the computational consumption, and has achieved better abilities of handling complete occlusion over a few frames.

Joint polarization tracking and channel equalization based on radius-directed linear Kalman filter

NASA Astrophysics Data System (ADS)

Zhang, Qun; Yang, Yanfu; Zhong, Kangping; Liu, Jie; Wu, Xiong; Yao, Yong

2018-01-01

We propose a joint polarization tracking and channel equalization scheme based on radius-directed linear Kalman filter (RD-LKF) by introducing the butterfly finite-impulse-response (FIR) filter in our previously proposed RD-LKF method. Along with the fast polarization tracking, it can also simultaneously compensate the inter-symbol interference (ISI) effects including residual chromatic dispersion and polarization mode dispersion. Compared with the conventional radius-directed equalizer (RDE) algorithm, it is demonstrated experimentally that three times faster convergence speed, one order of magnitude better tracking capability, and better BER performance is obtained in polarization division multiplexing 16 quadrature amplitude modulation system. Besides, the influences of the algorithm parameters on the convergence and the tracking performance are investigated by numerical simulation.

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System.

PubMed

Xie, Ruihong; Zhang, Tao; Li, Jiaquan; Dai, Ming

2017-05-09

This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight) motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration) control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square) error is 1.253 mrad when tracking 10° 0.2 Hz signal.

Development of a railway wagon-track interaction model: Case studies on excited tracks

NASA Astrophysics Data System (ADS)

Xu, Lei; Chen, Xianmai; Li, Xuwei; He, Xianglin

2018-02-01

In this paper, a theoretical framework for modeling the railway wagon-ballast track interactions is presented, in which the dynamic equations of motion of wagon-track systems are constructed by effectively coupling the linear and nonlinear dynamic characteristics of system components. For the linear components, the energy-variational principle is directly used to derive their dynamic matrices, while for the nonlinear components, the dynamic equilibrium method is implemented to deduce the load vectors, based on which a novel railway wagon-ballast track interaction model is developed, and being validated by comparing with the experimental data measured from a heavy haul railway and another advanced model. With this study, extensive contributions in figuring out the critical speed of instability, limits and localizations of track irregularities over derailment accidents are presented by effectively integrating the dynamic simulation model, the track irregularity probabilistic model and time-frequency analysis method. The proposed approaches can provide crucial information to guarantee the running safety and stability of the wagon-track system when considering track geometries and various running speeds.

Discriminative correlation filter tracking with occlusion detection

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Chen, Zhong; Yu, XiPeng; Zhang, Ting; He, Jing

2018-03-01

Aiming at the problem that the correlation filter-based tracking algorithm can not track the target of severe occlusion, a target re-detection mechanism is proposed. First of all, based on the ECO, we propose the multi-peak detection model and the response value to distinguish the occlusion and deformation in the target tracking, which improve the success rate of tracking. And then we add the confidence model to update the mechanism to effectively prevent the model offset problem which due to similar targets or background during the tracking process. Finally, the redetection mechanism of the target is added, and the relocation is performed after the target is lost, which increases the accuracy of the target positioning. The experimental results demonstrate that the proposed tracker performs favorably against state-of-the-art methods in terms of robustness and accuracy.

Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking

PubMed Central

Wan, Y.; Hansen, C.

2018-01-01

Research on microscopy data from developing biological samples usually requires tracking individual cells over time. When cells are three-dimensionally and densely packed in a time-dependent scan of volumes, tracking results can become unreliable and uncertain. Not only are cell segmentation results often inaccurate to start with, but it also lacks a simple method to evaluate the tracking outcome. Previous cell tracking methods have been validated against benchmark data from real scans or artificial data, whose ground truth results are established by manual work or simulation. However, the wide variety of real-world data makes an exhaustive validation impossible. Established cell tracking tools often fail on new data, whose issues are also difficult to diagnose with only manual examinations. Therefore, data-independent tracking evaluation methods are desired for an explosion of microscopy data with increasing scale and resolution. In this paper, we propose the uncertainty footprint, an uncertainty quantification and visualization technique that examines nonuniformity at local convergence for an iterative evaluation process on a spatial domain supported by partially overlapping bases. We demonstrate that the patterns revealed by the uncertainty footprint indicate data processing quality in two algorithms from a typical cell tracking workflow – cell identification and association. A detailed analysis of the patterns further allows us to diagnose issues and design methods for improvements. A 4D cell tracking workflow equipped with the uncertainty footprint is capable of self diagnosis and correction for a higher accuracy than previous methods whose evaluation is limited by manual examinations. PMID:29456279

Method for dose-reduced 3D catheter tracking on a scanning-beam digital x-ray system using dynamic electronic collimation

NASA Astrophysics Data System (ADS)

Dunkerley, David A. P.; Funk, Tobias; Speidel, Michael A.

2016-03-01

Scanning-beam digital x-ray (SBDX) is an inverse geometry x-ray fluoroscopy system capable of tomosynthesis-based 3D catheter tracking. This work proposes a method of dose-reduced 3D tracking using dynamic electronic collimation (DEC) of the SBDX scanning x-ray tube. Positions in the 2D focal spot array are selectively activated to create a regionof- interest (ROI) x-ray field around the tracked catheter. The ROI position is updated for each frame based on a motion vector calculated from the two most recent 3D tracking results. The technique was evaluated with SBDX data acquired as a catheter tip inside a chest phantom was pulled along a 3D trajectory. DEC scans were retrospectively generated from the detector images stored for each focal spot position. DEC imaging of a catheter tip in a volume measuring 11.4 cm across at isocenter required 340 active focal spots per frame, versus 4473 spots in full-FOV mode. The dose-area-product (DAP) and peak skin dose (PSD) for DEC versus full field-of-view (FOV) scanning were calculated using an SBDX Monte Carlo simulation code. DAP was reduced to 7.4% to 8.4% of the full-FOV value, consistent with the relative number of active focal spots (7.6%). For image sequences with a moving catheter, PSD was 33.6% to 34.8% of the full-FOV value. The root-mean-squared-deviation between DEC-based 3D tracking coordinates and full-FOV 3D tracking coordinates was less than 0.1 mm. The 3D distance between the tracked tip and the sheath centerline averaged 0.75 mm. Dynamic electronic collimation can reduce dose with minimal change in tracking performance.

Multi-Stage Target Tracking with Drift Correction and Position Prediction

NASA Astrophysics Data System (ADS)

Chen, Xin; Ren, Keyan; Hou, Yibin

2018-04-01

Most existing tracking methods are hard to combine accuracy and performance, and do not consider the shift between clarity and blur that often occurs. In this paper, we propound a multi-stage tracking framework with two particular modules: position prediction and corrective measure. We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy. Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms. Then, we propose a position prediction module to reduce the computation cost and make tracker more capable of fast motion. Experimental result shows that our tracking method is more robust compared to others and more accurate on the benchmark sequences.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

An analysis of automatic human detection and tracking

NASA Astrophysics Data System (ADS)

Demuth, Philipe R.; Cosmo, Daniel L.; Ciarelli, Patrick M.

2015-12-01

This paper presents an automatic method to detect and follow people on video streams. This method uses two techniques to determine the initial position of the person at the beginning of the video file: one based on optical flow and the other one based on Histogram of Oriented Gradients (HOG). After defining the initial bounding box, tracking is done using four different trackers: Median Flow tracker, TLD tracker, Mean Shift tracker and a modified version of the Mean Shift tracker using HSV color space. The results of the methods presented in this paper are then compared at the end of the paper.

State Recognition of High Voltage Isolation Switch Based on Background Difference and Iterative Search

NASA Astrophysics Data System (ADS)

Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai

2018-03-01

The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.

A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique

NASA Astrophysics Data System (ADS)

Bocz, Péter; Vinkó, Ákos; Posgay, Zoltán

2018-03-01

This paper presents an automatic method for detecting vertical track irregularities on tramway operation using acceleration measurements on trams. For monitoring of tramway tracks, an unconventional measurement setup is developed, which records the data of 3-axes wireless accelerometers mounted on wheel discs. Accelerations are processed to obtain the vertical track irregularities to determine whether the track needs to be repaired. The automatic detection algorithm is based on time-frequency distribution analysis and determines the defect locations. Admissible limits (thresholds) are given for detecting moderate and severe defects using statistical analysis. The method was validated on frequented tram lines in Budapest and accurately detected severe defects with a hit rate of 100%, with no false alarms. The methodology is also sensitive to moderate and small rail surface defects at the low operational speed.

AN ALTERNATIVE CALIBRATION OF CR-39 DETECTORS FOR RADON DETECTION BEYOND THE SATURATION LIMIT.

PubMed

Franci, Daniele; Aureli, Tommaso; Cardellini, Francesco

2016-12-01

Time-integrated measurements of indoor radon levels are commonly carried out using solid-state nuclear track detectors (SSNTDs), due to the numerous advantages offered by this radiation detection technique. However, the use of SSNTD also presents some problems that may affect the accuracy of the results. The effect of overlapping tracks often results in the underestimation of the detected track density, which leads to the reduction of the counting efficiency for increasing radon exposure. This article aims to address the effect of overlapping tracks by proposing an alternative calibration technique based on the measurement of the fraction of the detector surface covered by alpha tracks. The method has been tested against a set of Monte Carlo data and then applied to a set of experimental data collected at the radon chamber of the Istituto Nazionale di Metrologia delle Radiazioni Ionizzanti, at the ENEA centre in Casaccia, using CR-39 detectors. It has been proved that the method allows to extend the detectable range of radon exposure far beyond the intrinsic limit imposed by the standard calibration based on the track density. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Vibro-acoustic performance of newly designed tram track structures

NASA Astrophysics Data System (ADS)

Haladin, Ivo; Lakušić, Stjepan; Ahac, Maja

2017-09-01

Rail vehicles in interaction with a railway structure induce vibrations that are propagating to surrounding structures and cause noise disturbance in the surrounding areas. Since tram tracks in urban areas often share the running surface with road vehicles one of top priorities is to achieve low maintenance and long lasting structure. Research conducted in scope of this paper gives an overview of newly designed tram track structures designated for use on Zagreb tram network and their performance in terms of noise and vibration mitigation. Research has been conducted on a 150 m long test section consisted of three tram track types: standard tram track structure commonly used on tram lines in Zagreb, optimized tram structure for better noise and vibration mitigation and a slab track with double sleepers embedded in a concrete slab, which presents an entirely new approach of tram track construction in Zagreb. Track has been instrumented with acceleration sensors, strain gauges and revision shafts for inspection. Relative deformations give an insight into track structure dynamic load distribution through the exploitation period. Further the paper describes vibro-acoustic measurements conducted at the test site. To evaluate the track performance from the vibro-acoustical standpoint, detailed analysis of track decay rate has been analysed. Opposed to measurement technique using impact hammer for track decay rate measurements, newly developed measuring technique using vehicle pass by vibrations as a source of excitation has been proposed and analysed. Paper gives overview of the method, it’s benefits compared to standard method of track decay rate measurements and method evaluation based on noise measurements of the vehicle pass by.

Comparing capacity value estimation techniques for photovoltaic solar power

DOE PAGES

Madaeni, Seyed Hossein; Sioshansi, Ramteen; Denholm, Paul

2012-09-28

In this paper, we estimate the capacity value of photovoltaic (PV) solar plants in the western U.S. Our results show that PV plants have capacity values that range between 52% and 93%, depending on location and sun-tracking capability. We further compare more robust but data- and computationally-intense reliability-based estimation techniques with simpler approximation methods. We show that if implemented properly, these techniques provide accurate approximations of reliability-based methods. Overall, methods that are based on the weighted capacity factor of the plant provide the most accurate estimate. As a result, we also examine the sensitivity of PV capacity value to themore » inclusion of sun-tracking systems.« less

WE-AB-303-08: Direct Lung Tumor Tracking Using Short Imaging Arcs

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

Shieh, C; Huang, C; Keall, P

2015-06-15

Purpose: Most current tumor tracking technologies rely on implanted markers, which suffer from potential toxicity of marker placement and mis-targeting due to marker migration. Several markerless tracking methods have been proposed: these are either indirect methods or have difficulties tracking lung tumors in most clinical cases due to overlapping anatomies in 2D projection images. We propose a direct lung tumor tracking algorithm robust to overlapping anatomies using short imaging arcs. Methods: The proposed algorithm tracks the tumor based on kV projections acquired within the latest six-degree imaging arc. To account for respiratory motion, an external motion surrogate is used tomore » select projections of the same phase within the latest arc. For each arc, the pre-treatment 4D cone-beam CT (CBCT) with tumor contours are used to estimate and remove the contribution to the integral attenuation from surrounding anatomies. The position of the tumor model extracted from 4D CBCT of the same phase is then optimized to match the processed projections using the conjugate gradient method. The algorithm was retrospectively validated on two kV scans of a lung cancer patient with implanted fiducial markers. This patient was selected as the tumor is attached to the mediastinum, representing a challenging case for markerless tracking methods. The tracking results were converted to expected marker positions and compared with marker trajectories obtained via direct marker segmentation (ground truth). Results: The root-mean-squared-errors of tracking were 0.8 mm and 0.9 mm in the superior-inferior direction for the two scans. Tracking error was found to be below 2 and 3 mm for 90% and 98% of the time, respectively. Conclusions: A direct lung tumor tracking algorithm robust to overlapping anatomies was proposed and validated on two scans of a lung cancer patient. Sub-millimeter tracking accuracy was observed, indicating the potential of this algorithm for real-time guidance applications.« less

Multiple template-based fluoroscopic tracking of lung tumor mass without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Gregory C.; Alexander, Brian; Jiang, Steve B.

2007-10-01

Precise lung tumor localization in real time is particularly important for some motion management techniques, such as respiratory gating or beam tracking with a dynamic multi-leaf collimator, due to the reduced clinical tumor volume (CTV) to planning target volume (PTV) margin and/or the escalated dose. There might be large uncertainties in deriving tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using a template matching method (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007 Phys. Med. Biol. 52 741-55). In this paper, we present an extension of this method to multiple-template matching for directly tracking the lung tumor mass in fluoroscopy video. The basic idea is as follows: (i) during the patient setup session, a pair of orthogonal fluoroscopic image sequences are taken and processed off-line to generate a set of reference templates that correspond to different breathing phases and tumor positions; (ii) during treatment delivery, fluoroscopic images are continuously acquired and processed; (iii) the similarity between each reference template and the processed incoming image is calculated; (iv) the tumor position in the incoming image is then estimated by combining the tumor centroid coordinates in reference templates with proper weights based on the measured similarities. With different handling of image processing and similarity calculation, two such multiple-template tracking techniques have been developed: one based on motion-enhanced templates and Pearson's correlation score while the other based on eigen templates and mean-squared error. The developed techniques have been tested on six sequences of fluoroscopic images from six lung cancer patients against the reference tumor positions manually determined by a radiation oncologist. The tumor centroid coordinates automatically detected using both methods agree well with the manually marked reference locations. The eigenspace tracking method performs slightly better than the motion-enhanced method, with average localization errors less than 2 pixels (1 mm) and the error at a 95% confidence level of about 2-4 pixels (1-2 mm). This work demonstrates the feasibility of direct tracking of a lung tumor mass in fluoroscopic images without implanted fiducial markers using multiple reference templates.

Least Squares Approach to the Alignment of the Generic High Precision Tracking System

NASA Astrophysics Data System (ADS)

de Renstrom, Pawel Brückman; Haywood, Stephen

2006-04-01

A least squares method to solve a generic alignment problem of a high granularity tracking system is presented. The algorithm is based on an analytical linear expansion and allows for multiple nested fits, e.g. imposing a common vertex for groups of particle tracks is of particular interest. We present a consistent and complete recipe to impose constraints on either implicit or explicit parameters. The method has been applied to the full simulation of a subset of the ATLAS silicon tracking system. The ultimate goal is to determine ≈35,000 degrees of freedom (DoF's). We present a limited scale exercise exploring various aspects of the solution.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

PubMed

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-03-20

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

PubMed Central

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-01-01

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods. PMID:28335537

Real-time tracking of respiratory-induced tumor motion by dose-rate regulation

NASA Astrophysics Data System (ADS)

Han-Oh, Yeonju Sarah

We have developed a novel real-time tumor-tracking technology, called Dose-Rate-Regulated Tracking (DRRT), to compensate for tumor motion caused by breathing. Unlike other previously proposed tumor-tracking methods, this new method uses a preprogrammed dynamic multileaf collimator (MLC) sequence in combination with real-time dose-rate control. This new scheme circumvents the technical challenge in MLC-based tumor tracking, that is to control the MLC motion in real time, based on real-time detected tumor motion. The preprogrammed MLC sequence describes the movement of the tumor, as a function of breathing phase, amplitude, or tidal volume. The irregularity of tumor motion during treatment is handled by real-time regulation of the dose rate, which effectively speeds up or slows down the delivery of radiation as needed. This method is based on the fact that all of the parameters in dynamic radiation delivery, including MLC motion, are enslaved to the cumulative dose, which, in turn, can be accelerated or decelerated by varying the dose rate. Because commercially available MLC systems do not allow the MLC delivery sequence to be modified in real time based on the patient's breathing signal, previously proposed tumor-tracking techniques using a MLC cannot be readily implemented in the clinic today. By using a preprogrammed MLC sequence to handle the required motion, the task for real-time control is greatly simplified. We have developed and tested the pre- programmed MLC sequence and the dose-rate regulation algorithm using lung-cancer patients breathing signals. It has been shown that DRRT can track the tumor with an accuracy of less than 2 mm for a latency of the DRRT system of less than 0.35 s. We also have evaluated the usefulness of guided breathing for DRRT. Since DRRT by its very nature can compensate for breathing-period changes, guided breathing was shown to be unnecessary for real-time tracking when using DRRT. Finally, DRRT uses the existing dose-rate control system that is provided for current linear accelerators. Therefore, DRRT can be achieved with minimal modification of existing technology, and this can shorten substantially the time necessary to establish DRRT in clinical practice.

A novel framework for objective detection and tracking of TC center from noisy satellite imagery

NASA Astrophysics Data System (ADS)

Johnson, Bibin; Thomas, Sachin; Rani, J. Sheeba

2018-07-01

This paper proposes a novel framework for automatically determining and tracking the center of a tropical cyclone (TC) during its entire life-cycle from the Thermal infrared (TIR) channel data of the geostationary satellite. The proposed method handles meteorological images with noise, missing or partial information due to the seasonal variability and lack of significant spatial or vortex features. To retrieve the cyclone center from these circumstances, a synergistic approach based on objective measures and Numerical Weather Prediction (NWP) model is being proposed. This method employs a spatial gradient scheme to process missing and noisy frames or a spatio-temporal gradient scheme for image sequences that are continuous and contain less noise. The initial estimate of the TC center from the missing imagery is corrected by exploiting a NWP model based post-processing scheme. The validity of the framework is tested on Infrared images of different cyclones obtained from various Geostationary satellites such as the Meteosat-7, INSAT- 3 D , Kalpana-1 etc. The computed track is compared with the actual track data obtained from Joint Typhoon Warning Center (JTWC), and it shows a reduction of mean track error by 11 % as compared to the other state of the art methods in the presence of missing and noisy frames. The proposed method is also successfully tested for simultaneous retrieval of the TC center from images containing multiple non-overlapping cyclones.

Tracking of multiple targets using online learning for reference model adaptation.

PubMed

Pernkopf, Franz

2008-12-01

Recently, much work has been done in multiple object tracking on the one hand and on reference model adaptation for a single-object tracker on the other side. In this paper, we do both tracking of multiple objects (faces of people) in a meeting scenario and online learning to incrementally update the models of the tracked objects to account for appearance changes during tracking. Additionally, we automatically initialize and terminate tracking of individual objects based on low-level features, i.e., face color, face size, and object movement. Many methods unlike our approach assume that the target region has been initialized by hand in the first frame. For tracking, a particle filter is incorporated to propagate sample distributions over time. We discuss the close relationship between our implemented tracker based on particle filters and genetic algorithms. Numerous experiments on meeting data demonstrate the capabilities of our tracking approach. Additionally, we provide an empirical verification of the reference model learning during tracking of indoor and outdoor scenes which supports a more robust tracking. Therefore, we report the average of the standard deviation of the trajectories over numerous tracking runs depending on the learning rate.

New insights on ion track morphology in pyrochlores by aberration corrected scanning transmission electron microscopy

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

Sachan, Ritesh; Zhang, Yanwen; Ou, Xin

Here we demonstrate the enhanced imaging capabilities of an aberration corrected scanning transmission electron microscope to advance the understanding of ion track structure in pyrochlore structured materials (i.e., Gd 2Ti 2O 7 and Gd 2TiZrO 7). Track formation occurs due to the inelastic transfer of energy from incident ions to electrons, and atomic-level details of track morphology as a function of energy-loss are revealed in the present work. A comparison of imaging details obtained by varying collection angles of detectors is discussed in the present work. A quantitative analysis of phase identification using high-angle annular dark field imaging is performedmore » on the ion tracks. Finally, a novel 3-dimensional track reconstruction method is provided that is based on depth dependent imaging of the ion tracks. The technique is used in extracting the atomic-level details of nanoscale features, such as the disordered ion tracks, which are embedded in relatively thicker matrix. Another relevance of the method is shown by measuring the tilt of the ion tracks relative to the electron beam incidence that helps in knowing the structure and geometry of ion tracks quantitatively.« less

New insights on ion track morphology in pyrochlores by aberration corrected scanning transmission electron microscopy

DOE PAGES

Sachan, Ritesh; Zhang, Yanwen; Ou, Xin; ...

2016-12-13

Here we demonstrate the enhanced imaging capabilities of an aberration corrected scanning transmission electron microscope to advance the understanding of ion track structure in pyrochlore structured materials (i.e., Gd 2Ti 2O 7 and Gd 2TiZrO 7). Track formation occurs due to the inelastic transfer of energy from incident ions to electrons, and atomic-level details of track morphology as a function of energy-loss are revealed in the present work. A comparison of imaging details obtained by varying collection angles of detectors is discussed in the present work. A quantitative analysis of phase identification using high-angle annular dark field imaging is performedmore » on the ion tracks. Finally, a novel 3-dimensional track reconstruction method is provided that is based on depth dependent imaging of the ion tracks. The technique is used in extracting the atomic-level details of nanoscale features, such as the disordered ion tracks, which are embedded in relatively thicker matrix. Another relevance of the method is shown by measuring the tilt of the ion tracks relative to the electron beam incidence that helps in knowing the structure and geometry of ion tracks quantitatively.« less

Methods of reconstruction of multi-particle events in the new coordinate-tracking setup

NASA Astrophysics Data System (ADS)

Vorobyev, V. S.; Shutenko, V. V.; Zadeba, E. A.

2018-01-01

At the Unique Scientific Facility NEVOD (MEPhI), a large coordinate-tracking detector based on drift chambers for investigations of muon bundles generated by ultrahigh energy primary cosmic rays is being developed. One of the main characteristics of the bundle is muon multiplicity. Three methods of reconstruction of multiple events were investigated: the sequential search method, method of finding the straight line and method of histograms. The last method determines the number of tracks with the same zenith angle in the event. It is most suitable for the determination of muon multiplicity: because of a large distance to the point of generation of muons, their trajectories are quasiparallel. The paper presents results of application of three reconstruction methods to data from the experiment, and also first results of the detector operation.

A software solution to dynamically reduce metallic distortions of electromagnetic tracking systems for image-guided surgery.

PubMed

Li, Mengfei; Hansen, Christian; Rose, Georg

2017-09-01

Electromagnetic tracking systems (EMTS) have achieved a high level of acceptance in clinical settings, e.g., to support tracking of medical instruments in image-guided interventions. However, tracking errors caused by movable metallic medical instruments and electronic devices are a critical problem which prevents the wider application of EMTS for clinical applications. We plan to introduce a method to dynamically reduce tracking errors caused by metallic objects in proximity to the magnetic sensor coil of the EMTS. We propose a method using ramp waveform excitation based on modeling the conductive distorter as a resistance-inductance circuit. Additionally, a fast data acquisition method is presented to speed up the refresh rate. With the current approach, the sensor's positioning mean error is estimated to be 3.4, 1.3 and 0.7 mm, corresponding to a distance between the sensor and center of the transmitter coils' array of up to 200, 150 and 100 mm, respectively. The sensor pose error caused by different medical instruments placed in proximity was reduced by the proposed method to a level lower than 0.5 mm in position and [Formula: see text] in orientation. By applying the newly developed fast data acquisition method, we achieved a system refresh rate up to approximately 12.7 frames per second. Our software-based approach can be integrated into existing medical EMTS seamlessly with no change in hardware. It improves the tracking accuracy of clinical EMTS when there is a metallic object placed near the sensor coil and has the potential to improve the safety and outcome of image-guided interventions.

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

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

Fahimian, B.

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniquesmore » for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.« less

MO-FG-BRD-04: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking

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

Low, D.

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniquesmore » for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.« less

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

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

Berbeco, R.

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniquesmore » for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.« less

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

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

Keall, P.

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniquesmore » for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.« less

Evaluation of Methods for In-Situ Calibration of Field-Deployable Microphone Phased Arrays

NASA Technical Reports Server (NTRS)

Humphreys, William M.; Lockard, David P.; Khorrami, Mehdi R.; Culliton, William G.; McSwain, Robert G.

2017-01-01

Current field-deployable microphone phased arrays for aeroacoustic flight testing require the placement of hundreds of individual sensors over a large area. Depending on the duration of the test campaign, the microphones may be required to stay deployed at the testing site for weeks or even months. This presents a challenge in regards to tracking the response (i.e., sensitivity) of the individual sensors as a function of time in order to evaluate the health of the array. To address this challenge, two different methods for in-situ tracking of microphone responses are described. The first relies on the use of an aerial sound source attached as a payload on a hovering small Unmanned Aerial System (sUAS) vehicle. The second relies on the use of individually excited ground-based sound sources strategically placed throughout the array pattern. Testing of the two methods was performed in microphone array deployments conducted at Fort A.P. Hill in 2015 and at Edwards Air Force Base in 2016. The results indicate that the drift in individual sensor responses can be tracked reasonably well using both methods. Thus, in-situ response tracking methods are useful as a diagnostic tool for monitoring the health of a phased array during long duration deployments.

Long-term object tracking combined offline with online learning

NASA Astrophysics Data System (ADS)

Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun

2016-04-01

We propose a simple yet effective method for long-term object tracking. Different from the traditional visual tracking method, which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion. To summarize, our algorithm can be roughly decomposed into an initialization stage and a tracking stage. In the initialization stage, an offline detector is trained to get the object appearance information at the category level, which is used for detecting the potential target and initializing the tracking stage. The tracking stage consists of three modules: the online tracking module, detection module, and decision module. A pretrained detector is used for maintaining drift of the online tracker, while the online tracker is used for filtering out false positive detections. A confidence selection mechanism is proposed to optimize the object location based on the online tracker and detection. If the target is lost, the pretrained detector is utilized to reinitialize the whole algorithm when the target is relocated. During experiments, we evaluate our method on several challenging video sequences, and it demonstrates huge improvement compared with detection and online tracking only.

An image‐based method to synchronize cone‐beam CT and optical surface tracking

PubMed Central

Schaerer, Joël; Riboldi, Marco; Sarrut, David; Baroni, Guido

2015-01-01

The integration of in‐room X‐ray imaging and optical surface tracking has gained increasing importance in the field of image guided radiotherapy (IGRT). An essential step for this integration consists of temporally synchronizing the acquisition of X‐ray projections and surface data. We present an image‐based method for the synchronization of cone‐beam computed tomography (CBCT) and optical surface systems, which does not require the use of additional hardware. The method is based on optically tracking the motion of a component of the CBCT/gantry unit, which rotates during the acquisition of the CBCT scan. A calibration procedure was implemented to relate the position of the rotating component identified by the optical system with the time elapsed since the beginning of the CBCT scan, thus obtaining the temporal correspondence between the acquisition of X‐ray projections and surface data. The accuracy of the proposed synchronization method was evaluated on a motorized moving phantom, performing eight simultaneous acquisitions with an Elekta Synergy CBCT machine and the AlignRT optical device. The median time difference between the sinusoidal peaks of phantom motion signals extracted from the synchronized CBCT and AlignRT systems ranged between ‐3.1 and 12.9 msec, with a maximum interquartile range of 14.4 msec. The method was also applied to clinical data acquired from seven lung cancer patients, demonstrating the potential of the proposed approach in estimating the individual and daily variations in respiratory parameters and motion correlation of internal and external structures. The presented synchronization method can be particularly useful for tumor tracking applications in extracranial radiation treatments, especially in the field of patient‐specific breathing models, based on the correlation between internal tumor motion and external surface surrogates. PACS number: 87

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

Validation of model-based deformation correction in image-guided liver surgery via tracked intraoperative ultrasound: preliminary method and results

NASA Astrophysics Data System (ADS)

Clements, Logan W.; Collins, Jarrod A.; Wu, Yifei; Simpson, Amber L.; Jarnagin, William R.; Miga, Michael I.

2015-03-01

Soft tissue deformation represents a significant error source in current surgical navigation systems used for open hepatic procedures. While numerous algorithms have been proposed to rectify the tissue deformation that is encountered during open liver surgery, clinical validation of the proposed methods has been limited to surface based metrics and sub-surface validation has largely been performed via phantom experiments. Tracked intraoperative ultrasound (iUS) provides a means to digitize sub-surface anatomical landmarks during clinical procedures. The proposed method involves the validation of a deformation correction algorithm for open hepatic image-guided surgery systems via sub-surface targets digitized with tracked iUS. Intraoperative surface digitizations were acquired via a laser range scanner and an optically tracked stylus for the purposes of computing the physical-to-image space registration within the guidance system and for use in retrospective deformation correction. Upon completion of surface digitization, the organ was interrogated with a tracked iUS transducer where the iUS images and corresponding tracked locations were recorded. After the procedure, the clinician reviewed the iUS images to delineate contours of anatomical target features for use in the validation procedure. Mean closest point distances between the feature contours delineated in the iUS images and corresponding 3-D anatomical model generated from the preoperative tomograms were computed to quantify the extent to which the deformation correction algorithm improved registration accuracy. The preliminary results for two patients indicate that the deformation correction method resulted in a reduction in target error of approximately 50%.

Extending interferometric synthetic aperture radar measurements from one to two dimensions

NASA Astrophysics Data System (ADS)

Bechor, Noah

Interferometric synthetic aperture radar (InSAR), a very effective technique for measuring crustal deformation, provides measurements in only one dimension, along the radar line of sight. Imaging radar measurements from satellite-based systems are sensitive to both vertical and across-track displacements, but insensitive to along-track displacement. Multiple observations can resolve the first two components, but the along-track component remains elusive. The best existing method to obtain the along-track displacement involves pixel-level azimuth cross-correlation. The measurements are quite coarse (typically 15 cm precision), and they require large computation times. In contrast, across-track and vertical InSAR measurements can reach centimeter-level precision and are readily derived. We present a new method to extract along-track displacements from InSAR data. The new method, multiple aperture InSAR (MAI), is based on split-beam processing of InSAR data to create forward- and backward-looking interferograms. The phase difference between the two modified interferograms provides the along-track displacement component. Thus, from each conventional InSAR pair we extract two components of the displacement vector: one along the line of sight, the other in the along-track direction. Multiple MAI observations, either at two look angles or from the ascending and descending radar passes, then yield the three-dimensional displacement field. We analyze precision of our method by comparing our solution to GPS and offset-derived along-track displacements from interferograms of the M7.1 1999, Hector Mine earthquake. The RMS error between GPS displacements and our results ranges from 5 to 8.8cm. Our method is consistent with along-track displacements derived by pixel-offsets, themselves limited to 12-15cm precision. The theoretical MAI precision depends on SNR and coherence. For SNR=100 the expected precision is 3, 11cm for coherence of 0.8, 0.4, respectively. Finally, we evaluate how the new measurements improve the determination of the earthquake coseismic slip distribution by comparison of models derived from multiple data types. We find that MAI data help constrain the southern portion of the lip distribution, by adding information where GPS data are sparse and the deformation is below the azimuth pixel-offsets detection threshold.

Real-time subpixel-accuracy tracking of single mitochondria in neurons reveals heterogeneous mitochondrial motion.

PubMed

Alsina, Adolfo; Lai, Wu Ming; Wong, Wai Kin; Qin, Xianan; Zhang, Min; Park, Hyokeun

2017-11-04

Mitochondria are essential for cellular survival and function. In neurons, mitochondria are transported to various subcellular regions as needed. Thus, defects in the axonal transport of mitochondria are related to the pathogenesis of neurodegenerative diseases, and the movement of mitochondria has been the subject of intense research. However, the inability to accurately track mitochondria with subpixel accuracy has hindered this research. Here, we report an automated method for tracking mitochondria based on the center of fluorescence. This tracking method, which is accurate to approximately one-tenth of a pixel, uses the centroid of an individual mitochondrion and provides information regarding the distance traveled between consecutive imaging frames, instantaneous speed, net distance traveled, and average speed. Importantly, this new tracking method enables researchers to observe both directed motion and undirected movement (i.e., in which the mitochondrion moves randomly within a small region, following a sub-diffusive motion). This method significantly improves our ability to analyze the movement of mitochondria and sheds light on the dynamic features of mitochondrial movement. Copyright © 2017 Elsevier Inc. All rights reserved.

H∞ output tracking control of uncertain and disturbed nonlinear systems based on neural network model

NASA Astrophysics Data System (ADS)

Li, Chengcheng; Li, Yuefeng; Wang, Guanglin

2017-07-01

The work presented in this paper seeks to address the tracking problem for uncertain continuous nonlinear systems with external disturbances. The objective is to obtain a model that uses a reference-based output feedback tracking control law. The control scheme is based on neural networks and a linear difference inclusion (LDI) model, and a PDC structure and H∞ performance criterion are used to attenuate external disturbances. The stability of the whole closed-loop model is investigated using the well-known quadratic Lyapunov function. The key principles of the proposed approach are as follows: neural networks are first used to approximate nonlinearities, to enable a nonlinear system to then be represented as a linearised LDI model. An LMI (linear matrix inequality) formula is obtained for uncertain and disturbed linear systems. This formula enables a solution to be obtained through an interior point optimisation method for some nonlinear output tracking control problems. Finally, simulations and comparisons are provided on two practical examples to illustrate the validity and effectiveness of the proposed method.

Ultraheavy cosmic ray tracks in meteorites: A reappraisal, based on calibrations with relativistic ions

NASA Technical Reports Server (NTRS)

Perron, C.

1985-01-01

Experiments were carried out on tracks of high energy U ions in olivine, a common meteoritic mineral. The results offer an explanation for the lack of success of previous attempts to derive the Ultraheavy Cosmic Ray composition from the study of tracks in meteorites. They also suggest how such experiments should be performed. The methods tested are described and illustrated.

Automatic Spatio-Temporal Flow Velocity Measurement in Small Rivers Using Thermal Image Sequences

NASA Astrophysics Data System (ADS)

Lin, D.; Eltner, A.; Sardemann, H.; Maas, H.-G.

2018-05-01

An automatic spatio-temporal flow velocity measurement approach, using an uncooled thermal camera, is proposed in this paper. The basic principle of the method is to track visible thermal features at the water surface in thermal camera image sequences. Radiometric and geometric calibrations are firstly implemented to remove vignetting effects in thermal imagery and to get the interior orientation parameters of the camera. An object-based unsupervised classification approach is then applied to detect the interest regions for data referencing and thermal feature tracking. Subsequently, GCPs are extracted to orient the river image sequences and local hot points are identified as tracking features. Afterwards, accurate dense tracking outputs are obtained using pyramidal Lucas-Kanade method. To validate the accuracy potential of the method, measurements obtained from thermal feature tracking are compared with reference measurements taken by a propeller gauge. Results show a great potential of automatic flow velocity measurement in small rivers using imagery from a thermal camera.

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools.

PubMed

Dutta, Priyanka; Lehmann, Christina; Odedra, Devang; Singh, Deepika; Pohl, Christian

2015-12-16

Quantitatively capturing developmental processes is crucial to derive mechanistic models and key to identify and describe mutant phenotypes. Here protocols are presented for preparing embryos and adult C. elegans animals for short- and long-term time-lapse microscopy and methods for tracking and quantification of developmental processes. The methods presented are all based on C. elegans strains available from the Caenorhabditis Genetics Center and on open-source software that can be easily implemented in any laboratory independently of the microscopy system used. A reconstruction of a 3D cell-shape model using the modelling software IMOD, manual tracking of fluorescently-labeled subcellular structures using the multi-purpose image analysis program Endrov, and an analysis of cortical contractile flow using PIVlab (Time-Resolved Digital Particle Image Velocimetry Tool for MATLAB) are shown. It is discussed how these methods can also be deployed to quantitatively capture other developmental processes in different models, e.g., cell tracking and lineage tracing, tracking of vesicle flow.

Detection of Ballast Damage by In-Situ Vibration Measurement of Sleepers

NASA Astrophysics Data System (ADS)

Lam, H. F.; Wong, M. T.; Keefe, R. M.

2010-05-01

Ballasted track is one of the most important elements of railway transportation systems worldwide. Owing to its importance in railway safety, many monitoring and evaluation methods have been developed. Current railway track monitoring systems are comprehensive, fast and efficient in testing railway track level and alignment, rail gauge, rail corrugation, etc. However, the monitoring of ballast condition still relies very much on visual inspection and core tests. Although extensive research has been carried out in the development of non-destructive methods for ballast condition evaluation, a commonly accepted and cost-effective method is still in demand. In Hong Kong practice, if abnormal train vibration is reported by the train operator or passengers, permanent way inspectors will locate the problem area by track geometry measurement. It must be pointed out that visual inspection can only identify ballast damage on the track surface, the track geometry deficiencies and rail twists can be detected using a track gauge. Ballast damage under the sleeper loading area and the ballast shoulder, which are the main factors affecting track stability and ride quality, are extremely difficult if not impossible to be detected by visual inspection. Core test is a destructive test, which is expensive, time consuming and may be disruptive to traffic. A fast real-time ballast damage detection method that can be implemented by permanent way inspectors with simple equipment can certainly provide valuable information for engineers in assessing the safety and riding quality of ballasted track systems. The main objective of this paper is to study the feasibility in using the vibration characteristics of sleepers in quantifying the ballast condition under the sleepers, and so as to explore the possibility in developing a handy method for the detection of ballast damage based on the measured vibration of sleepers.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

A novel method for automated tracking and quantification of adult zebrafish behaviour during anxiety.

PubMed

Nema, Shubham; Hasan, Whidul; Bhargava, Anamika; Bhargava, Yogesh

2016-09-15

Behavioural neuroscience relies on software driven methods for behavioural assessment, but the field lacks cost-effective, robust, open source software for behavioural analysis. Here we propose a novel method which we called as ZebraTrack. It includes cost-effective imaging setup for distraction-free behavioural acquisition, automated tracking using open-source ImageJ software and workflow for extraction of behavioural endpoints. Our ImageJ algorithm is capable of providing control to users at key steps while maintaining automation in tracking without the need for the installation of external plugins. We have validated this method by testing novelty induced anxiety behaviour in adult zebrafish. Our results, in agreement with established findings, showed that during state-anxiety, zebrafish showed reduced distance travelled, increased thigmotaxis and freezing events. Furthermore, we proposed a method to represent both spatial and temporal distribution of choice-based behaviour which is currently not possible to represent using simple videograms. ZebraTrack method is simple and economical, yet robust enough to give results comparable with those obtained from costly proprietary software like Ethovision XT. We have developed and validated a novel cost-effective method for behavioural analysis of adult zebrafish using open-source ImageJ software. Copyright © 2016 Elsevier B.V. All rights reserved.

SU-C-18A-02: Image-Based Camera Tracking: Towards Registration of Endoscopic Video to CT

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

Ingram, S; Rao, A; Wendt, R

Purpose: Endoscopic examinations are routinely performed on head and neck and esophageal cancer patients. However, these images are underutilized for radiation therapy because there is currently no way to register them to a CT of the patient. The purpose of this work is to develop a method to track the motion of an endoscope within a structure using images from standard clinical equipment. This method will be incorporated into a broader endoscopy/CT registration framework. Methods: We developed a software algorithm to track the motion of an endoscope within an arbitrary structure. We computed frame-to-frame rotation and translation of the cameramore » by tracking surface points across the video sequence and utilizing two-camera epipolar geometry. The resulting 3D camera path was used to recover the surrounding structure via triangulation methods. We tested this algorithm on a rigid cylindrical phantom with a pattern spray-painted on the inside. We did not constrain the motion of the endoscope while recording, and we did not constrain our measurements using the known structure of the phantom. Results: Our software algorithm can successfully track the general motion of the endoscope as it moves through the phantom. However, our preliminary data do not show a high degree of accuracy in the triangulation of 3D point locations. More rigorous data will be presented at the annual meeting. Conclusion: Image-based camera tracking is a promising method for endoscopy/CT image registration, and it requires only standard clinical equipment. It is one of two major components needed to achieve endoscopy/CT registration, the second of which is tying the camera path to absolute patient geometry. In addition to this second component, future work will focus on validating our camera tracking algorithm in the presence of clinical imaging features such as patient motion, erratic camera motion, and dynamic scene illumination.« less

Fast spacecraft adaptive attitude tracking control through immersion and invariance design

NASA Astrophysics Data System (ADS)

Wen, Haowei; Yue, Xiaokui; Li, Peng; Yuan, Jianping

2017-10-01

This paper presents a novel non-certainty-equivalence adaptive control method for the attitude tracking control problem of spacecraft with inertia uncertainties. The proposed immersion and invariance (I&I) based adaptation law provides a more direct and flexible approach to circumvent the limitations of the basic I&I method without employing any filter signal. By virtue of the adaptation high-gain equivalence property derived from the proposed adaptive method, the closed-loop adaptive system with a low adaptation gain could recover the high adaptation gain performance of the filter-based I&I method, and the resulting control torque demands during the initial transient has been significantly reduced. A special feature of this method is that the convergence of the parameter estimation error has been observably improved by utilizing an adaptation gain matrix instead of a single adaptation gain value. Numerical simulations are presented to highlight the various benefits of the proposed method compared with the certainty-equivalence-based control method and filter-based I&I control schemes.

Effective star tracking method based on optical flow analysis for star trackers.

PubMed

Sun, Ting; Xing, Fei; Wang, Xiaochu; Li, Jin; Wei, Minsong; You, Zheng

2016-12-20

Benefiting from rapid development of imaging sensor technology, modern optical technology, and a high-speed computing chip, the star tracker's accuracy, dynamic performance, and update rate have been greatly improved with low power consumption and miniature size. The star tracker is currently one of the most competitive attitude measurement sensors. However, due to restrictions of the optical imaging system, difficulties still exist in moving star spot detection and star tracking when in special motion conditions. An effective star tracking method based on optical flow analysis for star trackers is proposed in this paper. Spot-based optical flow, based on a gray gradient between two adjacent star images, is analyzed to distinguish the star spot region and obtain an accurate star spot position so that the star tracking can keep continuous under high dynamic conditions. The obtained star vectors and extended Kalman filter (EKF) are then combined to conduct an angular velocity estimation to ensure region prediction of the star spot; this can be combined with the optical flow analysis result. Experiment results show that the method proposed in this paper has advantages in conditions of large angular velocity and large angular acceleration, despite the presence of noise. Higher functional density and better performance can be achieved; thus, the star tracker can be more widely applied in small satellites, remote sensing, and other complex space missions.

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment

PubMed Central

Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment. PMID:29088228

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.

PubMed

Hong, Zhiling; Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment.

A Railway Track Geometry Measuring Trolley System Based on Aided INS

PubMed Central

Chen, Qijin; Niu, Xiaoji; Zuo, Lili; Zhang, Tisheng; Xiao, Fuqin; Liu, Yi; Liu, Jingnan

2018-01-01

Accurate measurement of the railway track geometry is a task of fundamental importance to ensure the track quality in both the construction phase and the regular maintenance stage. Conventional track geometry measuring trolleys (TGMTs) in combination with classical geodetic surveying apparatus such as total stations alone cannot meet the requirements of measurement accuracy and surveying efficiency at the same time. Accurate and fast track geometry surveying applications call for an innovative surveying method that can measure all or most of the track geometric parameters in short time without interrupting the railway traffic. We provide a novel solution to this problem by integrating an inertial navigation system (INS) with a geodetic surveying apparatus, and design a modular TGMT system based on aided INS, which can be configured according to different surveying tasks including precise adjustment of slab track, providing tamping measurements, measuring track deformation and irregularities, and determination of the track axis. TGMT based on aided INS can operate in mobile surveying mode to significantly improve the surveying efficiency. Key points in the design of the TGMT’s architecture and the data processing concept and workflow are introduced in details, which should benefit subsequent research and provide a reference for the implementation of this kind of TGMT. The surveying performance of proposed TGMT with different configurations is assessed in the track geometry surveying experiments and actual projects. PMID:29439423

Application of RFID in the area of agricultural products quality traceability and tracking and the anti-collision algorithm

NASA Astrophysics Data System (ADS)

Wang, Zu-liang; Zhang, Ting; Xie, Shi-yang

2017-01-01

In order to improve the agricultural tracing efficiency and reduce tracking and monitoring cost, agricultural products quality tracking and tracing based on Radio-Frequency Identification(RFID) technology is studied, then tracing and tracking model is set up. Three-layer structure model is established to realize the high quality of agricultural products traceability and tracking. To solve the collision problems between multiple RFID tags and improve the identification efficiency a new reservation slot allocation mechanism is proposed. And then we analyze and optimize the parameter by numerical simulation method.

Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences

PubMed Central

Liu, Yun; Wang, Chuanxu; Zhang, Shujun; Cui, Xuehong

2016-01-01

Pedestrian tracking is a critical problem in the field of computer vision. Particle filters have been proven to be very useful in pedestrian tracking for nonlinear and non-Gaussian estimation problems. However, pedestrian tracking in complex environment is still facing many problems due to changes of pedestrian postures and scale, moving background, mutual occlusion, and presence of pedestrian. To surmount these difficulties, this paper presents tracking algorithm of multiple pedestrians based on particle filters in video sequences. The algorithm acquires confidence value of the object and the background through extracting a priori knowledge thus to achieve multipedestrian detection; it adopts color and texture features into particle filter to get better observation results and then automatically adjusts weight value of each feature according to current tracking environment. During the process of tracking, the algorithm processes severe occlusion condition to prevent drift and loss phenomena caused by object occlusion and associates detection results with particle state to propose discriminated method for object disappearance and emergence thus to achieve robust tracking of multiple pedestrians. Experimental verification and analysis in video sequences demonstrate that proposed algorithm improves the tracking performance and has better tracking results. PMID:27847514

MO-FG-BRD-00: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management

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

NONE

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniquesmore » for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.« less

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

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

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems ismore » expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.« less

Scene-based method for spatial misregistration detection in hyperspectral imagery.

PubMed

Dell'Endice, Francesco; Nieke, Jens; Schläpfer, Daniel; Itten, Klaus I

2007-05-20

Hyperspectral imaging (HSI) sensors suffer from spatial misregistration, an artifact that prevents the accurate acquisition of the spectra. Physical considerations let us assume that the influence of the spatial misregistration on the acquired data depends both on the wavelength and on the across-track position. A scene-based method, based on edge detection, is therefore proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic projections, giving an estimation for spatial misregistration, and also allowing identification of misalignments. The method has been applied to several hyperspectral sensors, either prism, or grating-based designs. The results confirm the dependence assumptions on lambda and theta, spectral wavelength and across-track pixel, respectively. Suggestions are also given to correct for spatial misregistration.

Neuro-Analogical Gate Tuning of Trajectory Data Fusion for a Mecanum-Wheeled Special Needs Chair

PubMed Central

ElSaharty, M. A.; zakzouk, Ezz Eldin

2017-01-01

Trajectory tracking of mobile wheeled chairs using internal shaft encoder and inertia measurement unit(IMU), exhibits several complications and accumulated errors in the tracking process due to wheel slippage, offset drift and integration approximations. These errors can be realized when comparing localization results from such sensors with a camera tracking system. In long trajectory tracking, such errors can accumulate and result in significant deviations which make data from these sensors unreliable for tracking. Meanwhile the utilization of an external camera tracking system is not always a feasible solution depending on the implementation environment. This paper presents a novel sensor fusion method that combines the measurements of internal sensors to accurately predict the location of the wheeled chair in an environment. The method introduces a new analogical OR gate structured with tuned parameters using multi-layer feedforward neural network denoted as “Neuro-Analogical Gate” (NAG). The resulting system minimize any deviation error caused by the sensors, thus accurately tracking the wheeled chair location without the requirement of an external camera tracking system. The fusion methodology has been tested with a prototype Mecanum wheel-based chair, and significant improvement over tracking response, error and performance has been observed. PMID:28045973

TESOL Methods: Changing Tracks, Challenging Trends

ERIC Educational Resources Information Center

Kumaravadivelu, B.

2006-01-01

This article traces the major trends in TESOL methods in the past 15 years. It focuses on the TESOL profession's evolving perspectives on language teaching methods in terms of three perceptible shifts: (a) from communicative language teaching to task-based language teaching, (b) from method-based pedagogy to postmethod pedagogy, and (c) from…

Global finite-time attitude consensus tracking control for a group of rigid spacecraft

NASA Astrophysics Data System (ADS)

Li, Penghua

2017-10-01

The problem of finite-time attitude consensus for multiple rigid spacecraft with a leader-follower architecture is investigated in this paper. To achieve the finite-time attitude consensus, at the first step, a distributed finite-time convergent observer is proposed for each follower to estimate the leader's attitude in a finite time. Then based on the terminal sliding mode control method, a new finite-time attitude tracking controller is designed such that the leader's attitude can be tracked in a finite time. Finally, a finite-time observer-based distributed control strategy is proposed. It is shown that the attitude consensus can be achieved in a finite time under the proposed controller. Simulation results are given to show the effectiveness of the proposed method.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms.

PubMed

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-06-06

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms

PubMed Central

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-01-01

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable. PMID:28587275

Human movement tracking based on Kalman filter

NASA Astrophysics Data System (ADS)

Zhang, Yi; Luo, Yuan

2006-11-01

During the rehabilitation process of the post-stroke patients is conducted, their movements need to be localized and learned so that incorrect movement can be instantly modified or tuned. Therefore, tracking these movement becomes vital and necessary for the rehabilitative course. In the technologies of human movement tracking, the position prediction of human movement is very important. In this paper, we first analyze the configuration of the human movement system and choice of sensors. Then, The Kalman filter algorithm and its modified algorithm are proposed and to be used to predict the position of human movement. In the end, on the basis of analyzing the performance of the method, it is clear that the method described can be used to the system of human movement tracking.

Development of Matched (migratory Analytical Time Change Easy Detection) Method for Satellite-Tracked Migratory Birds

NASA Astrophysics Data System (ADS)

Doko, Tomoko; Chen, Wenbo; Higuchi, Hiroyoshi

2016-06-01

Satellite tracking technology has been used to reveal the migration patterns and flyways of migratory birds. In general, bird migration can be classified according to migration status. These statuses include the wintering period, spring migration, breeding period, and autumn migration. To determine the migration status, periods of these statuses should be individually determined, but there is no objective method to define 'a threshold date' for when an individual bird changes its status. The research objective is to develop an effective and objective method to determine threshold dates of migration status based on satellite-tracked data. The developed method was named the "MATCHED (Migratory Analytical Time Change Easy Detection) method". In order to demonstrate the method, data acquired from satellite-tracked Tundra Swans were used. MATCHED method is composed by six steps: 1) dataset preparation, 2) time frame creation, 3) automatic identification, 4) visualization of change points, 5) interpretation, and 6) manual correction. Accuracy was tested. In general, MATCHED method was proved powerful to identify the change points between migration status as well as stopovers. Nevertheless, identifying "exact" threshold dates is still challenging. Limitation and application of this method was discussed.

WiFi RFID demonstration for resource tracking in a statewide disaster drill.

PubMed

Cole, Stacey L; Siddiqui, Javeed; Harry, David J; Sandrock, Christian E

2011-01-01

To investigate the capabilities of Radio Frequency Identification (RFID) tracking of patients and medical equipment during a simulated disaster response scenario. RFID infrastructure was deployed at two small rural hospitals, in one large academic medical center and in two vehicles. Several item types from the mutual aid equipment list were selected for tracking during the demonstration. A central database server was installed at the UC Davis Medical Center (UCDMC) that collected RFID information from all constituent sites. The system was tested during a statewide disaster drill. During the drill, volunteers at UCDMC were selected to locate assets using the traditional method of locating resources and then using the RFID system. This study demonstrated the effectiveness of RFID infrastructure in real-time resource identification and tracking. Volunteers at UCDMC were able to locate assets substantially faster using RFID, demonstrating that real-time geolocation can be substantially more efficient and accurate than traditional manual methods. A mobile, Global Positioning System (GPS)-enabled RFID system was installed in a pediatric ambulance and connected to the central RFID database via secure cellular communication. This system is unique in that it provides for seamless region-wide tracking that adaptively uses and seamlessly integrates both outdoor cellular-based mobile tracking and indoor WiFi-based tracking. RFID tracking can provide a real-time picture of the medical situation across medical facilities and other critical locations, leading to a more coordinated deployment of resources. The RFID system deployed during this study demonstrated the potential to improve the ability to locate and track victims, healthcare professionals, and medical equipment during a region-wide disaster.

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

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

Mazur, T; Wang, Y; Fischer-Valuck, B

2015-06-15

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. Wemore » use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective motion assessment. Applications of these methods include motion assessment, identifying treatment windows for gating, and determining optimal margins for treatment.« less

Benefits and challenges to using DNA-based identification methods: An example study of larval fish from nearshore areas of Lake Superior

EPA Science Inventory

DNA-based identification methods could increase the ability of aquatic resource managers to track patterns of invasive species, especially for taxa that are difficult to identify morphologically. Nonetheless, use of DNA-based identification methods in aquatic surveys is still unc...

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

PubMed

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

2012-08-01

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

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Magneto-optical tracking of flexible laparoscopic ultrasound: model-based online detection and correction of magnetic tracking errors.

PubMed

Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir

2009-06-01

Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.

Implementation of a web-based medication tracking system in a large academic medical center.

PubMed

Calabrese, Sam V; Williams, Jonathan P

2012-10-01

Pharmacy workflow efficiencies achieved through the use of an electronic medication-tracking system are described. Medication dispensing turnaround times at the inpatient pharmacy of a large hospital were evaluated before and after transition from manual medication tracking to a Web-based tracking process involving sequential bar-code scanning and real-time monitoring of medication status. The transition was carried out in three phases: (1) a workflow analysis, including the identification of optimal points for medication scanning with hand-held wireless devices, (2) the phased implementation of an automated solution and associated hardware at a central dispensing pharmacy and three satellite locations, and (3) postimplementation data collection to evaluate the impact of the new tracking system and areas for improvement. Relative to the manual tracking method, electronic medication tracking allowed the capture of far more data points, enabling the pharmacy team to delineate the time required for each step of the medication dispensing process and to identify the steps most likely to involve delays. A comparison of baseline and postimplementation data showed substantial reductions in overall medication turnaround times with the use of the Web-based tracking system (time reductions of 45% and 22% at the central and satellite sites, respectively). In addition to more accurate projections and documentation of turnaround times, the Web-based tracking system has facilitated quality-improvement initiatives. Implementation of an electronic tracking system for monitoring the delivery of medications provided a comprehensive mechanism for calculating turnaround times and allowed the pharmacy to identify bottlenecks within the medication distribution system. Altering processes removed these bottlenecks and decreased delivery turnaround times.

Model-based approach to partial tracking for musical transcription

NASA Astrophysics Data System (ADS)

Sterian, Andrew; Wakefield, Gregory H.

1998-10-01

We present a new method for musical partial tracking in the context of musical transcription using a time-frequency Kalman filter structure. The filter is based upon a model for the evolution of a partial behavior across a wide range of pitch from four brass instruments. Statistics are computed independently for the partial attributes of frequency and log-power first differences. We present observed power spectral density shapes, total powers, and histograms, as well as least-squares approximations to these. We demonstrate that a Kalman filter tracker using this partial model is capable of tracking partials in music. We discuss how the filter structure naturally provides quality-of-fit information about the data for use in further processing and how this information can be used to perform partial track initiation and termination within a common framework. We propose that a model-based approach to partial tracking is preferable to existing approaches which generally use heuristic rules or birth/death notions over a small time neighborhood. The advantages include better performance in the presence of cluttered data and simplified tracking over missed observations.

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors

PubMed Central

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-01-01

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method. PMID:28825684

AAA gunnermodel based on observer theory. [predicting a gunner's tracking response

NASA Technical Reports Server (NTRS)

Kou, R. S.; Glass, B. C.; Day, C. N.; Vikmanis, M. M.

1978-01-01

The Luenberger observer theory is used to develop a predictive model of a gunner's tracking response in antiaircraft artillery systems. This model is composed of an observer, a feedback controller and a remnant element. An important feature of the model is that the structure is simple, hence a computer simulation requires only a short execution time. A parameter identification program based on the least squares curve fitting method and the Gauss Newton gradient algorithm is developed to determine the parameter values of the gunner model. Thus, a systematic procedure exists for identifying model parameters for a given antiaircraft tracking task. Model predictions of tracking errors are compared with human tracking data obtained from manned simulation experiments. Model predictions are in excellent agreement with the empirical data for several flyby and maneuvering target trajectories.

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

PubMed

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-08-21

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

PubMed

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

PubMed Central

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J.

2017-01-01

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter. PMID:28273796

CHARGE SPECTRUM OF HEAVY AND SUPERHEAVY COMPONENTS OF GALACTIC COSMIC RAYS: RESULTS OF THE OLIMPIYA EXPERIMENT

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

Alexeev, Victor; Kalinina, Galina; Pavlova, Tatyana, E-mail: aval37@mail.ru, E-mail: gakalin@mail.ru, E-mail: pavlova4tat@mail.ru

2016-10-01

The aim of the OLIMPIYA experiment is to search for and identify traces of heavy and superheavy nuclei of galactic cosmic rays (GCR) in olivine crystals from stony–iron meteorites serving as nuclear track detectors. The method is based on layer-by-layer grinding and etching of particle tracks in these crystals. Unlike the techniques of other authors, this annealing-free method uses two parameters: the etching rate along the track ( V {sub etch}) and the total track length ( L ), to identify charge Z of a projectile. A series of irradiations with different swift heavy ions at the accelerator facilities ofmore » GSI (Darmstadt) and IMP (Lanzhou) were performed in order to determine and calibrate the dependence of projectile charge on V {sub etch} and L . To date, one of the most essential results of the experiment is the obtained charge spectrum of GCR nuclei within the range of Z > 40, based on about 11.6 thousand processed tracks. As the result of data processing, 384 nuclei with charges Z ≥ 75 have been identified, including 10 nuclei identified as actinides (90 < Z < 103). Three tracks were identified to be produced by nuclei with charges 113 < Z < 129. Such nuclei may be part of the Island of Stability of transfermium elements.« less

Tracking Data Acquisition System (TDAS) for the 1990's. Volume 6: TDAS navigation system architecture

NASA Technical Reports Server (NTRS)

Elrod, B. D.; Jacobsen, A.; Cook, R. A.; Singh, R. N. P.

1983-01-01

One-way range and Doppler methods for providing user orbit and time determination are examined. Forward link beacon tracking, with on-board processing of independent navigation signals broadcast continuously by TDAS spacecraft; forward link scheduled tracking; with on-board processing of navigation data received during scheduled TDAS forward link service intervals; and return link scheduled tracking; with ground-based processing of user generated navigation data during scheduled TDAS return link service intervals are discussed. A system level definition and requirements assessment for each alternative, an evaluation of potential navigation performance and comparison with TDAS mission model requirements is included. TDAS satellite tracking is also addressed for two alternatives: BRTS and VLBI tracking.

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian football.

PubMed

Edgecomb, S J; Norton, K I

2006-05-01

Sports scientists require a thorough understanding of the energy demands of sports and physical activities so that optimal training strategies and game simulations can be constructed. A range of techniques has been used to both directly assess and estimate the physiological and biochemical changes during competition. A fundamental approach to understanding the contribution of the energy systems in physical activity has involved the use of time-motion studies. A number of tools have been used from simple pen and paper methods, the use of video recordings, to sophisticated electronic tracking devices. Depending on the sport, there may be difficulties in using electronic tracking devices because of concerns of player safety. This paper assesses two methods currently used to measure player movement patterns during competition: (1) global positioning technology (GPS) and (2) a computer-based tracking (CBT) system that relies on a calibrated miniaturised playing field and mechanical movements of the tracker. A range of ways was used to determine the validity and reliability of these methods for tracking Australian footballers for distance covered during games. Comparisons were also made between these methods. The results indicate distances measured using CBT overestimated the actual values (measured with a calibrated trundle wheel) by an average of about 5.8%. The GPS system overestimated the actual values by about 4.8%. Distances measured using CBT in experienced hands were as accurate as the GPS technology. Both systems showed relatively small errors in true distances.

Large scale track analysis for wide area motion imagery surveillance

NASA Astrophysics Data System (ADS)

van Leeuwen, C. J.; van Huis, J. R.; Baan, J.

2016-10-01

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the high-resolution images allow detection and tracking of moving vehicles, but this is a highly challenging task. By using a chain of computer vision detectors and machine learning techniques, we are capable of producing high quality track information of more than 40 thousand vehicles per five minutes. When faced with such a vast number of vehicular tracks, it is useful for analysts to be able to quickly query information based on region of interest, color, maneuvers or other high-level types of information, to gain insight and find relevant activities in the flood of information. In this paper we propose a set of tools, combined in a graphical user interface, which allows data analysts to survey vehicles in a large observed area. In order to retrieve (parts of) images from the high-resolution data, we developed a multi-scale tile-based video file format that allows to quickly obtain only a part, or a sub-sampling of the original high resolution image. By storing tiles of a still image according to a predefined order, we can quickly retrieve a particular region of the image at any relevant scale, by skipping to the correct frames and reconstructing the image. Location based queries allow a user to select tracks around a particular region of interest such as landmark, building or street. By using an integrated search engine, users can quickly select tracks that are in the vicinity of locations of interest. Another time-reducing method when searching for a particular vehicle, is to filter on color or color intensity. Automatic maneuver detection adds information to the tracks that can be used to find vehicles based on their behavior.

Passive Acoustic Methods for Tracking Marine Mammals Using Widely-Spaced Bottom-Mounted Hydrophones

DTIC Science & Technology

2009-09-30

HARP [Wiggins 2007] at about 400m depth on the summit of Cross Seamount , approximately 290 km south of the Hawaiian island of Oahu (dataset provided...based tracking methods developed in this project are used to support ONR award N000140910489: The ecology and acoustic behavior of minke whales in the ...N000140811142 http://www.soest.hawaii.edu/ore/faculty/nosal LONG-TERM GOALS The long-term goal of this project is to improve passive acoustic methods

Automatic Intra-Operative Stitching of Non-Overlapping Cone-Beam CT Acquisitions

PubMed Central

Fotouhi, Javad; Fuerst, Bernhard; Unberath, Mathias; Reichenstein, Stefan; Lee, Sing Chun; Johnson, Alex A.; Osgood, Greg M.; Armand, Mehran; Navab, Nassir

2018-01-01

Purpose Cone-Beam Computed Tomography (CBCT) is one of the primary imaging modalities in radiation therapy, dentistry, and orthopedic interventions. While CBCT provides crucial intraoperative information, it is bounded by a limited imaging volume, resulting in reduced effectiveness. This paper introduces an approach allowing real-time intraoperative stitching of overlapping and non-overlapping CBCT volumes to enable 3D measurements on large anatomical structures. Methods A CBCT-capable mobile C-arm is augmented with a Red-Green-Blue-Depth (RGBD) camera. An off-line co-calibration of the two imaging modalities results in co-registered video, infrared, and X-ray views of the surgical scene. Then, automatic stitching of multiple small, non-overlapping CBCT volumes is possible by recovering the relative motion of the C-arm with respect to the patient based on the camera observations. We propose three methods to recover the relative pose: RGB-based tracking of visual markers that are placed near the surgical site, RGBD-based simultaneous localization and mapping (SLAM) of the surgical scene which incorporates both color and depth information for pose estimation, and surface tracking of the patient using only depth data provided by the RGBD sensor. Results On an animal cadaver, we show stitching errors as low as 0.33 mm, 0.91 mm, and 1.72mm when the visual marker, RGBD SLAM, and surface data are used for tracking, respectively. Conclusions The proposed method overcomes one of the major limitations of CBCT C-arm systems by integrating vision-based tracking and expanding the imaging volume without any intraoperative use of calibration grids or external tracking systems. We believe this solution to be most appropriate for 3D intraoperative verification of several orthopedic procedures. PMID:29569728

Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

PubMed

Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

2011-12-01

In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

The seam visual tracking method for large structures

NASA Astrophysics Data System (ADS)

Bi, Qilin; Jiang, Xiaomin; Liu, Xiaoguang; Cheng, Taobo; Zhu, Yulong

2017-10-01

In this paper, a compact and flexible weld visual tracking method is proposed. Firstly, there was the interference between the visual device and the work-piece to be welded when visual tracking height cannot change. a kind of weld vision system with compact structure and tracking height is researched. Secondly, according to analyze the relative spatial pose between the camera, the laser and the work-piece to be welded and study with the theory of relative geometric imaging, The mathematical model between image feature parameters and three-dimensional trajectory of the assembly gap to be welded is established. Thirdly, the visual imaging parameters of line structured light are optimized by experiment of the weld structure of the weld. Fourth, the interference that line structure light will be scatters at the bright area of metal and the area of surface scratches will be bright is exited in the imaging. These disturbances seriously affect the computational efficiency. The algorithm based on the human eye visual attention mechanism is used to extract the weld characteristics efficiently and stably. Finally, in the experiment, It is verified that the compact and flexible weld tracking method has the tracking accuracy of 0.5mm in the tracking of large structural parts. It is a wide range of industrial application prospects.

Design of an autonomous teleoperated cargo transporting vehicle for lunar base operations

NASA Technical Reports Server (NTRS)

Holt, James; Lao, Tom; Monali, Nkoy

1989-01-01

At the turn of the century NASA plans to begin construction of a lunar base. The base will likely consist of developed areas (i.e., habitation, laboratory, landing and launching sites, power plant) separated from each other due to safety considerations. The Self-Repositioning Track Vehicle (SRTV) was designed to transport cargo between these base facilities. The SRTV operates by using two robotic arms to raise and position segments of track upon which the vehicle travels. The SRTV utilizes the semiautonomous mobility (SAM) method of teleoperation; actuator-controlled interlocking track sections; two robotic arms each with five degrees of freedom; and these materials: titanium for structural members and aluminum for shell members, with the possible use of light-weight, high-strength composites.

A method to track rotational motion for use in single-molecule biophysics.

PubMed

Lipfert, Jan; Kerssemakers, Jacob J W; Rojer, Maylon; Dekker, Nynke H

2011-10-01

The double helical nature of DNA links many cellular processes such as DNA replication, transcription, and repair to rotational motion and the accumulation of torsional strain. Magnetic tweezers (MTs) are a single-molecule technique that enables the application of precisely calibrated stretching forces to nucleic acid tethers and to control their rotational motion. However, conventional magnetic tweezers do not directly monitor rotation or measure torque. Here, we describe a method to directly measure rotational motion of particles in MT. The method relies on attaching small, non-magnetic beads to the magnetic beads to act as fiducial markers for rotational tracking. CCD images of the beads are analyzed with a tracking algorithm specifically designed to minimize crosstalk between translational and rotational motion: first, the in-plane center position of the magnetic bead is determined with a kernel-based tracker, while subsequently the height and rotation angle of the bead are determined via correlation-based algorithms. Evaluation of the tracking algorithm using both simulated images and recorded images of surface-immobilized beads demonstrates a rotational resolution of 0.1°, while maintaining a translational resolution of 1-2 nm. Example traces of the rotational fluctuations exhibited by DNA-tethered beads confined in magnetic potentials of varying stiffness demonstrate the robustness of the method and the potential for simultaneous tracking of multiple beads. Our rotation tracking algorithm enables the extension of MTs to magnetic torque tweezers (MTT) to directly measure the torque in single molecules. In addition, we envision uses of the algorithm in a range of biophysical measurements, including further extensions of MT, tethered particle motion, and optical trapping measurements.

Application of the SRI cloud-tracking technique to rapid-scan GOES observations

NASA Technical Reports Server (NTRS)

Wolf, D. E.; Endlich, R. M.

1980-01-01

An automatic cloud tracking system was applied to multilayer clouds associated with severe storms. The method was tested using rapid scan observations of Hurricane Eloise obtained by the GOES satellite on 22 September 1975. Cloud tracking was performed using clustering based either on visible or infrared data. The clusters were tracked using two different techniques. The data of 4 km and 8 km resolution of the automatic system yielded comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System.

Design of a Solar Tracking System Using the Brightest Region in the Sky Image Sensor

PubMed Central

Wei, Ching-Chuan; Song, Yu-Chang; Chang, Chia-Chi; Lin, Chuan-Bi

2016-01-01

Solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection it offers. However, the conversion efficiency of solar energy is still low. If the photovoltaic panel perpendicularly tracks the sun, the solar energy conversion efficiency will be improved. In this article, we propose an innovative method to track the sun using an image sensor. In our method, it is logical to assume the points of the brightest region in the sky image representing the location of the sun. Then, the center of the brightest region is assumed to be the solar-center, and is mathematically calculated using an embedded processor (Raspberry Pi). Finally, the location information on the sun center is sent to the embedded processor to control two servo motors that are capable of moving both horizontally and vertically to track the sun. In comparison with the existing sun tracking methods using image sensors, such as the Hough transform method, our method based on the brightest region in the sky image remains accurate under conditions such as a sunny day and building shelter. The practical sun tracking system using our method was implemented and tested. The results reveal that the system successfully captured the real sun center in most weather conditions, and the servo motor system was able to direct the photovoltaic panel perpendicularly to the sun center. In addition, our system can be easily and practically integrated, and can operate in real-time. PMID:27898002

Design of a Solar Tracking System Using the Brightest Region in the Sky Image Sensor.

PubMed

Wei, Ching-Chuan; Song, Yu-Chang; Chang, Chia-Chi; Lin, Chuan-Bi

2016-11-25

Solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection it offers. However, the conversion efficiency of solar energy is still low. If the photovoltaic panel perpendicularly tracks the sun, the solar energy conversion efficiency will be improved. In this article, we propose an innovative method to track the sun using an image sensor. In our method, it is logical to assume the points of the brightest region in the sky image representing the location of the sun. Then, the center of the brightest region is assumed to be the solar-center, and is mathematically calculated using an embedded processor (Raspberry Pi). Finally, the location information on the sun center is sent to the embedded processor to control two servo motors that are capable of moving both horizontally and vertically to track the sun. In comparison with the existing sun tracking methods using image sensors, such as the Hough transform method, our method based on the brightest region in the sky image remains accurate under conditions such as a sunny day and building shelter. The practical sun tracking system using our method was implemented and tested. The results reveal that the system successfully captured the real sun center in most weather conditions, and the servo motor system was able to direct the photovoltaic panel perpendicularly to the sun center. In addition, our system can be easily and practically integrated, and can operate in real-time.

Development of a vehicle-track model assembly and numerical method for simulation of wheel-rail dynamic interaction due to unsupported sleepers

NASA Astrophysics Data System (ADS)

Zhu, Jian Jun; Ahmed, A. K. W.; Rakheja, Subhash; Khajepour, Amir

2010-12-01

In practice, it is not very uncommon to find railway track systems with unsupported sleepers due to the uneven settlement of a ballasted track system. These unsupported sleepers are among the major vibration excitations for a train and track system when a train moves forwards on a track. The vibration induced by unsupported sleepers can cause a large dynamic contact force between wheels and rails. For heavily loaded high-speed trains, the deteriorated sleeper support may lead to accelerated degradation of the railway track and vehicle components, and may thus impose safety risk to the operation. This paper presents analyses of a coupled vehicle-track assembly consisting of a roll plane vehicle model, a continuous track system model and an adaptive wheel-rail contact model. In order to improve the simulation efficiency, a numerical approach based on the central finite difference method is proposed in this investigation. The developed model assembly and proposed simulation method are utilised to simulate the vehicle-track dynamic interaction in the presence of unsupported sleepers. The dynamic response in terms of the dynamic wheel-rail interaction force due to one or multiple unsupported sleepers is studied. Important factors influencing the dynamic wheel-rail interaction force in the presence of sleeper voids are also investigated. The results show that the vehicle speed, the gap size and the number of unsupported sleepers primarily dictate the magnitude of impact load which can be significant.

Probabilistic multi-person localisation and tracking in image sequences

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2017-05-01

The localisation and tracking of persons in image sequences in commonly guided by recursive filters. Especially in a multi-object tracking environment, where mutual occlusions are inherent, the predictive model is prone to drift away from the actual target position when not taking context into account. Further, if the image-based observations are imprecise, the trajectory is prone to be updated towards a wrong position. In this work we address both these problems by using a new predictive model on the basis of Gaussian Process Regression, and by using generic object detection, as well as instance-specific classification, for refined localisation. The predictive model takes into account the motion of every tracked pedestrian in the scene and the prediction is executed with respect to the velocities of neighbouring persons. In contrast to existing methods our approach uses a Dynamic Bayesian Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image, are modelled as unknowns. This allows the detection to be corrected before it is incorporated into the recursive filter. Our method is evaluated on a publicly available benchmark dataset and outperforms related methods in terms of geometric precision and tracking accuracy.

Discriminative object tracking via sparse representation and online dictionary learning.

PubMed

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Crystal Identification in Dual-Layer-Offset DOI-PET Detectors Using Stratified Peak Tracking Based on SVD and Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Dai, Tiantian; Ma, Tianyu; Liu, Yaqiang; Gu, Yu

2016-10-01

An Anger-logic based pixelated PET detector block requires a crystal position map (CPM) to assign the position of each detected event to a most probable crystal index. Accurate assignments are crucial to PET imaging performance. In this paper, we present a novel automatic approach to generate the CPMs for dual-layer offset (DLO) PET detectors using a stratified peak tracking method. In which, the top and bottom layers are distinguished by their intensity difference and the peaks of the top and bottom layers are tracked based on a singular value decomposition (SVD) and mean-shift algorithm in succession. The CPM is created by classifying each pixel to its nearest peak and assigning the pixel with the crystal index of that peak. A Matlab-based graphical user interface program was developed including the automatic algorithm and a manual interaction procedure. The algorithm was tested for three DLO PET detector blocks. Results show that the proposed method exhibits good performance as well as robustness for all the three blocks. Compared to the existing methods, our approach can directly distinguish the layer and crystal indices using the information of intensity and offset grid pattern.

Three plot correlation-based small infrared target detection in dense sun-glint environment for infrared search and track

NASA Astrophysics Data System (ADS)

Kim, Sungho; Choi, Byungin; Kim, Jieun; Kwon, Soon; Kim, Kyung-Tae

2012-05-01

This paper presents a separate spatio-temporal filter based small infrared target detection method to address the sea-based infrared search and track (IRST) problem in dense sun-glint environment. It is critical to detect small infrared targets such as sea-skimming missiles or asymmetric small ships for national defense. On the sea surface, sun-glint clutters degrade the detection performance. Furthermore, if we have to detect true targets using only three images with a low frame rate camera, then the problem is more difficult. We propose a novel three plot correlation filter and statistics based clutter reduction method to achieve robust small target detection rate in dense sun-glint environment. We validate the robust detection performance of the proposed method via real infrared test sequences including synthetic targets.

Real Time Target Tracking in a Phantom Using Ultrasonic Imaging

NASA Astrophysics Data System (ADS)

Xiao, X.; Corner, G.; Huang, Z.

In this paper we present a real-time ultrasound image guidance method suitable for tracking the motion of tumors. A 2D ultrasound based motion tracking system was evaluated. A robot was used to control the focused ultrasound and position it at the target that has been segmented from a real-time ultrasound video. Tracking accuracy and precision were investigated using a lesion mimicking phantom. Experiments have been conducted and results show sufficient efficiency of the image guidance algorithm. This work could be developed as the foundation for combining the real time ultrasound imaging tracking and MRI thermometry monitoring non-invasive surgery.

Long-Term Tracking of a Specific Vehicle Using Airborne Optical Camera Systems

NASA Astrophysics Data System (ADS)

Kurz, F.; Rosenbaum, D.; Runge, H.; Cerra, D.; Mattyus, G.; Reinartz, P.

2016-06-01

In this paper we present two low cost, airborne sensor systems capable of long-term vehicle tracking. Based on the properties of the sensors, a method for automatic real-time, long-term tracking of individual vehicles is presented. This combines the detection and tracking of the vehicle in low frame rate image sequences and applies the lagged Cell Transmission Model (CTM) to handle longer tracking outages occurring in complex traffic situations, e.g. tunnels. The CTM model uses the traffic conditions in the proximities of the target vehicle and estimates its motion to predict the position where it reappears. The method is validated on an airborne image sequence acquired from a helicopter. Several reference vehicles are tracked within a range of 500m in a complex urban traffic situation. An artificial tracking outage of 240m is simulated, which is handled by the CTM. For this, all the vehicles in the close proximity are automatically detected and tracked to estimate the basic density-flow relations of the CTM model. Finally, the real and simulated trajectories of the reference vehicles in the outage are compared showing good correspondence also in congested traffic situations.

Target tracking system based on preliminary and precise two-stage compound cameras

NASA Astrophysics Data System (ADS)

Shen, Yiyan; Hu, Ruolan; She, Jun; Luo, Yiming; Zhou, Jie

2018-02-01

Early detection of goals and high-precision of target tracking is two important performance indicators which need to be balanced in actual target search tracking system. This paper proposed a target tracking system with preliminary and precise two - stage compound. This system using a large field of view to achieve the target search. After the target was searched and confirmed, switch into a small field of view for two field of view target tracking. In this system, an appropriate filed switching strategy is the key to achieve tracking. At the same time, two groups PID parameters are add into the system to reduce tracking error. This combination way with preliminary and precise two-stage compound can extend the scope of the target and improve the target tracking accuracy and this method has practical value.

Geometric estimation of intestinal contraction for motion tracking of video capsule endoscope

NASA Astrophysics Data System (ADS)

Mi, Liang; Bao, Guanqun; Pahlavan, Kaveh

2014-03-01

Wireless video capsule endoscope (VCE) provides a noninvasive method to examine the entire gastrointestinal (GI) tract, especially small intestine, where other endoscopic instruments can barely reach. VCE is able to continuously provide clear pictures in short fixed intervals, and as such researchers have attempted to use image processing methods to track the video capsule in order to locate the abnormalities inside the GI tract. To correctly estimate the speed of the motion of the endoscope capsule, the radius of the intestinal track must be known a priori. Physiological factors such as intestinal contraction, however, dynamically change the radius of the small intestine, which could bring large errors in speed estimation. In this paper, we are aiming to estimate the radius of the contracted intestinal track. First a geometric model is presented for estimating the radius of small intestine based on the black hole on endoscopic images. To validate our proposed model, a 3-dimentional virtual testbed that emulates the intestinal contraction is then introduced in details. After measuring the size of the black holes on the test images, we used our model to esimate the radius of the contracted intestinal track. Comparision between analytical results and the emulation model parameters has verified that our proposed method could preciously estimate the radius of the contracted small intestine based on endoscopic images.

Skull registration for prone patient position using tracked ultrasound

NASA Astrophysics Data System (ADS)

Underwood, Grace; Ungi, Tamas; Baum, Zachary; Lasso, Andras; Kronreif, Gernot; Fichtinger, Gabor

2017-03-01

PURPOSE: Tracked navigation has become prevalent in neurosurgery. Problems with registration of a patient and a preoperative image arise when the patient is in a prone position. Surfaces accessible to optical tracking on the back of the head are unreliable for registration. We investigated the accuracy of surface-based registration using points accessible through tracked ultrasound. Using ultrasound allows access to bone surfaces that are not available through optical tracking. Tracked ultrasound could eliminate the need to work (i) under the table for registration and (ii) adjust the tracker between surgery and registration. In addition, tracked ultrasound could provide a non-invasive method in comparison to an alternative method of registration involving screw implantation. METHODS: A phantom study was performed to test the feasibility of tracked ultrasound for registration. An initial registration was performed to partially align the pre-operative computer tomography data and skull phantom. The initial registration was performed by an anatomical landmark registration. Surface points accessible by tracked ultrasound were collected and used to perform an Iterative Closest Point Algorithm. RESULTS: When the surface registration was compared to a ground truth landmark registration, the average TRE was found to be 1.6+/-0.1mm and the average distance of points off the skull surface was 0.6+/-0.1mm. CONCLUSION: The use of tracked ultrasound is feasible for registration of patients in prone position and eliminates the need to perform registration under the table. The translational component of error found was minimal. Therefore, the amount of TRE in registration is due to a rotational component of error.

Significant body point labeling and tracking.

PubMed

Azhar, Faisal; Tjahjadi, Tardi

2014-09-01

In this paper, a method is presented to label and track anatomical landmarks (e.g., head, hand/arm, feet), which are referred to as significant body points (SBPs), using implicit body models. By considering the human body as an inverted pendulum model, ellipse fitting and contour moments are applied to classify it as being in Stand, Sit, or Lie posture. A convex hull of the silhouette contour is used to determine the locations of SBPs. The particle filter or a motion flow-based method is used to predict SBPs in occlusion. Stick figures of various activities are generated by connecting the SBPs. The qualitative and quantitative evaluation show that the proposed method robustly labels and tracks SBPs in various activities of two different (low and high) resolution data sets.

Super-resolution imaging applied to moving object tracking

NASA Astrophysics Data System (ADS)

Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

2017-10-01

Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

Modeling the effects of high-G stress on pilots in a tracking task

NASA Technical Reports Server (NTRS)

Korn, J.; Kleinman, D. L.

1978-01-01

Air-to-air tracking experiments were conducted at the Aerospace Medical Research Laboratories using both fixed and moving base dynamic environment simulators. The obtained data, which includes longitudinal error of a simulated air-to-air tracking task as well as other auxiliary variables, was analyzed using an ensemble averaging method. In conjunction with these experiments, the optimal control model is applied to model a human operator under high-G stress.

Using the Image Analysis Method for Describing Soil Detachment by a Single Water Drop Impact

PubMed Central

Ryżak, Magdalena; Bieganowski, Andrzej

2012-01-01

The aim of the present work was to develop a method based on image analysis for describing soil detachment caused by the impact of a single water drop. The method consisted of recording tracks made by splashed particles on blotting paper under an optical microscope. The analysis facilitated division of the recorded particle tracks on the paper into drops, “comets” and single particles. Additionally, the following relationships were determined: (i) the distances of splash; (ii) the surface areas of splash tracks into relation to distance; (iii) the surface areas of the solid phase transported over a given distance; and (iv) the ratio of the solid phase to the splash track area in relation to distance. Furthermore, the proposed method allowed estimation of the weight of soil transported by a single water drop splash in relation to the distance of the water drop impact. It was concluded that the method of image analysis of splashed particles facilitated analysing the results at very low water drop energy and generated by single water drops.

Can low-cost motion-tracking systems substitute a Polhemus system when researching social motor coordination in children?

PubMed

Romero, Veronica; Amaral, Joseph; Fitzpatrick, Paula; Schmidt, R C; Duncan, Amie W; Richardson, Michael J

2017-04-01

Functionally stable and robust interpersonal motor coordination has been found to play an integral role in the effectiveness of social interactions. However, the motion-tracking equipment required to record and objectively measure the dynamic limb and body movements during social interaction has been very costly, cumbersome, and impractical within a non-clinical or non-laboratory setting. Here we examined whether three low-cost motion-tracking options (Microsoft Kinect skeletal tracking of either one limb or whole body and a video-based pixel change method) can be employed to investigate social motor coordination. Of particular interest was the degree to which these low-cost methods of motion tracking could be used to capture and index the coordination dynamics that occurred between a child and an experimenter for three simple social motor coordination tasks in comparison to a more expensive, laboratory-grade motion-tracking system (i.e., a Polhemus Latus system). Overall, the results demonstrated that these low-cost systems cannot substitute the Polhemus system in some tasks. However, the lower-cost Microsoft Kinect skeletal tracking and video pixel change methods were successfully able to index differences in social motor coordination in tasks that involved larger-scale, naturalistic whole body movements, which can be cumbersome and expensive to record with a Polhemus. However, we found the Kinect to be particularly vulnerable to occlusion and the pixel change method to movements that cross the video frame midline. Therefore, particular care needs to be taken in choosing the motion-tracking system that is best suited for the particular research.

Comparative analysis of three different methods for monitoring the use of green bridges by wildlife.

PubMed

Gužvica, Goran; Bošnjak, Ivana; Bielen, Ana; Babić, Danijel; Radanović-Gužvica, Biserka; Šver, Lidija

2014-01-01

Green bridges are used to decrease highly negative impact of roads/highways on wildlife populations and their effectiveness is evaluated by various monitoring methods. Based on the 3-year monitoring of four Croatian green bridges, we compared the effectiveness of three indirect monitoring methods: track-pads, camera traps and active infrared (IR) trail monitoring system. The ability of the methods to detect different species and to give good estimation of number of animal crossings was analyzed. The accuracy of species detection by track-pad method was influenced by granulometric composition of track-pad material, with the best results obtained with higher percentage of silt and clay. We compared the species composition determined by track-pad and camera trap methods and found that monitoring by tracks underestimated the ratio of small canids, while camera traps underestimated the ratio of roe deer. Regarding total number of recorder events, active IR detectors recorded from 11 to 19 times more events then camera traps and app. 80% of them were not caused by animal crossings. Camera trap method underestimated the real number of total events. Therefore, an algorithm for filtration of the IR dataset was developed for approximation of the real number of crossings. Presented results are valuable for future monitoring of wildlife crossings in Croatia and elsewhere, since advantages and disadvantages of used monitoring methods are shown. In conclusion, different methods should be chosen/combined depending on the aims of the particular monitoring study.

Fission-track dating applied to mineral exploration

USGS Publications Warehouse

Naeser, C.W.

1984-01-01

The partial to total resetting of fission-track ages of minerals in country rock near a mineralized area can be used to (1) locate a thermal anomaly, and (2) date the mineralizing event. Two mining districts in Colorado have been studied - Rico and Gilman. Rico is a precious- and base-metal mining district. Initial fission-track dating of a sill located about 6 km from the center of the district gave ages of 20 Myr and 65 Myr for apatite and zircon, respectively. The Eagle Mine in the Gilman District is the largest producer of zinc in the state of Colorado. Fission-track dating of zircon from a 70 Myr-old sill shows partial resetting of the zircon (45 Myr). The thermal anomaly identified by fission-track dating is seen in both districts far outside the area affected by obvious alteration. Based on the results of these two pilot studies, fission-track dating can be a useful exploration method for thermal anomalies associated with buried or otherwise poorly expressed mineral deposits.

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

Ishii, H.; Fujino, H.; Bian, Z.

In this study, two types of marker-based tracking methods for Augmented Reality have been developed. One is a method which employs line-shaped markers and the other is a method which employs circular-shaped markers. These two methods recognize the markers by means of image processing and calculate the relative position and orientation between the markers and the camera in real time. The line-shaped markers are suitable to be pasted in the buildings such as NPPs where many pipes and tanks exist. The circular-shaped markers are suitable for the case that there are many obstacles and it is difficult to use line-shapedmore » markers because the obstacles hide the part of the line-shaped markers. Both methods can extend the maximum distance between the markers and the camera compared to the legacy marker-based tracking methods. (authors)« less

Use of Nanoparticle Contrast Agents for Cell Tracking with Computed Tomography

PubMed Central

2017-01-01

Efforts to develop novel cell-based therapies originated with the first bone marrow transplant on a leukemia patient in 1956. Preclinical and clinical examples of cell-based treatment strategies have shown promising results across many disciplines in medicine, with recent advances in immune cell therapies for cancer producing remarkable response rates, even in patients with multiple treatment failures. However, cell-based therapies suffer from inconsistent outcomes, motivating the search for tools that allow monitoring of cell delivery and behavior in vivo. Noninvasive cell imaging techniques, also known as cell tracking, have been developed to address this issue. These tools can allow real-time, quantitative, and long-term monitoring of transplanted cells in the recipient, providing insight on cell migration, distribution, viability, differentiation, and fate, all of which play crucial roles in treatment efficacy. Understanding these parameters allows the optimization of cell choice, delivery route, and dosage for therapy and advances cell-based therapy for specific clinical uses. To date, most cell tracking work has centered on imaging modalities such as MRI, radionuclide imaging, and optical imaging. However, X-ray computed tomography (CT) is an emerging method for cell tracking that has several strengths such as high spatial and temporal resolution, and excellent quantitative capabilities. The advantages of CT for cell tracking are enhanced by its wide availability and cost effectiveness, allowing CT to become one of the most popular clinical imaging modalities and a key asset in disease diagnosis. In this review, we will discuss recent advances in cell tracking methods using X-ray CT in various applications, in addition to predictions on how the field will progress. PMID:28485976

Automated identification and tracking of polar-cap plasma patches at solar minimum

NASA Astrophysics Data System (ADS)

Burston, R.; Hodges, K.; Astin, I.; Jayachandran, P. T.

2014-03-01

A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

Robust Pedestrian Tracking and Recognition from FLIR Video: A Unified Approach via Sparse Coding

PubMed Central

Li, Xin; Guo, Rui; Chen, Chao

2014-01-01

Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the analysis of forward-looking infrared (FLIR) video to support nighttime machine vision systems. A key technical contribution of this work is to unify existing sparse coding-based approaches toward tracking and recognition under the same framework, so that they can benefit from each other in a closed-loop. On the one hand, tracking the same object through temporal frames allows us to achieve improved recognition performance through dynamical updating of template/dictionary and combining multiple recognition results; on the other hand, the recognition of individual objects facilitates the tracking of multiple objects (i.e., walking pedestrians), especially in the presence of occlusion within a crowded environment. We report experimental results on both the CASIAPedestrian Database and our own collected FLIR video database to demonstrate the effectiveness of the proposed joint tracking-and-recognition approach. PMID:24961216

Improved Leg Tracking Considering Gait Phase and Spline-Based Interpolation during Turning Motion in Walk Tests.

PubMed

Yorozu, Ayanori; Moriguchi, Toshiki; Takahashi, Masaki

2015-09-04

Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other, and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association considering gait phase and a Catmull-Rom spline-based interpolation during the occlusion are proposed. From the experimental results with young people, we confirm   that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared to a three-dimensional motion analysis system (VICON).

Gamma-ray momentum reconstruction from Compton electron trajectories by filtered back-projection

DOE PAGES

Haefner, A.; Gunter, D.; Plimley, B.; ...

2014-11-03

Gamma-ray imaging utilizing Compton scattering has traditionally relied on measuring coincident gamma-ray interactions to map directional information of the source distribution. This coincidence requirement makes it an inherently inefficient process. We present an approach to gamma-ray reconstruction from Compton scattering that requires only a single electron tracking detector, thus removing the coincidence requirement. From the Compton scattered electron momentum distribution, our algorithm analytically computes the incident photon's correlated direction and energy distributions. Because this method maps the source energy and location, it is useful in applications, where prior information about the source distribution is unknown. We demonstrate this method withmore » electron tracks measured in a scientific Si charge coupled device. While this method was demonstrated with electron tracks in a Si-based detector, it is applicable to any detector that can measure electron direction and energy, or equivalently the electron momentum. For example, it can increase the sensitivity to obtain energy and direction in gas-based systems that suffer from limited efficiency.« less

Comparison of Two Alternative Methods for Tracking Toe Trajectory

NASA Technical Reports Server (NTRS)

Miller, Chris; Peters, Brian; Brady, Rachel; Mulavara, Ajitkumar; Warren, Liz; Feiveson, Al; Bloomberg, Jacob

2007-01-01

Toe trajectory during the swing phase of locomotion has been identified as a precise motor control task (Karst, et al., 1999). The standard method for tracking toe trajectory is to place a marker on the superior aspect of the distal end of the 2nd toe itself (Karst, et al., 1999; Winter, 1992). However, others have based their toe trajectory results either on a marker positioned on the lateral aspect of the 5th metatarsal head (Dingwell, et al., 1999; Osaki, et al., 2007), or on a virtual toe marker computed at the anterior tip of the second toe based on the positions of other real foot markers (Miller, et al., 2006). While these methods for tracking the toe may seem similar, their results may not be directly comparable. The purpose of this study was to compute toe trajectory parameters using a 5th metatarsal marker and a virtual toe marker, and compare their results with those of the standard toe marker.

Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

NASA Astrophysics Data System (ADS)

Li, Ze

2017-09-01

In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

3D deformable organ model based liver motion tracking in ultrasound videos

NASA Astrophysics Data System (ADS)

Kim, Jung-Bae; Hwang, Youngkyoo; Oh, Young-Taek; Bang, Won-Chul; Lee, Heesae; Kim, James D. K.; Kim, Chang Yeong

2013-03-01

This paper presents a novel method of using 2D ultrasound (US) cine images during image-guided therapy to accurately track the 3D position of a tumor even when the organ of interest is in motion due to patient respiration. Tracking is possible thanks to a 3D deformable organ model we have developed. The method consists of three processes in succession. The first process is organ modeling where we generate a personalized 3D organ model from high quality 3D CT or MR data sets captured during three different respiratory phases. The model includes the organ surface, vessel and tumor, which can all deform and move in accord with patient respiration. The second process is registration of the organ model to 3D US images. From 133 respiratory phase candidates generated from the deformable organ model, we resolve the candidate that best matches the 3D US images according to vessel centerline and surface. As a result, we can determine the position of the US probe. The final process is real-time tracking using 2D US cine images captured by the US probe. We determine the respiratory phase by tracking the diaphragm on the image. The 3D model is then deformed according to respiration phase and is fitted to the image by considering the positions of the vessels. The tumor's 3D positions are then inferred based on respiration phase. Testing our method on real patient data, we have found the accuracy of 3D position is within 3.79mm and processing time is 5.4ms during tracking.

Rapid Antibiotic Susceptibility Testing of Uropathogenic E. coli by Tracking Submicron Scale Motion of Single Bacterial Cells.

PubMed

Syal, Karan; Shen, Simon; Yang, Yunze; Wang, Shaopeng; Haydel, Shelley E; Tao, Nongjian

2017-08-25

To combat antibiotic resistance, a rapid antibiotic susceptibility testing (AST) technology that can identify resistant infections at disease onset is required. Current clinical AST technologies take 1-3 days, which is often too slow for accurate treatment. Here we demonstrate a rapid AST method by tracking sub-μm scale bacterial motion with an optical imaging and tracking technique. We apply the method to clinically relevant bacterial pathogens, Escherichia coli O157: H7 and uropathogenic E. coli (UPEC) loosely tethered to a glass surface. By analyzing dose-dependent sub-μm motion changes in a population of bacterial cells, we obtain the minimum bactericidal concentration within 2 h using human urine samples spiked with UPEC. We validate the AST method using the standard culture-based AST methods. In addition to population studies, the method allows single cell analysis, which can identify subpopulations of resistance strains within a sample.

A computer-vision-based rotating speed estimation method for motor bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Wang, Xiaoxian; Guo, Jie; Lu, Siliang; Shen, Changqing; He, Qingbo

2017-06-01

Diagnosis of motor bearing faults under variable speed is a problem. In this study, a new computer-vision-based order tracking method is proposed to address this problem. First, a video recorded by a high-speed camera is analyzed with the speeded-up robust feature extraction and matching algorithm to obtain the instantaneous rotating speed (IRS) of the motor. Subsequently, an audio signal recorded by a microphone is equi-angle resampled for order tracking in accordance with the IRS curve, through which the frequency-domain signal is transferred to an angular-domain one. The envelope order spectrum is then calculated to determine the fault characteristic order, and finally the bearing fault pattern is determined. The effectiveness and robustness of the proposed method are verified with two brushless direct-current motor test rigs, in which two defective bearings and a healthy bearing are tested separately. This study provides a new noninvasive measurement approach that simultaneously avoids the installation of a tachometer and overcomes the disadvantages of tacholess order tracking methods for motor bearing fault diagnosis under variable speed.

Registration using natural features for augmented reality systems.

PubMed

Yuan, M L; Ong, S K; Nee, A Y C

2006-01-01

Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have been conducted to validate the performance of this proposed method.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

PubMed

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-04-15

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

PubMed Central

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-01-01

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505

Contribution of macrophages in the contrast loss in iron oxide-based MRI cancer cell tracking studies

PubMed Central

Danhier, Pierre; Deumer, Gladys; Joudiou, Nicolas; Bouzin, Caroline; Levêque, Philippe; Haufroid, Vincent; Jordan, Bénédicte F.; Feron, Olivier; Sonveaux, Pierre; Gallez, Bernard

2017-01-01

Magnetic resonance imaging (MRI) cell tracking of cancer cells labeled with superparamagnetic iron oxides (SPIO) allows visualizing metastatic cells in preclinical models. However, previous works showed that the signal void induced by SPIO on T2(*)-weighted images decreased over time. Here, we aim at characterizing the fate of iron oxide nanoparticles used in cell tracking studies and the role of macrophages in SPIO metabolism. In vivo MRI cell tracking of SPIO positive 4T1 breast cancer cells revealed a quick loss of T2* contrast after injection. We next took advantage of electron paramagnetic resonance (EPR) spectroscopy and inductively coupled plasma mass spectroscopy (ICP-MS) for characterizing the evolution of superparamagnetic and non-superparamagnetic iron pools in 4T1 breast cancer cells and J774 macrophages after SPIO labeling. These in vitro experiments and histology studies performed on 4T1 tumors highlighted the quick degradation of iron oxides by macrophages in SPIO-based cell tracking experiments. In conclusion, the release of SPIO by dying cancer cells and the subsequent uptake of iron oxides by tumor macrophages are limiting factors in MRI cell tracking experiments that plead for the use of (MR) reporter-gene based imaging methods for the long-term tracking of metastatic cells. PMID:28467814

Video-based measurements for wireless capsule endoscope tracking

NASA Astrophysics Data System (ADS)

Spyrou, Evaggelos; Iakovidis, Dimitris K.

2014-01-01

The wireless capsule endoscope is a swallowable medical device equipped with a miniature camera enabling the visual examination of the gastrointestinal (GI) tract. It wirelessly transmits thousands of images to an external video recording system, while its location and orientation are being tracked approximately by external sensor arrays. In this paper we investigate a video-based approach to tracking the capsule endoscope without requiring any external equipment. The proposed method involves extraction of speeded up robust features from video frames, registration of consecutive frames based on the random sample consensus algorithm, and estimation of the displacement and rotation of interest points within these frames. The results obtained by the application of this method on wireless capsule endoscopy videos indicate its effectiveness and improved performance over the state of the art. The findings of this research pave the way for a cost-effective localization and travel distance measurement of capsule endoscopes in the GI tract, which could contribute in the planning of more accurate surgical interventions.

Three-dimensional tracking of small aquatic organisms using fluorescent nanoparticles.

PubMed

Ekvall, Mikael T; Bianco, Giuseppe; Linse, Sara; Linke, Heiner; Bäckman, Johan; Hansson, Lars-Anders

2013-01-01

Tracking techniques are vital for the understanding of the biology and ecology of organisms. While such techniques have provided important information on the movement and migration of large animals, such as mammals and birds, scientific advances in understanding the individual behaviour and interactions of small (mm-scale) organisms have been hampered by constraints, such as the sizes of existing tracking devices, in existing tracking methods. By combining biology, chemistry and physics we here present a method that allows three-dimensional (3D) tracking of individual mm-sized aquatic organisms. The method is based on in-vivo labelling of the organisms with fluorescent nanoparticles, so-called quantum dots, and tracking of the organisms in 3D via the quantum-dot fluorescence using a synchronized multiple camera system. It allows for the efficient and simultaneous study of the behaviour of one as well as multiple individuals in large volumes of observation, thus enabling the study of behavioural interactions at the community scale. The method is non-perturbing - we demonstrate that the labelling is not affecting the behavioural response of the organisms - and is applicable over a wide range of taxa, including cladocerans as well as insects, suggesting that our methodological concept opens up for new research fields on individual behaviour of small animals. Hence, this offers opportunities to focus on important biological, ecological and behavioural questions never before possible to address.

Low-Latency Line Tracking Using Event-Based Dynamic Vision Sensors

PubMed Central

Everding, Lukas; Conradt, Jörg

2018-01-01

In order to safely navigate and orient in their local surroundings autonomous systems need to rapidly extract and persistently track visual features from the environment. While there are many algorithms tackling those tasks for traditional frame-based cameras, these have to deal with the fact that conventional cameras sample their environment with a fixed frequency. Most prominently, the same features have to be found in consecutive frames and corresponding features then need to be matched using elaborate techniques as any information between the two frames is lost. We introduce a novel method to detect and track line structures in data streams of event-based silicon retinae [also known as dynamic vision sensors (DVS)]. In contrast to conventional cameras, these biologically inspired sensors generate a quasicontinuous stream of vision information analogous to the information stream created by the ganglion cells in mammal retinae. All pixels of DVS operate asynchronously without a periodic sampling rate and emit a so-called DVS address event as soon as they perceive a luminance change exceeding an adjustable threshold. We use the high temporal resolution achieved by the DVS to track features continuously through time instead of only at fixed points in time. The focus of this work lies on tracking lines in a mostly static environment which is observed by a moving camera, a typical setting in mobile robotics. Since DVS events are mostly generated at object boundaries and edges which in man-made environments often form lines they were chosen as feature to track. Our method is based on detecting planes of DVS address events in x-y-t-space and tracing these planes through time. It is robust against noise and runs in real time on a standard computer, hence it is suitable for low latency robotics. The efficacy and performance are evaluated on real-world data sets which show artificial structures in an office-building using event data for tracking and frame data for ground-truth estimation from a DAVIS240C sensor. PMID:29515386

3-D model-based vehicle tracking.

PubMed

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

An Empirical Human Controller Model for Preview Tracking Tasks.

PubMed

van der El, Kasper; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus Rene M; Mulder, Max

2016-11-01

Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.

Does navigated transcranial stimulation increase the accuracy of tractography? A prospective clinical trial based on intraoperative motor evoked potential monitoring during deep brain stimulation.

PubMed

Forster, Marie-Therese; Hoecker, Alexander Claudius; Kang, Jun-Suk; Quick, Johanna; Seifert, Volker; Hattingen, Elke; Hilker, Rüdiger; Weise, Lutz Martin

2015-06-01

Tractography based on diffusion tensor imaging has become a popular tool for delineating white matter tracts for neurosurgical procedures. To explore whether navigated transcranial magnetic stimulation (nTMS) might increase the accuracy of fiber tracking. Tractography was performed according to both anatomic delineation of the motor cortex (n = 14) and nTMS results (n = 9). After implantation of the definitive electrode, stimulation via the electrode was performed, defining a stimulation threshold for eliciting motor evoked potentials recorded during deep brain stimulation surgery. Others have shown that of arm and leg muscles. This threshold was correlated with the shortest distance between the active electrode contact and both fiber tracks. Results were evaluated by correlation to motor evoked potential monitoring during deep brain stimulation, a surgical procedure causing hardly any brain shift. Distances to fiber tracks clearly correlated with motor evoked potential thresholds. Tracks based on nTMS had a higher predictive value than tracks based on anatomic motor cortex definition (P < .001 and P = .005, respectively). However, target site, hemisphere, and active electrode contact did not influence this correlation. The implementation of tractography based on nTMS increases the accuracy of fiber tracking. Moreover, this combination of methods has the potential to become a supplemental tool for guiding electrode implantation.

Determining the bias and variance of a deterministic finger-tracking algorithm.

PubMed

Morash, Valerie S; van der Velden, Bas H M

2016-06-01

Finger tracking has the potential to expand haptic research and applications, as eye tracking has done in vision research. In research applications, it is desirable to know the bias and variance associated with a finger-tracking method. However, assessing the bias and variance of a deterministic method is not straightforward. Multiple measurements of the same finger position data will not produce different results, implying zero variance. Here, we present a method of assessing deterministic finger-tracking variance and bias through comparison to a non-deterministic measure. A proof-of-concept is presented using a video-based finger-tracking algorithm developed for the specific purpose of tracking participant fingers during a psychological research study. The algorithm uses ridge detection on videos of the participant's hand, and estimates the location of the right index fingertip. The algorithm was evaluated using data from four participants, who explored tactile maps using only their right index finger and all right-hand fingers. The algorithm identified the index fingertip in 99.78 % of one-finger video frames and 97.55 % of five-finger video frames. Although the algorithm produced slightly biased and more dispersed estimates relative to a human coder, these differences (x=0.08 cm, y=0.04 cm) and standard deviations (σ x =0.16 cm, σ y =0.21 cm) were small compared to the size of a fingertip (1.5-2.0 cm). Some example finger-tracking results are provided where corrections are made using the bias and variance estimates.

A hybrid method for accurate star tracking using star sensor and gyros.

PubMed

Lu, Jiazhen; Yang, Lie; Zhang, Hao

2017-10-01

Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

NASA Astrophysics Data System (ADS)

Tian, Yuexin; Gao, Kun; Liu, Ying; Han, Lu

2015-08-01

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

USE OF BACTEROIDES PCR-BASED METHODS TO EXAMINE FECAL CONTAMINATION SOURCES IN TROPICAL COASTAL WATERS

EPA Science Inventory

Several library independent Microbial Source Tracking methods have been developed to rapidly determine the source of fecal contamination. Thus far, none of these methods have been tested in tropical marine waters. In this study, we used a Bacteroides 16S rDNA PCR-based...

Effects of Detailed Illustrations on Science Learning: An Eye-Tracking Study

ERIC Educational Resources Information Center

Lin, Yu Ying; Holmqvist, Kenneth; Miyoshi, Kiyofumi; Ashida, Hiroshi

2017-01-01

The eye-tracking method was used to assess the influence of detailed, colorful illustrations on reading behaviors and learning outcomes. Based on participants' subjective ratings in a pre-study, we selected eight one-page human anatomy lessons. In the main study, participants learned these eight human anatomy lessons; four were accompanied by…

Global Output-Feedback Control for Simultaneous Tracking and Stabilization of Wheeled Mobile Robots

NASA Astrophysics Data System (ADS)

Chang, J.; Zhang, L. J.; Xue, D.

A time-varying global output-feedback controller is presented that solves both tracking and stabilization for wheeled mobile robots simultaneously at the torque level. The controller synthesis is based on a coordinate transformation, Lyapunov direct method and backstepping technique. The performance of the proposed controller is demonstrated by simulation.

Finite-time tracking control for multiple non-holonomic mobile robots based on visual servoing

NASA Astrophysics Data System (ADS)

Ou, Meiying; Li, Shihua; Wang, Chaoli

2013-12-01

This paper investigates finite-time tracking control problem of multiple non-holonomic mobile robots via visual servoing. It is assumed that the pinhole camera is fixed to the ceiling, and camera parameters are unknown. The desired reference trajectory is represented by a virtual leader whose states are available to only a subset of the followers, and the followers have only interaction. First, the camera-objective visual kinematic model is introduced by utilising the pinhole camera model for each mobile robot. Second, a unified tracking error system between camera-objective visual servoing model and desired reference trajectory is introduced. Third, based on the neighbour rule and by using finite-time control method, continuous distributed cooperative finite-time tracking control laws are designed for each mobile robot with unknown camera parameters, where the communication topology among the multiple mobile robots is assumed to be a directed graph. Rigorous proof shows that the group of mobile robots converges to the desired reference trajectory in finite time. Simulation example illustrates the effectiveness of our method.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm.

PubMed

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-24

Indoor occupants' positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans' position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm

PubMed Central

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-01

Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. PMID:29364188

Study of moving object detecting and tracking algorithm for video surveillance system

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhang, Rongfu

2010-10-01

This paper describes a specific process of moving target detecting and tracking in the video surveillance.Obtain high-quality background is the key to achieving differential target detecting in the video surveillance.The paper is based on a block segmentation method to build clear background,and using the method of background difference to detecing moving target,after a series of treatment we can be extracted the more comprehensive object from original image,then using the smallest bounding rectangle to locate the object.In the video surveillance system, the delay of camera and other reasons lead to tracking lag,the model of Kalman filter based on template matching was proposed,using deduced and estimated capacity of Kalman,the center of smallest bounding rectangle for predictive value,predicted the position in the next moment may appare,followed by template matching in the region as the center of this position,by calculate the cross-correlation similarity of current image and reference image,can determine the best matching center.As narrowed the scope of searching,thereby reduced the searching time,so there be achieve fast-tracking.

Mathematical imaging methods for mitosis analysis in live-cell phase contrast microscopy.

PubMed

Grah, Joana Sarah; Harrington, Jennifer Alison; Koh, Siang Boon; Pike, Jeremy Andrew; Schreiner, Alexander; Burger, Martin; Schönlieb, Carola-Bibiane; Reichelt, Stefanie

2017-02-15

In this paper we propose a workflow to detect and track mitotic cells in time-lapse microscopy image sequences. In order to avoid the requirement for cell lines expressing fluorescent markers and the associated phototoxicity, phase contrast microscopy is often preferred over fluorescence microscopy in live-cell imaging. However, common specific image characteristics complicate image processing and impede use of standard methods. Nevertheless, automated analysis is desirable due to manual analysis being subjective, biased and extremely time-consuming for large data sets. Here, we present the following workflow based on mathematical imaging methods. In the first step, mitosis detection is performed by means of the circular Hough transform. The obtained circular contour subsequently serves as an initialisation for the tracking algorithm based on variational methods. It is sub-divided into two parts: in order to determine the beginning of the whole mitosis cycle, a backwards tracking procedure is performed. After that, the cell is tracked forwards in time until the end of mitosis. As a result, the average of mitosis duration and ratios of different cell fates (cell death, no division, division into two or more daughter cells) can be measured and statistics on cell morphologies can be obtained. All of the tools are featured in the user-friendly MATLAB®Graphical User Interface MitosisAnalyser. Copyright © 2017. Published by Elsevier Inc.

Multilevel Space-Time Aggregation for Bright Field Cell Microscopy Segmentation and Tracking

PubMed Central

Inglis, Tiffany; De Sterck, Hans; Sanders, Geoffrey; Djambazian, Haig; Sladek, Robert; Sundararajan, Saravanan; Hudson, Thomas J.

2010-01-01

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant “saliency measure” is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (“object tunnels”) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system. PMID:20467468

Method and system for controlling the position of a beam of light

DOEpatents

Steinkraus, Jr., Robert F.; Johnson, Gary W [Livermore, CA; Ruggiero, Anthony J [Livermore, CA

2011-08-09

An method and system for laser beam tracking and pointing is based on a conventional position sensing detector (PSD) or quadrant cell but with the use of amplitude-modulated light. A combination of logarithmic automatic gain control, filtering, and synchronous detection offers high angular precision with exceptional dynamic range and sensitivity, while maintaining wide bandwidth. Use of modulated light enables the tracking of multiple beams simultaneously through the use of different modulation frequencies. It also makes the system resistant to interfering light sources such as ambient light. Beam pointing is accomplished by feeding back errors in the measured beam position to a beam steering element, such as a steering mirror. Closed-loop tracking performance is superior to existing methods, especially under conditions of atmospheric scintillation.

Optical tracking of acoustic radiation force impulse-induced dynamics in a tissue-mimicking phantom

PubMed Central

Bouchard, Richard R.; Palmeri, Mark L.; Pinton, Gianmarco F.; Trahey, Gregg E.; Streeter, Jason E.; Dayton, Paul A.

2009-01-01

Optical tracking was utilized to investigate the acoustic radiation force impulse (ARFI)-induced response, generated by a 5-MHz piston transducer, in a translucent tissue-mimicking phantom. Suspended 10-μm microspheres were tracked axially and laterally at multiple locations throughout the field of view of an optical microscope with 0.5-μm displacement resolution, in both dimensions, and at frame rates of up to 36 kHz. Induced dynamics were successfully captured before, during, and after the ARFI excitation at depths of up to 4.8 mm from the phantom’s proximal boundary. Results are presented for tracked axial and lateral displacements resulting from on-axis and off-axis (i.e., shear wave) acquisitions; these results are compared to matched finite element method modeling and independent ultrasonically based empirical results and yielded reasonable agreement in most cases. A shear wave reflection, generated by the proximal boundary, consistently produced an artifact in tracked displacement data later in time (i.e., after the initial ARFI-induced displacement peak). This tracking method provides high-frame-rate, two-dimensional tracking data and thus could prove useful in the investigation of complex ARFI-induced dynamics in controlled experimental settings. PMID:19894849

Conceptual Design of a Communication-Based Deep Space Navigation Network

NASA Technical Reports Server (NTRS)

Anzalone, Evan J.; Chuang, C. H.

2012-01-01

As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.

Measurement of left ventricular torsion using block-matching-based speckle tracking for two-dimensional echocardiography

NASA Astrophysics Data System (ADS)

Sun, Feng-Rong; Wang, Xiao-Jing; Wu, Qiang; Yao, Gui-Hua; Zhang, Yun

2013-01-01

Left ventricular (LV) torsion is a sensitive and global index of LV systolic and diastolic function, but how to noninvasively measure it is challenging. Two-dimensional echocardiography and the block-matching based speckle tracking method were used to measure LV torsion. Main advantages of the proposed method over the previous ones are summarized as follows: (1) The method is automatic, except for manually selecting some endocardium points on the end-diastolic frame in initialization step. (2) The diamond search strategy is applied, with a spatial smoothness constraint introduced into the sum of absolute differences matching criterion; and the reference frame during the search is determined adaptively. (3) The method is capable of removing abnormal measurement data automatically. The proposed method was validated against that using Doppler tissue imaging and some preliminary clinical experimental studies were presented to illustrate clinical values of the proposed method.

Tracking coherent structures in massively-separated and turbulent flows

NASA Astrophysics Data System (ADS)

Rockwood, Matthew; Huang, Yangzi; Green, Melissa

2018-01-01

Coherent vortex structures are tracked in simulations of massively-separated and turbulent flows. Topological Lagrangian saddle points are found using intersections of the positive and negative finite-time Lyapunov exponent ridges, and these points are then followed in order to track individual coherent structure motion both in a complex interacting three-dimensional flow (turbulent channel) and during vortex formation (two-dimensional bluff body shedding). For a simulation of wall-bounded turbulence in a channel flow, tracking Lagrangian saddles shows that the average structure convection speed exhibits a similar trend as a previously published result based on velocity and pressure correlations, giving validity to the method. When this tracking method is applied in a study of a circular cylinder in cross-flow it shows that Lagrangian saddles rapidly accelerate away from the cylinder surface as the vortex sheds. This saddle behavior is compared with the time-resolved static pressure distribution on the circular cylinder, yielding locations on a cylinder surface where common sensors could detect this phenomenon, which is not available from force measurements or vortex circulation calculations. The current method of tracking coherent structures yields insight into the behavior of the coherent structures in both of the diverse flows presented, highlighting the breadth of its potential application.

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

LEA Detection and Tracking Method for Color-Independent Visual-MIMO

PubMed Central

Kim, Jai-Eun; Kim, Ji-Won; Kim, Ki-Doo

2016-01-01

Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement. PMID:27384563

LEA Detection and Tracking Method for Color-Independent Visual-MIMO.

PubMed

Kim, Jai-Eun; Kim, Ji-Won; Kim, Ki-Doo

2016-07-02

Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement.

High-accuracy and real-time 3D positioning, tracking system for medical imaging applications based on 3D digital image correlation

NASA Astrophysics Data System (ADS)

Xue, Yuan; Cheng, Teng; Xu, Xiaohai; Gao, Zeren; Li, Qianqian; Liu, Xiaojing; Wang, Xing; Song, Rui; Ju, Xiangyang; Zhang, Qingchuan

2017-01-01

This paper presents a system for positioning markers and tracking the pose of a rigid object with 6 degrees of freedom in real-time using 3D digital image correlation, with two examples for medical imaging applications. Traditional DIC method was improved to meet the requirements of the real-time by simplifying the computations of integral pixel search. Experiments were carried out and the results indicated that the new method improved the computational efficiency by about 4-10 times in comparison with the traditional DIC method. The system was aimed for orthognathic surgery navigation in order to track the maxilla segment after LeFort I osteotomy. Experiments showed noise for the static point was at the level of 10-3 mm and the measurement accuracy was 0.009 mm. The system was demonstrated on skin surface shape evaluation of a hand for finger stretching exercises, which indicated a great potential on tracking muscle and skin movements.

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Learning to Rapidly Re-Contact the Lost Plume in Chemical Plume Tracing

PubMed Central

Cao, Meng-Li; Meng, Qing-Hao; Wang, Jia-Ying; Luo, Bing; Jing, Ya-Qi; Ma, Shu-Gen

2015-01-01

Maintaining contact between the robot and plume is significant in chemical plume tracing (CPT). In the time immediately following the loss of chemical detection during the process of CPT, Track-Out activities bias the robot heading relative to the upwind direction, expecting to rapidly re-contact the plume. To determine the bias angle used in the Track-Out activity, we propose an online instance-based reinforcement learning method, namely virtual trail following (VTF). In VTF, action-value is generalized from recently stored instances of successful Track-Out activities. We also propose a collaborative VTF (cVTF) method, in which multiple robots store their own instances, and learn from the stored instances, in the same database. The proposed VTF and cVTF methods are compared with biased upwind surge (BUS) method, in which all Track-Out activities utilize an offline optimized universal bias angle, in an indoor environment with three different airflow fields. With respect to our experimental conditions, VTF and cVTF show stronger adaptability to different airflow environments than BUS, and furthermore, cVTF yields higher success rates and time-efficiencies than VTF. PMID:25825974

A novel feature-tracking echocardiographic method for the quantitation of regional myocardial function: validation in an animal model of ischemia-reperfusion.

PubMed

Pirat, Bahar; Khoury, Dirar S; Hartley, Craig J; Tiller, Les; Rao, Liyun; Schulz, Daryl G; Nagueh, Sherif F; Zoghbi, William A

2008-02-12

The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking-incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function.

The Tracking Resonance Frequency Method for Photoacoustic Measurements Based on the Phase Response

NASA Astrophysics Data System (ADS)

Suchenek, Mariusz

2017-04-01

One of the major issues in the use of the resonant photoacoustic cell is the resonance frequency of the cell. The frequency is not stable, and its changes depend mostly on temperature and gas mixture. This paper presents a new method for tracking resonance frequency, where both the amplitude and phase are calculated from the input samples. The stimulating frequency can be adjusted to the resonance frequency of the cell based on the phase. This method was implemented using a digital measurement system with an analog to digital converter, field programmable gate array (FPGA) and a microcontroller. The resonance frequency was changed by the injection of carbon dioxide into the cell. A theoretical description and experimental results are also presented.

Automatic Tracking Algorithm in Coaxial Near-Infrared Laser Ablation Endoscope for Fetus Surgery

NASA Astrophysics Data System (ADS)

Hu, Yan; Yamanaka, Noriaki; Masamune, Ken

2014-07-01

This article reports a stable vessel object tracking method for the treatment of twin-to-twin transfusion syndrome based on our previous 2 DOF endoscope. During the treatment of laser coagulation, it is necessary to focus on the exact position of the target object, however it moves by the mother's respiratory motion and still remains a challenge to obtain and track the position precisely. In this article, an algorithm which uses features from accelerated segment test (FAST) to extract the features and optical flow as the object tracking method, is proposed to deal with above problem. Further, we experimentally simulate the movement due to the mother's respiration, and the results of position errors and similarity verify the effectiveness of the proposed tracking algorithm for laser ablation endoscopy in-vitro and under water considering two influential factors. At average, the errors are about 10 pixels and the similarity over 0.92 are obtained in the experiments.

Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range Sensors

PubMed Central

Girard, Gabriel; Côté, Stéphane; Zlatanova, Sisi; Barette, Yannick; St-Pierre, Johanne; van Oosterom, Peter

2011-01-01

Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians. PMID:22164034

Forensic use of photo response non-uniformity of imaging sensors and a counter method.

PubMed

Dirik, Ahmet Emir; Karaküçük, Ahmet

2014-01-13

Analogous to use of bullet scratches in forensic science, the authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, photo-response non-uniformity noise (PRNU) has been used in source camera identification (SCI). However, this technique can be used maliciously to track or inculpate innocent people. To impede such tracking, PRNU noise should be suppressed significantly. Based on this motivation, we propose a counter forensic method to deceive SCI. Experimental results show that it is possible to impede PRNU-based camera identification for various imaging sensors while preserving the image quality.

3D tracking of laparoscopic instruments using statistical and geometric modeling.

PubMed

Wolf, Rémi; Duchateau, Josselin; Cinquin, Philippe; Voros, Sandrine

2011-01-01

During a laparoscopic surgery, the endoscope can be manipulated by an assistant or a robot. Several teams have worked on the tracking of surgical instruments, based on methods ranging from the development of specific devices to image processing methods. We propose to exploit the instruments' insertion points, which are fixed on the patients abdominal cavity, as a geometric constraint for the localization of the instruments. A simple geometric model of a laparoscopic instrument is described, as well as a parametrization that exploits a spherical geometric grid, which offers attracting homogeneity and isotropy properties. The general architecture of our proposed approach is based on the probabilistic Condensation algorithm.

Registration Combining Wide and Narrow Baseline Feature Tracking Techniques for Markerless AR Systems.

PubMed

Duan, Liya; Guan, Tao; Yang, Bo

2009-01-01

Augmented reality (AR) is a field of computer research which deals with the combination of real world and computer generated data. Registration is one of the most difficult problems currently limiting the usability of AR systems. In this paper, we propose a novel natural feature tracking based registration method for AR applications. The proposed method has following advantages: (1) it is simple and efficient, as no man-made markers are needed for both indoor and outdoor AR applications; moreover, it can work with arbitrary geometric shapes including planar, near planar and non planar structures which really enhance the usability of AR systems. (2) Thanks to the reduced SIFT based augmented optical flow tracker, the virtual scene can still be augmented on the specified areas even under the circumstances of occlusion and large changes in viewpoint during the entire process. (3) It is easy to use, because the adaptive classification tree based matching strategy can give us fast and accurate initialization, even when the initial camera is different from the reference image to a large degree. Experimental evaluations validate the performance of the proposed method for online pose tracking and augmentation.

Concept and simulation study of a novel localization method for robotic endoscopic capsules using multiple positron emission markers

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

Than, Trung Duc, E-mail: dtt581@uowmail.edu.au; Alici, Gursel, E-mail: gursel@uow.edu.au; Zhou, Hao, E-mail: hz467@uowmail.edu.au

2014-07-15

Purpose: Over the last decade, wireless capsule endoscope has been the tool of choice for noninvasive inspection of the gastrointestinal tract, especially in the small intestine. However, the latest clinical products have not been equipped with a sufficiently accurate localization system which makes it difficult to determine the location of intestinal abnormalities, and to apply follow-up interventions such as biopsy or drug delivery. In this paper, the authors present a novel localization method based on tracking three positron emission markers embedded inside an endoscopic capsule. Methods: Three spherical {sup 22}Na markers with diameters of less than 1 mm are embeddedmore » in the cover of the capsule. Gamma ray detectors are arranged around a patient body to detect coincidence gamma rays emitted from the three markers. The position of each marker can then be estimated using the collected data by the authors’ tracking algorithm which consists of four consecutive steps: a method to remove corrupted data, an initialization method, a clustering method based on the Fuzzy C-means clustering algorithm, and a failure prediction method. Results: The tracking algorithm has been implemented inMATLAB utilizing simulation data generated from the Geant4 Application for Emission Tomography toolkit. The results show that this localization method can achieve real-time tracking with an average position error of less than 0.4 mm and an average orientation error of less than 2°. Conclusions: The authors conclude that this study has proven the feasibility and potential of the proposed technique in effectively determining the position and orientation of a robotic endoscopic capsule.« less

Refining the modelling of vehicle-track interaction

NASA Astrophysics Data System (ADS)

Kaiser, Ingo

2012-01-01

An enhanced model of a passenger coach running on a straight track is developed. This model includes wheelsets modelled as rotating flexible bodies, a track consisting of flexible rails supported on discrete sleepers and wheel-rail contact modules, which can describe non-elliptic contact patches based on a boundary element method (BEM). For the scenarios of undisturbed centred running and permanent hunting, the impact of the structural deformations of the wheelsets and the rails on the stress distribution in the wheel-rail contact is investigated.

The Genetic-Algorithm-Based Normal Boundary Intersection (GANBI) Method; An Efficient Approach to Pareto Multiobjective Optimization for Engineering Design

DTIC Science & Technology

2006-05-15

alarm performance in a cost-effective manner is the use of track - before - detect strategies, in which multiple sensor detections must occur within the...corresponding to the traditional sensor coverage problem. Also, in the track - before - detect context, reference is made to the field-level functions of...detection and false alarm as successful search and false search, respectively, because the track - before - detect process serves as a searching function

Instruction-based clinical eye-tracking study on the visual interpretation of divergence: How do students look at vector field plots?

NASA Astrophysics Data System (ADS)

Klein, P.; Viiri, J.; Mozaffari, S.; Dengel, A.; Kuhn, J.

2018-06-01

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux concept. We test the effectiveness of both strategies in an instruction-based eye-tracking study with N =41 physics majors. We found that students' performance improved when both strategies were introduced (74% correct) instead of only one strategy (64% correct), and students performed best when they were free to choose between the two strategies (88% correct). This finding supports the idea of introducing multiple representations of a physical concept to foster student understanding. Relevant eye-tracking measures demonstrate that both strategies imply different visual processing of the vector field plots, therefore reflecting conceptual differences between the strategies. Advanced analysis methods further reveal significant differences in eye movements between the best and worst performing students. For instance, the best students performed predominantly horizontal and vertical saccades, indicating correct interpretation of partial derivatives. They also focused on smaller regions when they balanced positive and negative flux. This mixed-method research leads to new insights into student visual processing of vector field representations, highlights the advantages and limitations of eye-tracking methodologies in this context, and discusses implications for teaching and for future research. The introduction of saccadic direction analysis expands traditional methods, and shows the potential to discover new insights into student understanding and learning difficulties.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Determination of feature generation methods for PTZ camera object tracking

NASA Astrophysics Data System (ADS)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Deterministic object tracking using Gaussian ringlet and directional edge features

NASA Astrophysics Data System (ADS)

Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

2017-10-01

Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression.

PubMed

Cherry, Kevin M; Peplinski, Brandon; Kim, Lauren; Wang, Shijun; Lu, Le; Zhang, Weidong; Liu, Jianfei; Wei, Zhuoshi; Summers, Ronald M

2015-01-01

Given the potential importance of marginal artery localization in automated registration in computed tomography colonography (CTC), we have devised a semi-automated method of marginal vessel detection employing sequential Monte Carlo tracking (also known as particle filtering tracking) by multiple cue fusion based on intensity, vesselness, organ detection, and minimum spanning tree information for poorly enhanced vessel segments. We then employed a random forest algorithm for intelligent cue fusion and decision making which achieved high sensitivity and robustness. After applying a vessel pruning procedure to the tracking results, we achieved statistically significantly improved precision compared to a baseline Hessian detection method (2.7% versus 75.2%, p<0.001). This method also showed statistically significantly improved recall rate compared to a 2-cue baseline method using fewer vessel cues (30.7% versus 67.7%, p<0.001). These results demonstrate that marginal artery localization on CTC is feasible by combining a discriminative classifier (i.e., random forest) with a sequential Monte Carlo tracking mechanism. In so doing, we present the effective application of an anatomical probability map to vessel pruning as well as a supplementary spatial coordinate system for colonic segmentation and registration when this task has been confounded by colon lumen collapse. Published by Elsevier B.V.

Magnetic eye tracking in mice

PubMed Central

Payne, Hannah L

2017-01-01

Eye movements provide insights about a wide range of brain functions, from sensorimotor integration to cognition; hence, the measurement of eye movements is an important tool in neuroscience research. We describe a method, based on magnetic sensing, for measuring eye movements in head-fixed and freely moving mice. A small magnet was surgically implanted on the eye, and changes in the magnet angle as the eye rotated were detected by a magnetic field sensor. Systematic testing demonstrated high resolution measurements of eye position of <0.1°. Magnetic eye tracking offers several advantages over the well-established eye coil and video-oculography methods. Most notably, it provides the first method for reliable, high-resolution measurement of eye movements in freely moving mice, revealing increased eye movements and altered binocular coordination compared to head-fixed mice. Overall, magnetic eye tracking provides a lightweight, inexpensive, easily implemented, and high-resolution method suitable for a wide range of applications. PMID:28872455

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI

PubMed Central

Stawicki, Piotr; Gembler, Felix; Rezeika, Aya; Volosyak, Ivan

2017-01-01

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques. PMID:28379187

FPGA Implementation of the Coupled Filtering Method and the Affine Warping Method.

PubMed

Zhang, Chen; Liang, Tianzhu; Mok, Philip K T; Yu, Weichuan

2017-07-01

In ultrasound image analysis, the speckle tracking methods are widely applied to study the elasticity of body tissue. However, "feature-motion decorrelation" still remains as a challenge for the speckle tracking methods. Recently, a coupled filtering method and an affine warping method were proposed to accurately estimate strain values, when the tissue deformation is large. The major drawback of these methods is the high computational complexity. Even the graphics processing unit (GPU)-based program requires a long time to finish the analysis. In this paper, we propose field-programmable gate array (FPGA)-based implementations of both methods for further acceleration. The capability of FPGAs on handling different image processing components in these methods is discussed. A fast and memory-saving image warping approach is proposed. The algorithms are reformulated to build a highly efficient pipeline on FPGA. The final implementations on a Xilinx Virtex-7 FPGA are at least 13 times faster than the GPU implementation on the NVIDIA graphic card (GeForce GTX 580).

Decentralised consensus-based formation tracking of multiple differential drive robots

NASA Astrophysics Data System (ADS)

Chu, Xing; Peng, Zhaoxia; Wen, Guoguang; Rahmani, Ahmed

2017-11-01

This article investigates the control problem for formation tracking of multiple nonholonomic robots under distributed manner which means each robot only needs local information exchange. A class of general state and input transform is introduced to convert the formation-tracking issue of multi-robot systems into the consensus-like problem with time-varying reference. The distributed observer-based protocol with nonlinear dynamics is developed for each robot to achieve the consensus tracking of the new system, which namely means a group of nonholonomic mobile robots can form the desired formation configuration with its centroid moving along the predefined reference trajectory. The finite-time stability of observer and control law is analysed rigorously by using the Lyapunov direct method, algebraic graph theory and matrix analysis. Numerical examples are finally provided to illustrate the effectiveness of the theory results proposed in this paper.

Distributed cooperative regulation for multiagent systems and its applications to power systems: a survey.

PubMed

Hu, Jianqiang; Li, Yaping; Yong, Taiyou; Cao, Jinde; Yu, Jie; Mao, Wenbo

2014-01-01

Cooperative regulation of multiagent systems has become an active research area in the past decade. This paper reviews some recent progress in distributed coordination control for leader-following multiagent systems and its applications in power system and mainly focuses on the cooperative tracking control in terms of consensus tracking control and containment tracking control. Next, methods on how to rank the network nodes are summarized for undirected/directed network, based on which one can determine which follower should be connected to leaders such that partial followers can perceive leaders' information. Furthermore, we present a survey of the most relevant scientific studies investigating the regulation and optimization problems in power systems based on distributed strategies. Finally, some potential applications in the frequency tracking regulation of smart grids are discussed at the end of the paper.

Distributed Cooperative Regulation for Multiagent Systems and Its Applications to Power Systems: A Survey

PubMed Central

Li, Yaping; Yong, Taiyou; Yu, Jie; Mao, Wenbo

2014-01-01

Cooperative regulation of multiagent systems has become an active research area in the past decade. This paper reviews some recent progress in distributed coordination control for leader-following multiagent systems and its applications in power system and mainly focuses on the cooperative tracking control in terms of consensus tracking control and containment tracking control. Next, methods on how to rank the network nodes are summarized for undirected/directed network, based on which one can determine which follower should be connected to leaders such that partial followers can perceive leaders' information. Furthermore, we present a survey of the most relevant scientific studies investigating the regulation and optimization problems in power systems based on distributed strategies. Finally, some potential applications in the frequency tracking regulation of smart grids are discussed at the end of the paper. PMID:25243199

Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors.

PubMed

Yu, Jinpeng; Shi, Peng; Yu, Haisheng; Chen, Bing; Lin, Chong

2015-07-01

This paper considers the problem of discrete-time adaptive position tracking control for a interior permanent magnet synchronous motor (IPMSM) based on fuzzy-approximation. Fuzzy logic systems are used to approximate the nonlinearities of the discrete-time IPMSM drive system which is derived by direct discretization using Euler method, and a discrete-time fuzzy position tracking controller is designed via backstepping approach. In contrast to existing results, the advantage of the scheme is that the number of the adjustable parameters is reduced to two only and the problem of coupling nonlinearity can be overcome. It is shown that the proposed discrete-time fuzzy controller can guarantee the tracking error converges to a small neighborhood of the origin and all the signals are bounded. Simulation results illustrate the effectiveness and the potentials of the theoretic results obtained.

Video-Based Eye Tracking in Sex Research: A Systematic Literature Review.

PubMed

Wenzlaff, Frederike; Briken, Peer; Dekker, Arne

2015-12-21

Although eye tracking has been used for decades, it has gained popularity in the area of sex research only recently. The aim of this article is to examine the potential merits of eye tracking for this field. We present a systematic review of the current use of video-based eye-tracking technology in this area, evaluate the findings, and identify future research opportunities. A total of 34 relevant studies published between 2006 and 2014 were identified for inclusion by means of online databases and other methods. We grouped them into three main areas of research: body perception and attractiveness, forensic research, and sexual orientation. Despite the methodological and theoretical differences across the studies, eye tracking has been shown to be a promising tool for sex research. The article suggests there is much potential for further studies to employ this technique because it is noninvasive and yet still allows for the assessment of both conscious and unconscious perceptional processes. Furthermore, eye tracking can be implemented in investigations of various theoretical backgrounds, ranging from biology to the social sciences.

Back-tracking of primary particle trajectories for muons detected at the Earth surface

NASA Astrophysics Data System (ADS)

Shutenko, V. V.

2017-01-01

Investigations of cosmic rays on the surface of the Earth allow to derive information of applied character on the conditions of the interplanetary magnetic field and of the geomagnetic field. For this purpose, it is necessary to collate trajectories of particles detected in the ground-based detector to trajectories of primary cosmic rays in the heliosphere. This problem is solved by means of various back-tracking methods. In this work, one of such methods is presented.

Model-based registration of multi-rigid-body for augmented reality

NASA Astrophysics Data System (ADS)

Ikeda, Sei; Hori, Hajime; Imura, Masataka; Manabe, Yoshitsugu; Chihara, Kunihiro

2009-02-01

Geometric registration between a virtual object and the real space is the most basic problem in augmented reality. Model-based tracking methods allow us to estimate three-dimensional (3-D) position and orientation of a real object by using a textured 3-D model instead of visual marker. However, it is difficult to apply existing model-based tracking methods to the objects that have movable parts such as a display of a mobile phone, because these methods suppose a single, rigid-body model. In this research, we propose a novel model-based registration method for multi rigid-body objects. For each frame, the 3-D models of each rigid part of the object are first rendered according to estimated motion and transformation from the previous frame. Second, control points are determined by detecting the edges of the rendered image and sampling pixels on these edges. Motion and transformation are then simultaneously calculated from distances between the edges and the control points. The validity of the proposed method is demonstrated through experiments using synthetic videos.

Fast Track Randomized Controlled Trial to Prevent Externalizing Psychiatric Disorders: Findings from Grades 3 to 9

ERIC Educational Resources Information Center

Journal of the American Academy of Child & Adolescent Psychiatry, 2007

2007-01-01

Objective: This study tests the efficacy of the Fast Track Program in preventing antisocial behavior and psychiatric disorders among groups varying in initial risk. Method: Schools within four sites (Durham, NC; Nashville, TN; Seattle, WA; and rural central Pennsylvania) were selected as high-risk institutions based on neighborhood crime and…

Development of DNA-based Identification methods to track the species composition of fish larvae within nearshore areas of the Great Lakes

EPA Science Inventory

The ability to track the identity and abundance of larval fish, which are ubiquitous during spawning season, may lead to a greater understanding of fish species distributions in Great Lakes nearshore areas including early-detection of invasive fish species before they become esta...

Granular Flow Graph, Adaptive Rule Generation and Tracking.

PubMed

Pal, Sankar Kumar; Chakraborty, Debarati Bhunia

2017-12-01

A new method of adaptive rule generation in granular computing framework is described based on rough rule base and granular flow graph, and applied for video tracking. In the process, several new concepts and operations are introduced, and methodologies formulated with superior performance. The flow graph enables in defining an intelligent technique for rule base adaptation where its characteristics in mapping the relevance of attributes and rules in decision-making system are exploited. Two new features, namely, expected flow graph and mutual dependency between flow graphs are defined to make the flow graph applicable in the tasks of both training and validation. All these techniques are performed in neighborhood granular level. A way of forming spatio-temporal 3-D granules of arbitrary shape and size is introduced. The rough flow graph-based adaptive granular rule-based system, thus produced for unsupervised video tracking, is capable of handling the uncertainties and incompleteness in frames, able to overcome the incompleteness in information that arises without initial manual interactions and in providing superior performance and gaining in computation time. The cases of partial overlapping and detecting the unpredictable changes are handled efficiently. It is shown that the neighborhood granulation provides a balanced tradeoff between speed and accuracy as compared to pixel level computation. The quantitative indices used for evaluating the performance of tracking do not require any information on ground truth as in the other methods. Superiority of the algorithm to nonadaptive and other recent ones is demonstrated extensively.

Energy dependent track structure parametrisations for protons and carbon ions based on nanometric simulations

NASA Astrophysics Data System (ADS)

Alexander, Frauke; Villagrasa, Carmen; Rabus, Hans; Wilkens, Jan J.

2015-09-01

The BioQuaRT project within the European Metrology Research Programme aims at correlating ion track structure characteristics with the biological effects of radiation and develops measurement and simulation techniques for determining ion track structure on different length scales from about 2 nm to about 10 μm. Within this framework, we investigate methods to translate track-structure quantities derived on a nanometre scale to macroscopic dimensions. Input data sets were generated by simulations of ion tracks of protons and carbon ions in liquid water using the Geant 4 Monte Carlo toolkit with the Geant4-DNA processes. Based on the energy transfer points - recorded with nanometre resolution - we investigated parametrisations of overall properties of ion track structure. Three different track structure parametrisations have been developed using the distances to the 10 next neighbouring ionisations, the radial energy distribution and ionisation cluster size distributions. These parametrisations of nanometric track structure build a basis for deriving biologically relevant mean values which are essential in the clinical situation where each voxel is exposed to a mixed radiation field. Contribution to the Topical Issue "COST Action Nano-IBCT: Nano-scale Processes Behind Ion-Beam Cancer Therapy", edited by Andrey Solov'yov, Nigel Mason, Gustavo García, Eugene Surdutovich.

Fusion-based multi-target tracking and localization for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

An UAV scheduling and planning method for post-disaster survey

NASA Astrophysics Data System (ADS)

Li, G. Q.; Zhou, X. G.; Yin, J.; Xiao, Q. Y.

2014-11-01

Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs' the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

NASA Astrophysics Data System (ADS)

Zachiu, C.; Ries, M.; Ramaekers, P.; Guey, J.-L.; Moonen, C. T. W.; de Senneville, B. Denis

2017-10-01

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ˜1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions.

PubMed

Zachiu, C; Ries, M; Ramaekers, P; Guey, J-L; Moonen, C T W; de Senneville, B Denis

2017-10-04

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.

PubMed

Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa

2015-12-01

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.

Adaptive control of space-based robot manipulators

NASA Technical Reports Server (NTRS)

Walker, Michael W.; Wee, Liang-Boon

1991-01-01

A control method is presented that achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. The 15-DOF system dynamics are divided into two components: a 9-DOF invertible portion and 6-DOF noninvertible portion. A controller is then designed to achieve trajectory tracking of the invertible portion of the system, which consists of the manipulator-joint positions and the orientation of the base. The motion of the noninvertible portion is bounded but otherwise unspecified. This portion of the system consists of the position of the robot's base and the position of the reaction wheels. A simulation is presented to demonstrate the effectiveness of the controller. A quadratic polynomial is used to generate the desired trajectory to illustrate the trajectory-tracking capability of the controller.

Decentralized cooperative TOA/AOA target tracking for hierarchical wireless sensor networks.

PubMed

Chen, Ying-Chih; Wen, Chih-Yu

2012-11-08

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processing is conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for the localization task. The proposed energy-efficient tracking algorithm allows each sub-cluster member to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for object position estimation.

Non-Static error tracking control for near space airship loading platform

NASA Astrophysics Data System (ADS)

Ni, Ming; Tao, Fei; Yang, Jiandong

2018-01-01

A control scheme based on internal model with non-static error is presented against the uncertainty of the near space airship loading platform system. The uncertainty in the tracking table is represented as interval variations in stability and control derivatives. By formulating the tracking problem of the uncertainty system as a robust state feedback stabilization problem of an augmented system, sufficient condition for the existence of robust tracking controller is derived in the form of linear matrix inequality (LMI). Finally, simulation results show that the new method not only has better anti-jamming performance, but also improves the dynamic performance of the high-order systems.

The performance of the ZEUS central tracking detector z-by-timing electronics in a transputer based data acquisition system

NASA Astrophysics Data System (ADS)

Foster, B.; Heath, G. P.; Llewellyn, T. J.; Gingrich, D. M.; Harnew, N.; Hallam-Baker, P. M.; Khatri, T.; McArthur, I. C.; Morawitz, P.; Nash, J.; Shield, P. D.; Topp-Jorgensen, S.; Wilson, F. F.; Allen, D. B.; Carter, R. C.; Jeffs, M. D.; Morrissey, M. C.; Quinton, S. P. H.; Lane, J. B.; Postranecky, M.

1993-05-01

The Central Tracking Detector of the ZEUS experiment employs a time difference technique to measure the z coordinate of each hit. The method provides fast, three-dimensional space point measurements which are used as input to all levels of the ZEUS trigger. Such a tracking trigger is essential in order to discriminate against events with vertices lying outside the nominal electron-proton interaction region. Since the beam crossing interval of the HERA collider is 96 ns, all data must be pipelined through the front-end readout electronics. Subsequent data aquisition employs a novel technique which utilizes a network of approximately 120 INMOS transputers to process the data in parallel. The z-by-timing method and its data aquisition have been employed successfully in recording and reconstructing tracks from electron-proton interactions in ZEUS.

Audio Tracking in Noisy Environments by Acoustic Map and Spectral Signature.

PubMed

Crocco, Marco; Martelli, Samuele; Trucco, Andrea; Zunino, Andrea; Murino, Vittorio

2018-05-01

A novel method is proposed for generic target tracking by audio measurements from a microphone array. To cope with noisy environments characterized by persistent and high energy interfering sources, a classification map (CM) based on spectral signatures is calculated by means of a machine learning algorithm. Next, the CM is combined with the acoustic map, describing the spatial distribution of sound energy, in order to obtain a cleaned joint map in which contributions from the disturbing sources are removed. A likelihood function is derived from this map and fed to a particle filter yielding the target location estimation on the acoustic image. The method is tested on two real environments, addressing both speaker and vehicle tracking. The comparison with a couple of trackers, relying on the acoustic map only, shows a sharp improvement in performance, paving the way to the application of audio tracking in real challenging environments.

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

Panfil, J; Patel, R; Surucu, M

Purpose: To compare markerless template-based tracking of lung tumors using dual energy (DE) cone-beam computed tomography (CBCT) projections versus single energy (SE) CBCT projections. Methods: A RANDO chest phantom with a simulated tumor in the upper right lung was used to investigate the effectiveness of tumor tracking using DE and SE CBCT projections. Planar kV projections from CBCT acquisitions were captured at 60 kVp (4 mAs) and 120 kVp (1 mAs) using the Varian TrueBeam and non-commercial iTools Capture software. Projections were taken at approximately every 0.53° while the gantry rotated. Due to limitations of the phantom, angles for whichmore » the shoulders blocked the tumor were excluded from tracking analysis. DE images were constructed using a weighted logarithmic subtraction that removed bony anatomy while preserving soft tissue structures. The tumors were tracked separately on DE and SE (120 kVp) images using a template-based tracking algorithm. The tracking results were compared to ground truth coordinates designated by a physician. Matches with a distance of greater than 3 mm from ground truth were designated as failing to track. Results: 363 frames were analyzed. The algorithm successfully tracked the tumor on 89.8% (326/363) of DE frames compared to 54.3% (197/363) of SE frames (p<0.0001). Average distance between tracking and ground truth coordinates was 1.27 +/− 0.67 mm for DE versus 1.83+/−0.74 mm for SE (p<0.0001). Conclusion: This study demonstrates the effectiveness of markerless template-based tracking using DE CBCT. DE imaging resulted in better detectability with more accurate localization on average versus SE. Supported by a grant from Varian Medical Systems.« less

LIDAR-based characterization and conservation of the first theropod dinosaur trackways from Arkansas, USA.

PubMed

Platt, Brian F; Suarez, Celina A; Boss, Stephen K; Williamson, Malcolm; Cothren, Jackson; Kvamme, Jo Ann C

2018-01-01

LIDAR-based analyses of the first theropod dinosaur trackways known from the state of Arkansas, USA are reported. The trackways were found on a limestone bedding plane in the Albian De Queen Formation in an active gypsum quarry. Because limited access precluded thorough field study, fieldwork focused on preserving the entire site digitally with ground-based LIDAR, and detailed measurements were later taken digitally from point cloud data. The site contains eight tridactyl trackways associated with sauropod trackways and numerous isolated tracks. Although there appear to be two different tridactyl morphotypes, we show that the tracks are all likely from a single species of trackmaker. We apply a simple method of estimating substrate consistency by comparing the differences between true track dimensions and apparent track dimensions. The tridactyl tracks at the southern end of the site are preserved with significantly greater differences in true vs. apparent dimensions and are shallower than the rest of the tridactyl tracks at the site, which we interpret as the result of outward expansion of the soft tissues of the foot upon contact with a firm substrate. We interpret the firm substrate as having high bulk density and high shear strength, which also explain associated manus-only sauropod tracks. We show that the tridactyl tracks are likely from theropod trackmakers and that footprint lengths, trackway paces, stride lengths, and pace angulations of the De Queen trackways are statistically indistinguishable from equivalent measurements of theropod trackways in the Glen Rose Formation. The Glen Rose tracks are attributed to the large-bodied theropod, Acrocanthosaurus and we likewise attribute the De Queen tracks to Acrocanthosaurus, which is known from skeletal remains in temporally equivalent units and from the mine itself.

EVALUATION OF HOST SPECIFIC PCR-BASED METHODS FOR THE IDENTIFICATION OF FECAL POLLUTION

EPA Science Inventory

Microbial Source Tracking (MST) is an approach to determine the origin of fecal pollution impacting a body of water. MST is based on the assumption that, given the appropriate method and indicator, the source of microbial pollution can be identified. One of the key elements of...

Neutron Radiography of Fluid Flow for Geothermal Energy Research

NASA Astrophysics Data System (ADS)

Bingham, P.; Polsky, Y.; Anovitz, L.; Carmichael, J.; Bilheux, H.; Jacobsen, D.; Hussey, D.

Enhanced geothermal systems seek to expand the potential for geothermal energy by engineering heat exchange systems within the earth. A neutron radiography imaging method has been developed for the study of fluid flow through rock under environmental conditions found in enhanced geothermal energy systems. For this method, a pressure vessel suitable for neutron radiography was designed and fabricated, modifications to imaging instrument setups were tested, multiple contrast agents were tested, and algorithms developed for tracking of flow. The method has shown success for tracking of single phase flow through a manufactured crack in a 3.81 cm (1.5 inch) diameter core within a pressure vessel capable of confinement up to 69 MPa (10,000 psi) using a particle tracking approach with bubbles of fluorocarbon-based fluid as the ;particles; and imaging with 10 ms exposures.

Indirect learning control for nonlinear dynamical systems

NASA Technical Reports Server (NTRS)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Comparison of two hardware-based hit filtering methods for trackers in high-pileup environments

NASA Astrophysics Data System (ADS)

Gradin, J.; Mårtensson, M.; Brenner, R.

2018-04-01

As experiments in high energy physics aim to measure increasingly rare processes, the experiments continually strive to increase the expected signal yields. In the case of the High Luminosity upgrade of the LHC, the luminosity is raised by increasing the number of simultaneous proton-proton interactions, so-called pile-up. This increases the expected yields of signal and background processes alike. The signal is embedded in a large background of processes that mimic that of signal events. It is therefore imperative for the experiments to develop new triggering methods to effectively distinguish the interesting events from the background. We present a comparison of two methods for filtering detector hits to be used for triggering on particle tracks: one based on a pattern matching technique using Associative Memory (AM) chips and the other based on the Hough transform. Their efficiency and hit rejection are evaluated for proton-proton collisions with varying amounts of pile-up using a simulation of a generic silicon tracking detector. It is found that, while both methods are feasible options for a track trigger with single muon efficiencies around 98–99%, the AM based pattern matching produces a lower number of hit combinations with respect to the Hough transform whilst keeping more of the true signal hits. We also present the effect on the two methods of increasing the amount of support material in the detector and of introducing inefficiencies by deactivating detector modules. The increased support material has negligable effects on the efficiency for both methods, while dropping 5% (10%) of the available modules decreases the efficiency to about 95% (87%) for both methods, irrespective of the amount of pile-up.

Ocean Heat Content Reveals Secrets of Fish Migrations

PubMed Central

Luo, Jiangang; Ault, Jerald S.; Shay, Lynn K.; Hoolihan, John P.; Prince, Eric D.; Brown, Craig A.; Rooker, Jay R.

2015-01-01

For centuries, the mechanisms surrounding spatially complex animal migrations have intrigued scientists and the public. We present a new methodology using ocean heat content (OHC), a habitat metric that is normally a fundamental part of hurricane intensity forecasting, to estimate movements and migration of satellite-tagged marine fishes. Previous satellite-tagging research of fishes using archival depth, temperature and light data for geolocations have been too coarse to resolve detailed ocean habitat utilization. We combined tag data with OHC estimated from ocean circulation and transport models in an optimization framework that substantially improved geolocation accuracy over SST-based tracks. The OHC-based movement track provided the first quantitative evidence that many of the tagged highly migratory fishes displayed affinities for ocean fronts and eddies. The OHC method provides a new quantitative tool for studying dynamic use of ocean habitats, migration processes and responses to environmental changes by fishes, and further, improves ocean animal tracking and extends satellite-based animal tracking data for other potential physical, ecological, and fisheries applications. PMID:26484541

Quantifying the tracking capability of space-based AIS systems

NASA Astrophysics Data System (ADS)

Skauen, Andreas Nordmo

2016-01-01

The Norwegian Defence Research Establishment (FFI) has operated three Automatic Identification System (AIS) receivers in space. Two are on dedicated nano-satellites, AISSat-1 and AISSat-2. The third, the NORAIS Receiver, was installed on the International Space Station. A general method for calculating the upper bound on the tracking capability of a space-based AIS system has been developed and the results from the algorithm applied to AISSat-1 and the NORAIS Receiver individually. In addition, a constellation of AISSat-1 and AISSat-2 is presented. The tracking capability is defined as the probability of re-detecting ships as they move around the globe and is explained to represent and upper bound on a space-based AIS system performance. AISSat-1 and AISSat-2 operates on the nominal AIS1 and AIS2 channels, while the NORAIS Receiver data used are from operations on the dedicated space AIS channels, AIS3 and AIS4. The improved tracking capability of operations on the space AIS channels is presented.

Fault-tolerant optimised tracking control for unknown discrete-time linear systems using a combined reinforcement learning and residual compensation methodology

NASA Astrophysics Data System (ADS)

Han, Ke-Zhen; Feng, Jian; Cui, Xiaohong

2017-10-01

This paper considers the fault-tolerant optimised tracking control (FTOTC) problem for unknown discrete-time linear system. A research scheme is proposed on the basis of data-based parity space identification, reinforcement learning and residual compensation techniques. The main characteristic of this research scheme lies in the parity-space-identification-based simultaneous tracking control and residual compensation. The specific technical line consists of four main contents: apply subspace aided method to design observer-based residual generator; use reinforcement Q-learning approach to solve optimised tracking control policy; rely on robust H∞ theory to achieve noise attenuation; adopt fault estimation triggered by residual generator to perform fault compensation. To clarify the design and implementation procedures, an integrated algorithm is further constructed to link up these four functional units. The detailed analysis and proof are subsequently given to explain the guaranteed FTOTC performance of the proposed conclusions. Finally, a case simulation is provided to verify its effectiveness.

Handheld pose tracking using vision-inertial sensors with occlusion handling

NASA Astrophysics Data System (ADS)

Li, Juan; Slembrouck, Maarten; Deboeverie, Francis; Bernardos, Ana M.; Besada, Juan A.; Veelaert, Peter; Aghajan, Hamid; Casar, José R.; Philips, Wilfried

2016-07-01

Tracking of a handheld device's three-dimensional (3-D) position and orientation is fundamental to various application domains, including augmented reality (AR), virtual reality, and interaction in smart spaces. Existing systems still offer limited performance in terms of accuracy, robustness, computational cost, and ease of deployment. We present a low-cost, accurate, and robust system for handheld pose tracking using fused vision and inertial data. The integration of measurements from embedded accelerometers reduces the number of unknown parameters in the six-degree-of-freedom pose calculation. The proposed system requires two light-emitting diode (LED) markers to be attached to the device, which are tracked by external cameras through a robust algorithm against illumination changes. Three data fusion methods have been proposed, including the triangulation-based stereo-vision system, constraint-based stereo-vision system with occlusion handling, and triangulation-based multivision system. Real-time demonstrations of the proposed system applied to AR and 3-D gaming are also included. The accuracy assessment of the proposed system is carried out by comparing with the data generated by the state-of-the-art commercial motion tracking system OptiTrack. Experimental results show that the proposed system has achieved high accuracy of few centimeters in position estimation and few degrees in orientation estimation.

Geometric calibration of a coordinate measuring machine using a laser tracking system

NASA Astrophysics Data System (ADS)

Umetsu, Kenta; Furutnani, Ryosyu; Osawa, Sonko; Takatsuji, Toshiyuki; Kurosawa, Tomizo

2005-12-01

This paper proposes a calibration method for a coordinate measuring machine (CMM) using a laser tracking system. The laser tracking system can measure three-dimensional coordinates based on the principle of trilateration with high accuracy and is easy to set up. The accuracy of length measurement of a single laser tracking interferometer (laser tracker) is about 0.3 µm over a length of 600 mm. In this study, we first measured 3D coordinates using the laser tracking system. Secondly, 21 geometric errors, namely, parametric errors of the CMM, were estimated by the comparison of the coordinates obtained by the laser tracking system and those obtained by the CMM. As a result, the estimated parametric errors agreed with those estimated by a ball plate measurement, which demonstrates the validity of the proposed calibration system.

An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

2008-01-01

This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

Analytical and experimental study of sleeper SAT S 312 in slab track Sateba system

NASA Astrophysics Data System (ADS)

Guigou-Carter, C.; Villot, M.; Guillerme, B.; Petit, C.

2006-06-01

In this paper, a simple prediction tool based on a two-dimensional model is developed for a slab track system composed of two rails with rail pads, sleepers with sleeper pads, and a concrete base slab. The track and the slab are considered as infinite beams with bending stiffness, loss factor and mass per unit length. The track system is represented by its impedance per unit length of track and the ground by its line input impedance calculated using a two-dimensional elastic half-space ground model based on the wave approach. Damping of each track component is modelled as hysteretic damping and is taken into account by using a complex stiffness. The unsprung mass of the vehicle is considered as a concentrated mass at the excitation point on the rail head. The effect of the dynamic stiffness of the sleeper pads on the vibration isolation is studied in detail, the vibration isolation provided by the track system being quantified by an insertion gain in dB per one-third octave band. The second part of this paper presents an experimental test rig used to measure the dynamic stiffness of the sleeper pads on a full width section of the track (two rails). The experimental set-up is submitted to vertical as well as horizontal static loads (via hydraulic jacks) and an electrodynamic shaker is used for dynamic excitation of the system. The determination of the dynamic stiffness of the sleeper pads is based on the approach called the "direct method". The limitations of the experimental set-up are discussed. The measurement results for one type of sleeper pad are presented.

Design and Modeling of a Test Bench for Dual-Motor Electric Drive Tracked Vehicles Based on a Dynamic Load Emulation Method.

PubMed

Wang, Zhe; Lv, Haoliang; Zhou, Xiaojun; Chen, Zhaomeng; Yang, Yong

2018-06-21

Dual-motor Electric Drive Tracked Vehicles (DDTVs) have attracted increasing attention due to their high transmission efficiency and economical fuel consumption. A test bench for the development and validation of new DDTV technologies is necessary and urgent. How to load the vehicle on a DDTV test bench exactly the same as on a real road is a crucial issue when designing the bench. This paper proposes a novel dynamic load emulation method to address this problem. The method adopts dual dynamometers to simulate both the road load and the inertia load that are imposed on the dual independent drive systems. The vehicle’s total inertia equivalent to the drive wheels is calculated with separate consideration of vehicle body, tracks and road wheels to obtain a more accurate inertia load. A speed tracking control strategy with feedforward compensation is implemented to control the dual dynamometers, so as to make the real-time dynamic load emulation possible. Additionally, a MATLAB/Simulink model of the test bench is built based on a dynamics analysis of the platform. Experiments are finally carried out on this test bench under different test conditions. The outcomes show that the proposed load emulation method is effective, and has good robustness and adaptability to complex driving conditions. Besides, the accuracy of the established test bench model is also demonstrated by comparing the results obtained from the simulation model and experiments.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

PubMed

Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

2017-08-30

Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

Measuring and tracking eye movements of a behaving archer fish by real-time stereo vision.

PubMed

Ben-Simon, Avi; Ben-Shahar, Ohad; Segev, Ronen

2009-11-15

The archer fish (Toxotes chatareus) exhibits unique visual behavior in that it is able to aim at and shoot down with a squirt of water insects resting on the foliage above water level and then feed on them. This extreme behavior requires excellent visual acuity, learning, and tight synchronization between the visual system and body motion. This behavior also raises many important questions, such as the fish's ability to compensate for air-water refraction and the neural mechanisms underlying target acquisition. While many such questions remain open, significant insights towards solving them can be obtained by tracking the eye and body movements of freely behaving fish. Unfortunately, existing tracking methods suffer from either a high level of invasiveness or low resolution. Here, we present a video-based eye tracking method for accurately and remotely measuring the eye and body movements of a freely moving behaving fish. Based on a stereo vision system and a unique triangulation method that corrects for air-glass-water refraction, we are able to measure a full three-dimensional pose of the fish eye and body with high temporal and spatial resolution. Our method, being generic, can be applied to studying the behavior of marine animals in general. We demonstrate how data collected by our method may be used to show that the hunting behavior of the archer fish is composed of surfacing concomitant with rotating the body around the direction of the fish's fixed gaze towards the target, until the snout reaches in the correct shooting position at water level.

Quantifying the statistical importance of utilizing regression over classic energy intensity calculations for tracking efficiency improvements in industry

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

Nimbalkar, Sachin U.; Wenning, Thomas J.; Guo, Wei

In the United States, manufacturing facilities account for about 32% of total domestic energy consumption in 2014. Robust energy tracking methodologies are critical to understanding energy performance in manufacturing facilities. Due to its simplicity and intuitiveness, the classic energy intensity method (i.e. the ratio of total energy use over total production) is the most widely adopted. However, the classic energy intensity method does not take into account the variation of other relevant parameters (i.e. product type, feed stock type, weather, etc.). Furthermore, the energy intensity method assumes that the facilities’ base energy consumption (energy use at zero production) is zero,more » which rarely holds true. Therefore, it is commonly recommended to utilize regression models rather than the energy intensity approach for tracking improvements at the facility level. Unfortunately, many energy managers have difficulties understanding why regression models are statistically better than utilizing the classic energy intensity method. While anecdotes and qualitative information may convince some, many have major reservations about the accuracy of regression models and whether it is worth the time and effort to gather data and build quality regression models. This paper will explain why regression models are theoretically and quantitatively more accurate for tracking energy performance improvements. Based on the analysis of data from 114 manufacturing plants over 12 years, this paper will present quantitative results on the importance of utilizing regression models over the energy intensity methodology. This paper will also document scenarios where regression models do not have significant relevance over the energy intensity method.« less

Quantitative Identification of the Annealing Degree of Apatite Fission Tracks Using Terahertz Time Domain Spectroscopy (THz-TDS).

PubMed

Wu, Hang; Wu, Shixiang; Qiu, Nansheng; Chang, Jian; Bao, Rima; Zhang, Xin; Liu, Nian; Liu, Shuai

2018-01-01

Apatite fission-track (AFT) analysis, a widely used low-temperature thermochronology method, can provide details of the hydrocarbon generation history of source rocks for use in hydrocarbon exploration. The AFT method is based on the annealing behavior of fission tracks generated by 238 U fission in apatite particles during geological history. Due to the cumbersome experimental steps and high expense, it is imperative to find an efficient and inexpensive technique to determinate the annealing degree of AFT. In this study, on the basis of the ellipsoid configuration of tracks, the track volume fraction model (TVFM) is established and the fission-track volume index is proposed. Furthermore, terahertz time domain spectroscopy (THz-TDS) is used for the first time to identify the variation of the AFT annealing degree of Durango apatite particles heated at 20, 275, 300, 325, 450, and 500 ℃ for 10 h. The THz absorbance of the sample increases with the degree of annealing. In addition, the THz absorption index is exponentially related to annealing temperature and can be used to characterize the fission-track volume index. Terahertz time domain spectroscopy can be an ancillary technique for AFT thermochronological research. More work is urgently needed to extrapolate experimental data to geological conditions.

Maximum power point tracking algorithm based on sliding mode and fuzzy logic for photovoltaic sources under variable environmental conditions

NASA Astrophysics Data System (ADS)

Atik, L.; Petit, P.; Sawicki, J. P.; Ternifi, Z. T.; Bachir, G.; Della, M.; Aillerie, M.

2017-02-01

Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on the environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, they have to operate at their MPP despite the inevitable changes in the environment. Various methods for maximum power point tracking (MPPT) were developed and finally implemented in solar power electronic controllers to increase the efficiency in the electricity production originate from renewables. In this paper we compare using Matlab tools Simulink, two different MPP tracking methods, which are, fuzzy logic control (FL) and sliding mode control (SMC), considering their efficiency in solar energy production.

Three-dimensional particle tracking via tunable color-encoded multiplexing.

PubMed

Duocastella, Martí; Theriault, Christian; Arnold, Craig B

2016-03-01

We present a novel 3D tracking approach capable of locating single particles with nanometric precision over wide axial ranges. Our method uses a fast acousto-optic liquid lens implemented in a bright field microscope to multiplex light based on color into different and selectable focal planes. By separating the red, green, and blue channels from an image captured with a color camera, information from up to three focal planes can be retrieved. Multiplane information from the particle diffraction rings enables precisely locating and tracking individual objects up to an axial range about 5 times larger than conventional single-plane approaches. We apply our method to the 3D visualization of the well-known coffee-stain phenomenon in evaporating water droplets.

Simultaneous tracking and regulation visual servoing of wheeled mobile robots with uncalibrated extrinsic parameters

NASA Astrophysics Data System (ADS)

Lu, Qun; Yu, Li; Zhang, Dan; Zhang, Xuebo

2018-01-01

This paper presentsa global adaptive controller that simultaneously solves tracking and regulation for wheeled mobile robots with unknown depth and uncalibrated camera-to-robot extrinsic parameters. The rotational angle and the scaled translation between the current camera frame and the reference camera frame, as well as the ones between the desired camera frame and the reference camera frame can be calculated in real time by using the pose estimation techniques. A transformed system is first obtained, for which an adaptive controller is then designed to accomplish both tracking and regulation tasks, and the controller synthesis is based on Lyapunov's direct method. Finally, the effectiveness of the proposed method is illustrated by a simulation study.

Random vibration analysis of train-bridge under track irregularities and traveling seismic waves using train-slab track-bridge interaction model

NASA Astrophysics Data System (ADS)

Zeng, Zhi-Ping; Zhao, Yan-Gang; Xu, Wen-Tao; Yu, Zhi-Wu; Chen, Ling-Kun; Lou, Ping

2015-04-01

The frequent use of bridges in high-speed railway lines greatly increases the probability that trains are running on bridges when earthquakes occur. This paper investigates the random vibrations of a high-speed train traversing a slab track on a continuous girder bridge subjected to track irregularities and traveling seismic waves by the pseudo-excitation method (PEM). To derive the equations of motion of the train-slab track-bridge interaction system, the multibody dynamics and finite element method models are used for the train and the track and bridge, respectively. By assuming track irregularities to be fully coherent random excitations with time lags between different wheels and seismic accelerations to be uniformly modulated, non-stationary random excitations with time lags between different foundations, the random load vectors of the equations of motion are transformed into a series of deterministic pseudo-excitations based on PEM and the wheel-rail contact relationship. A computer code is developed to obtain the time-dependent random responses of the entire system. As a case study, the random vibration characteristics of an ICE-3 high-speed train traversing a seven-span continuous girder bridge simultaneously excited by track irregularities and traveling seismic waves are analyzed. The influence of train speed and seismic wave propagation velocity on the random vibration characteristics of the bridge and train are discussed.

Quantitative microbial faecal source tracking with sampling guided by hydrological catchment dynamics.

PubMed

Reischer, G H; Haider, J M; Sommer, R; Stadler, H; Keiblinger, K M; Hornek, R; Zerobin, W; Mach, R L; Farnleitner, A H

2008-10-01

The impairment of water quality by faecal pollution is a global public health concern. Microbial source tracking methods help to identify faecal sources but the few recent quantitative microbial source tracking applications disregarded catchment hydrology and pollution dynamics. This quantitative microbial source tracking study, conducted in a large karstic spring catchment potentially influenced by humans and ruminant animals, was based on a tiered sampling approach: a 31-month water quality monitoring (Monitoring) covering seasonal hydrological dynamics and an investigation of flood events (Events) as periods of the strongest pollution. The detection of a ruminant-specific and a human-specific faecal Bacteroidetes marker by quantitative real-time PCR was complemented by standard microbiological and on-line hydrological parameters. Both quantitative microbial source tracking markers were detected in spring water during Monitoring and Events, with preponderance of the ruminant-specific marker. Applying multiparametric analysis of all data allowed linking the ruminant-specific marker to general faecal pollution indicators, especially during Events. Up to 80% of the variation of faecal indicator levels during Events could be explained by ruminant-specific marker levels proving the dominance of ruminant faecal sources in the catchment. Furthermore, soil was ruled out as a source of quantitative microbial source tracking markers. This study demonstrates the applicability of quantitative microbial source tracking methods and highlights the prerequisite of considering hydrological catchment dynamics in source tracking study design.

Modelling of Rail Vehicles and Track for Calculation of Ground-Vibration Transmission Into Buildings

NASA Astrophysics Data System (ADS)

Hunt, H. E. M.

1996-05-01

A methodology for the calculation of vibration transmission from railways into buildings is presented. The method permits existing models of railway vehicles and track to be incorporated and it has application to any model of vibration transmission through the ground. Special attention is paid to the relative phasing between adjacent axle-force inputs to the rail, so that vibration transmission may be calculated as a random process. The vehicle-track model is used in conjunction with a building model of infinite length. The tracking and building are infinite and parallel to each other and forces applied are statistically stationary in space so that vibration levels at any two points along the building are the same. The methodology is two-dimensional for the purpose of application of random process theory, but fully three-dimensional for calculation of vibration transmission from the track and through the ground into the foundations of the building. The computational efficiency of the method will interest engineers faced with the task of reducing vibration levels in buildings. It is possible to assess the relative merits of using rail pads, under-sleeper pads, ballast mats, floating-slab track or base isolation for particular applications.

A Computer Assisted Method to Track Listening Strategies in Second Language Learning

ERIC Educational Resources Information Center

Roussel, Stephanie

2011-01-01

Many studies about listening strategies are based on what learners report while listening to an oral message in the second language (Vandergrift, 2003; Graham, 2006). By recording a video of the computer screen while L2 learners (L1 French) were listening to an MP3-track in German, this study uses a novel approach and recent developments in…

Maneuver Algorithm for Bearings-Only Target Tracking with Acceleration and Field of View Constraints

NASA Astrophysics Data System (ADS)

Roh, Heekun; Shim, Sang-Wook; Tahk, Min-Jea

2018-05-01

This paper proposes a maneuver algorithm for the agent performing target tracking with bearing angle information only. The goal of the agent is to estimate the target position and velocity based only on the bearing angle data. The methods of bearings-only target state estimation are outlined. The nature of bearings-only target tracking problem is then addressed. Based on the insight from above-mentioned properties, the maneuver algorithm for the agent is suggested. The proposed algorithm is composed of a nonlinear, hysteresis guidance law and the estimation accuracy assessment criteria based on the theory of Cramer-Rao bound. The proposed guidance law generates lateral acceleration command based on current field of view angle. The accuracy criteria supply the expected estimation variance, which acts as a terminal criterion for the proposed algorithm. The aforementioned algorithm is verified with a two-dimensional simulation.

Visual Tracking Based on Extreme Learning Machine and Sparse Representation

PubMed Central

Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

2015-01-01

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359

Getting Inside the Expert's Head: An Analysis of Physician Cognitive Processes During Trauma Resuscitations.

PubMed

White, Matthew R; Braund, Heather; Howes, Daniel; Egan, Rylan; Gegenfurtner, Andreas; van Merrienboer, Jeroen J G; Szulewski, Adam

2018-04-23

Crisis resource management skills are integral to leading the resuscitation of a critically ill patient. Despite their importance, crisis resource management skills (and their associated cognitive processes) have traditionally been difficult to study in the real world. The objective of this study was to derive key cognitive processes underpinning expert performance in resuscitation medicine, using a new eye-tracking-based video capture method during clinical cases. During an 18-month period, a sample of 10 trauma resuscitations led by 4 expert trauma team leaders was analyzed. The physician team leaders were outfitted with mobile eye-tracking glasses for each case. After each resuscitation, participants were debriefed with a modified cognitive task analysis, based on a cued-recall protocol, augmented by viewing their own first-person perspective eye-tracking video from the clinical encounter. Eye-tracking technology was successfully applied as a tool to aid in the qualitative analysis of expert performance in a clinical setting. All participants stated that using these methods helped uncover previously unconscious aspects of their cognition. Overall, 5 major themes were derived from the interviews: logistic awareness, managing uncertainty, visual fixation behaviors, selective attendance to information, and anticipatory behaviors. The novel approach of cognitive task analysis augmented by eye tracking allowed the derivation of 5 unique cognitive processes underpinning expert performance in leading a resuscitation. An understanding of these cognitive processes has the potential to enhance educational methods and to create new assessment modalities of these previously tacit aspects of expertise in this field. Copyright © 2018 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

A novel active disturbance rejection based tracking design for laser system with quadrant photodetector

NASA Astrophysics Data System (ADS)

Manojlović, Stojadin M.; Barbarić, Žarko P.; Mitrović, Srđan T.

2015-06-01

A new tracking design for laser systems with different arrangements of a quadrant photodetector, based on the principle of active disturbance rejection control is suggested. The detailed models of quadrant photodetector with standard add-subtract, difference-over-sum and diagonal-difference-over-sum algorithms for displacement signals are included in the control loop. Target moving, non-linearity of a photodetector, parameter perturbations and exterior disturbances are treated as a total disturbance. Active disturbance rejection controllers with linear extended state observers for total disturbance estimation and rejection are designed. Proposed methods are analysed in frequency domain to quantify their stability characteristics and disturbance rejection performances. It is shown through simulations, that tracking errors are effectively compensated, providing the laser spot positioning in the area near the centre of quadrant photodetector where the mentioned algorithms have the highest sensitivity, which provides tracking of the manoeuvring targets with high accuracy.

A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery†

PubMed Central

Burgner, J.; Simpson, A. L.; Fitzpatrick, J. M.; Lathrop, R. A.; Herrell, S. D.; Miga, M. I.; Webster, R. J.

2013-01-01

Background Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper. Methods We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney. Results Experiments agree with model predictions, producing point RMS errors consistently < 1 mm, surface-based registration with mean closest point error < 1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney. Conclusions Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery. PMID:22761086

Rigid shape matching by segmentation averaging.

PubMed

Wang, Hongzhi; Oliensis, John

2010-04-01

We use segmentations to match images by shape. The new matching technique does not require point-to-point edge correspondence and is robust to small shape variations and spatial shifts. To address the unreliability of segmentations computed bottom-up, we give a closed form approximation to an average over all segmentations. Our method has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. For smoothing, instead of smoothing images based on local structures, we smooth based on the global optimal image structures. Our methods for segmentation, smoothing, and object detection perform competitively, and we also show promising results in shape-based tracking.

Correlation between external and internal respiratory motion: a validation study.

PubMed

Ernst, Floris; Bruder, Ralf; Schlaefer, Alexander; Schweikard, Achim

2012-05-01

In motion-compensated image-guided radiotherapy, accurate tracking of the target region is required. This tracking process includes building a correlation model between external surrogate motion and the motion of the target region. A novel correlation method is presented and compared with the commonly used polynomial model. The CyberKnife system (Accuray, Inc., Sunnyvale/CA) uses a polynomial correlation model to relate externally measured surrogate data (optical fibres on the patient's chest emitting red light) to infrequently acquired internal measurements (X-ray data). A new correlation algorithm based on ɛ -Support Vector Regression (SVR) was developed. Validation and comparison testing were done with human volunteers using live 3D ultrasound and externally measured infrared light-emitting diodes (IR LEDs). Seven data sets (5:03-6:27 min long) were recorded from six volunteers. Polynomial correlation algorithms were compared to the SVR-based algorithm demonstrating an average increase in root mean square (RMS) accuracy of 21.3% (0.4 mm). For three signals, the increase was more than 29% and for one signal as much as 45.6% (corresponding to more than 1.5 mm RMS). Further analysis showed the improvement to be statistically significant. The new SVR-based correlation method outperforms traditional polynomial correlation methods for motion tracking. This method is suitable for clinical implementation and may improve the overall accuracy of targeted radiotherapy.

Beam tracking phase tomography with laboratory sources

NASA Astrophysics Data System (ADS)

Vittoria, F. A.; Endrizzi, M.; Kallon, G. K. N.; Hagen, C. K.; Diemoz, P. C.; Zamir, A.; Olivo, A.

2018-04-01

An X-ray phase-contrast laboratory system is presented, based on the beam-tracking method. Beam-tracking relies on creating micro-beamlets of radiation by placing a structured mask before the sample, and analysing them by using a detector with sufficient resolution. The system is used in tomographic configuration to measure the three dimensional distribution of the linear attenuation coefficient, difference from unity of the real part of the refractive index, and of the local scattering power of specimens. The complementarity of the three signals is investigated, together with their potential use for material discrimination.

A Robust Head Tracking System Based on Monocular Vision and Planar Templates

PubMed Central

Caballero, Fernando; Maza, Iván; Molina, Roberto; Esteban, David; Ollero, Aníbal

2009-01-01

This paper details the implementation of a head tracking system suitable for its use in teleoperation stations or control centers, taking into account the limitations and constraints usually associated to those environments. The paper discusses and justifies the selection of the different methods and sensors to build the head tracking system, detailing also the processing steps of the system in operation. A prototype to validate the proposed approach is also presented along with several tests in a real environment with promising results. PMID:22291546

Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zheng-Lu; Bahm, Cathy

2001-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

The Identification and Tracking of Uterine Contractions Using Template Based Cross-Correlation.

PubMed

McDonald, Sarah C; Brooker, Graham; Phipps, Hala; Hyett, Jon

2017-09-01

The purpose of this paper is to outline a novel method of using template based cross-correlation to identify and track uterine contractions during labour. A purpose built six-channel Electromyography (EMG) device was used to collect data from consenting women during labour and birth. A range of templates were constructed for the purpose of identifying and tracking uterine activity when cross-correlated with the EMG signal. Peak finding techniques were applied on the cross-correlated result to simplify and automate the identification and tracking of contractions. The EMG data showed a unique pattern when a woman was contracting with key features of the contraction signal remaining consistent and identifiable across subjects. Contraction profiles across subjects were automatically identified using template based cross-correlation. Synthetic templates from a rectangular function with a duration of between 5 and 10 s performed best at identifying and tracking uterine activity across subjects. The successful application of this technique provides opportunity for both simple and accurate real-time analysis of contraction data while enabling investigations into the application of techniques such as machine learning which could enable automated learning from contraction data as part of real-time monitoring and post analysis.

White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.

PubMed

Dellani, Paulo R; Glaser, Martin; Wille, Paulo R; Vucurevic, Goran; Stadie, Axel; Bauermann, Thomas; Tropine, Andrei; Perneczky, Axel; von Wangenheim, Aldo; Stoeter, Peter

2007-03-01

Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation.

Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion

PubMed Central

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system. PMID:24693243

Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

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

Lee, B; Georgia Institute of Technology, Atlanta, GA; Wang, C

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities.more » These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell survival curves for high-LET radiation.« less

TH-A-19A-04: Latent Uncertainties and Performance of a GPU-Implemented Pre-Calculated Track Monte Carlo Method

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

Renaud, M; Seuntjens, J; Roberge, D

Purpose: Assessing the performance and uncertainty of a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport running on graphics processing units (GPU). While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from recycling a limited number of tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pre-generated track bank size can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pre-generated for electrons and protons using EGSnrc and GEANT4, respectively. The PMC algorithm for track transport was implementedmore » on the CUDA programming framework. GPU-PMC dose distributions were compared to benchmark dose distributions simulated using general-purpose MC codes in the same conditions. A latent uncertainty analysis was performed by comparing GPUPMC dose values to a “ground truth” benchmark while varying the track bank size and primary particle histories. Results: GPU-PMC dose distributions and benchmark doses were within 1% of each other in voxels with dose greater than 50% of Dmax. In proton calculations, a submillimeter distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty followed a Poisson distribution with the number of tracks per energy (TPE) and a track bank of 20,000 TPE produced a latent uncertainty of approximately 1%. Efficiency analysis showed a 937× and 508× gain over a single processor core running DOSXYZnrc for 16 MeV electrons in water and bone, respectively. Conclusion: The GPU-PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty below 1%. The track bank size necessary to achieve an optimal efficiency can be tuned based on the desired uncertainty. Coupled with a model to calculate dose contributions from uncharged particles, GPU-PMC is a candidate for inverse planning of modulated electron radiotherapy and scanned proton beams. This work was supported in part by FRSQ-MSSS (Grant No. 22090), NSERC RG (Grant No. 432290) and CIHR MOP (Grant No. MOP-211360)« less

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

Semi-active control of tracked vehicle suspension incorporating magnetorheological dampers

NASA Astrophysics Data System (ADS)

Ata, W. G.; Salem, A. M.

2017-05-01

In past years, the application of magnetorheological (MR) and electrorheological dampers in vehicle suspension has been widely studied, mainly for the purpose of vibration control. This paper presents theoretical study to identify an appropriate semi-active control method for MR-tracked vehicle suspension. Three representative control algorithms are simulated including the skyhook, hybrid and fuzzy-hybrid controllers. A seven degrees-of-freedom tracked vehicle suspension model incorporating MR dampers has been adopted for comparison between the performance of the three controllers. The model differential equations are derived based on Newton's second law of motion and the proposed control methods are developed. The performance of each control method under bump and sinusoidal road profiles for different vehicle speeds is simulated and compared with the performance of the conventional suspension system in time and frequency domains. The results show that the performance of tracked vehicle suspension with MR dampers is substantially improved. Moreover, the fuzzy-hybrid controller offers an excellent integrated performance in reducing the body accelerations as well as wheel bounce responses compared with the classical skyhook and hybrid controllers.

A Novel Feature-Tracking Echocardiographic Method for the Quantitation of Regional Myocardial Function

PubMed Central

Pirat, Bahar; Khoury, Dirar S.; Hartley, Craig J.; Tiller, Les; Rao, Liyun; Schulz, Daryl G.; Nagueh, Sherif F.; Zoghbi, William A.

2012-01-01

Objectives The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. Background A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking—incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Methods Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Results Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Conclusions Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function. PMID:18261685

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

MobileFusion: real-time volumetric surface reconstruction and dense tracking on mobile phones.

PubMed

Ondrúška, Peter; Kohli, Pushmeet; Izadi, Shahram

2015-11-01

We present the first pipeline for real-time volumetric surface reconstruction and dense 6DoF camera tracking running purely on standard, off-the-shelf mobile phones. Using only the embedded RGB camera, our system allows users to scan objects of varying shape, size, and appearance in seconds, with real-time feedback during the capture process. Unlike existing state of the art methods, which produce only point-based 3D models on the phone, or require cloud-based processing, our hybrid GPU/CPU pipeline is unique in that it creates a connected 3D surface model directly on the device at 25Hz. In each frame, we perform dense 6DoF tracking, which continuously registers the RGB input to the incrementally built 3D model, minimizing a noise aware photoconsistency error metric. This is followed by efficient key-frame selection, and dense per-frame stereo matching. These depth maps are fused volumetrically using a method akin to KinectFusion, producing compelling surface models. For each frame, the implicit surface is extracted for live user feedback and pose estimation. We demonstrate scans of a variety of objects, and compare to a Kinect-based baseline, showing on average ∼ 1.5cm error. We qualitatively compare to a state of the art point-based mobile phone method, demonstrating an order of magnitude faster scanning times, and fully connected surface models.

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

NASA Astrophysics Data System (ADS)

Abratenko, P.; Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Huang, E.-C.; James, C.; de Vries, J. Jan; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Kalousis, L. N.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2017-10-01

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks.

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

DOE PAGES

Abratenko, P.

2017-10-18

Here, we discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation,more » we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks.« less

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

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

Abratenko, P.

Here, we discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation,more » we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks.« less

Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Using Eye Trackers for Usability Evaluation of Health Information Technology: A Systematic Literature Review

PubMed Central

Yang, Yushi

2015-01-01

Background Eye-tracking technology has been used to measure human cognitive processes and has the potential to improve the usability of health information technology (HIT). However, it is still unclear how the eye-tracking method can be integrated with other traditional usability methodologies to achieve its full potential. Objective The objective of this study was to report on HIT evaluation studies that have used eye-tracker technology, and to envision the potential use of eye-tracking technology in future research. Methods We used four reference databases to initially identify 5248 related papers, which resulted in only 9 articles that met our inclusion criteria. Results Eye-tracking technology was useful in finding usability problems in many ways, but is still in its infancy for HIT usability evaluation. Limited types of HITs have been evaluated by eye trackers, and there has been a lack of evaluation research in natural settings. Conclusions More research should be done in natural settings to discover the real contextual-based usability problems of clinical and mobile HITs using eye-tracking technology with more standardized methodologies and guidance. PMID:27026079

Beyond Group: Multiple Person Tracking via Minimal Topology-Energy-Variation.

PubMed

Gao, Shan; Ye, Qixiang; Xing, Junliang; Kuijper, Arjan; Han, Zhenjun; Jiao, Jianbin; Ji, Xiangyang

2017-12-01

Tracking multiple persons is a challenging task when persons move in groups and occlude each other. Existing group-based methods have extensively investigated how to make group division more accurately in a tracking-by-detection framework; however, few of them quantify the group dynamics from the perspective of targets' spatial topology or consider the group in a dynamic view. Inspired by the sociological properties of pedestrians, we propose a novel socio-topology model with a topology-energy function to factor the group dynamics of moving persons and groups. In this model, minimizing the topology-energy-variance in a two-level energy form is expected to produce smooth topology transitions, stable group tracking, and accurate target association. To search for the strong minimum in energy variation, we design the discrete group-tracklet jump moves embedded in the gradient descent method, which ensures that the moves reduce the energy variation of group and trajectory alternately in the varying topology dimension. Experimental results on both RGB and RGB-D data sets show the superiority of our proposed model for multiple person tracking in crowd scenes.

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

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

Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures andmore » ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.« less

Electronic patient registration and tracking at mass vaccination clinics: a clinical study.

PubMed

Billittier, Anthony J; Lupiani, Patrick; Masterson, Gary; Masterson, Tim; Zak, Christopher

2003-01-01

To protect the citizens of the United States from the use of dangerous biological agents, the Center for Disease Control and Prevention (CDC) has been actively preparing to deal with the consequences of such an attack. Their plans include the deployment of mass immunization clinics to handle postevent vaccinations. As part of the planning efforts by the Western New York Public Health Alliance, a Web-based electronic patient registration and tracking system was developed and tested at a recent trial smallpox vaccination clinic. Initial goals were to determine what the pitfalls and benefits of using such a system might be in comparison to other methods of data collection. This exercise proved that use of an electronic system capable of scanning two-dimensional bar codes was superior to both paper-based and optical character recognition (OCR) methods of data collection and management. Major improvements in speed and/or accuracy were evident in all areas of the clinic, especially in patient registration, vaccine tracking and postclinic data analysis.

A Radiation Chemistry Code Based on the Green's Function of the Diffusion Equation

NASA Technical Reports Server (NTRS)

Plante, Ianik; Wu, Honglu

2014-01-01

Stochastic radiation track structure codes are of great interest for space radiation studies and hadron therapy in medicine. These codes are used for a many purposes, notably for microdosimetry and DNA damage studies. In the last two decades, they were also used with the Independent Reaction Times (IRT) method in the simulation of chemical reactions, to calculate the yield of various radiolytic species produced during the radiolysis of water and in chemical dosimeters. Recently, we have developed a Green's function based code to simulate reversible chemical reactions with an intermediate state, which yielded results in excellent agreement with those obtained by using the IRT method. This code was also used to simulate and the interaction of particles with membrane receptors. We are in the process of including this program for use with the Monte-Carlo track structure code Relativistic Ion Tracks (RITRACKS). This recent addition should greatly expand the capabilities of RITRACKS, notably to simulate DNA damage by both the direct and indirect effect.

Automatic PSO-Based Deformable Structures Markerless Tracking in Laparoscopic Cholecystectomy

NASA Astrophysics Data System (ADS)

Djaghloul, Haroun; Batouche, Mohammed; Jessel, Jean-Pierre

An automatic and markerless tracking method of deformable structures (digestive organs) during laparoscopic cholecystectomy intervention that uses the (PSO) behavour and the preoperative a priori knowledge is presented. The associated shape to the global best particles of the population determines a coarse representation of the targeted organ (the gallbladder) in monocular laparoscopic colored images. The swarm behavour is directed by a new fitness function to be optimized to improve the detection and tracking performance. The function is defined by a linear combination of two terms, namely, the human a priori knowledge term (H) and the particle's density term (D). Under the limits of standard (PSO) characteristics, experimental results on both synthetic and real data show the effectiveness and robustness of our method. Indeed, it outperforms existing methods without need of explicit initialization (such as active contours, deformable models and Gradient Vector Flow) on accuracy and convergence rate.

Visual tracking based on the sparse representation of the PCA subspace

NASA Astrophysics Data System (ADS)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

Classification between Failed Nodes and Left Nodes in Mobile Asset Tracking Systems †

PubMed Central

Kim, Kwangsoo; Jin, Jae-Yeon; Jin, Seong-il

2016-01-01

Medical asset tracking systems track a medical device with a mobile node and determine its status as either in or out, because it can leave a monitoring area. Due to a failed node, this system may decide that a mobile asset is outside the area, even though it is within the area. In this paper, an efficient classification method is proposed to separate mobile nodes disconnected from a wireless sensor network between nodes with faults and a node that actually has left the monitoring region. The proposed scheme uses two trends extracted from the neighboring nodes of a disconnected mobile node. First is the trend in a series of the neighbor counts; the second is that of the ratios of the boundary nodes included in the neighbors. Based on such trends, the proposed method separates failed nodes from mobile nodes that are disconnected from a wireless sensor network without failures. The proposed method is evaluated using both real data generated from a medical asset tracking system and also using simulations with the network simulator (ns-2). The experimental results show that the proposed method correctly differentiates between failed nodes and nodes that are no longer in the monitoring region, including the cases that the conventional methods fail to detect. PMID:26901200

Research on the Filtering Algorithm in Speed and Position Detection of Maglev Trains

PubMed Central

Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

2011-01-01

This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train’s structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally. PMID:22164012

Research on the filtering algorithm in speed and position detection of maglev trains.

PubMed

Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

2011-01-01

This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train's structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

Nested Tracking Graphs

DOE PAGES

Lukasczyk, Jonas; Weber, Gunther; Maciejewski, Ross; ...

2017-06-01

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to eachmore » other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We show the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.« less

Correlation and 3D-tracking of objects by pointing sensors

DOEpatents

Griesmeyer, J. Michael

2017-04-04

A method and system for tracking at least one object using a plurality of pointing sensors and a tracking system are disclosed herein. In a general embodiment, the tracking system is configured to receive a series of observation data relative to the at least one object over a time base for each of the plurality of pointing sensors. The observation data may include sensor position data, pointing vector data and observation error data. The tracking system may further determine a triangulation point using a magnitude of a shortest line connecting a line of sight value from each of the series of observation data from each of the plurality of sensors to the at least one object, and perform correlation processing on the observation data and triangulation point to determine if at least two of the plurality of sensors are tracking the same object. Observation data may also be branched, associated and pruned using new incoming observation data.

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

Borot de Battisti, Maxence, E-mail: M.E.P.Borot@um

Purpose: The development of MR-guided high dose rate (HDR) brachytherapy is under investigation due to the excellent tumor and organs at risk visualization of MRI. However, MR-based localization of needles (including catheters or tubes) has inherently a low update rate and the required image interpretation can be hampered by signal voids arising from blood vessels or calcifications limiting the precision of the needle guidance and reconstruction. In this paper, a new needle tracking prototype is investigated using fiber Bragg gratings (FBG)-based sensing: this prototype involves a MR-compatible stylet composed of three optic fibers with nine sets of embedded FBG sensorsmore » each. This stylet can be inserted into brachytherapy needles and allows a fast measurement of the needle deflection. This study aims to assess the potential of FBG-based sensing for real-time needle (including catheter or tube) tracking during MR-guided intervention. Methods: First, the MR compatibility of FBG-based sensing and its accuracy was evaluated. Different known needle deflections were measured using FBG-based sensing during simultaneous MR-imaging. Then, a needle tracking procedure using FBG-based sensing was proposed. This procedure involved a MR-based calibration of the FBG-based system performed prior to the interventional procedure. The needle tracking system was assessed in an experiment with a moving phantom during MR imaging. The FBG-based system was quantified by comparing the gold-standard shapes, the shape manually segmented on MRI and the FBG-based measurements. Results: The evaluation of the MR compatibility of FBG-based sensing and its accuracy shows that the needle deflection could be measured with an accuracy of 0.27 mm on average. Besides, the FBG-based measurements were comparable to the uncertainty of MR-based measurements estimated at half the voxel size in the MR image. Finally, the mean(standard deviation) Euclidean distance between MR- and FBG-based needle position measurements was equal to 0.79 mm(0.37 mm). The update rate and latency of the FBG-based needle position measurement were 100 and 300 ms, respectively. Conclusions: The FBG-based needle tracking procedure proposed in this paper is able to determine the position of the complete needle, under MR-imaging, with better accuracy and precision, higher update rate, and lower latency compared to current MR-based needle localization methods. This system would be eligible for MR-guided brachytherapy, in particular, for an improved needle guidance and reconstruction.« less

Towards 3D ultrasound image based soft tissue tracking: a transrectal ultrasound prostate image alignment system.

PubMed

Baumann, Michael; Mozer, Pierre; Daanen, Vincent; Troccaz, Jocelyne

2007-01-01

The emergence of real-time 3D ultrasound (US) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. We propose a 3D transrectal US based tracking system for precise prostate biopsy sample localisation. The aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. Since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. We propose a fast and robust multi-resolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. Global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. The method was tested on 237 prostate volumes acquired from 14 different patients for 3D to 3D and 3D to orthogonal 2D slices registration. The 3D-3D version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). The 3D to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max).

Characterization of a gamma-ray tracking array: A comparison of GRETINA and Gammasphere using a 60 Co source

DOE PAGES

Lauritsen, T.; Korichi, A.; Zhu, S.; ...

2016-08-21

In this paper, we provide a formalism for the characterization of tracking arrays with emphasis on the proper corrections required to extract their photopeak efficiencies and peak-to-total ratios. The methods are first applied to Gammasphere, a well characterized 4π array based on the principle of Compton suppression, and subsequently to GRETINA. In addition, the tracking efficiencies are then discussed and some guidelines as to what clustering angle to use in the tracking algorithm are presented. It was possible, using GEANT4 simulations, to scale the measured efficiencies up to the expected values for the full 4π implementation of GRETA.

Characterization of a gamma-ray tracking array: A comparison of GRETINA and Gammasphere using a 60 Co source

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

Lauritsen, T.; Korichi, A.; Zhu, S.

2016-11-01

In this paper, we provide a formalism for the characterization of the tracking arrays with emphasis on the proper corrections required to extract their photopeak efficiencies and peak-to-total ratios. The methods are first applied to Gammasphere, a well characterized 4pi array based on the principle of Compton suppression, and subsequently to GRETINA. The tracking efficiencies are then discussed and some guidelines as to what clustering angle to use in the tracking algorithm are presented. It was possible, using GEANT4 simulations, to scale the measured efficiencies up to the expected values for the full 4pi implementation of GRETA.

Gaussian mixture model based identification of arterial wall movement for computation of distension waveform.

PubMed

Patil, Ravindra B; Krishnamoorthy, P; Sethuraman, Shriram

2015-01-01

This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.

Three-dimensional particle tracking velocimetry using dynamic vision sensors

NASA Astrophysics Data System (ADS)

Borer, D.; Delbruck, T.; Rösgen, T.

2017-12-01

A fast-flow visualization method is presented based on tracking neutrally buoyant soap bubbles with a set of neuromorphic cameras. The "dynamic vision sensors" register only the changes in brightness with very low latency, capturing fast processes at a low data rate. The data consist of a stream of asynchronous events, each encoding the corresponding pixel position, the time instant of the event and the sign of the change in logarithmic intensity. The work uses three such synchronized cameras to perform 3D particle tracking in a medium sized wind tunnel. The data analysis relies on Kalman filters to associate the asynchronous events with individual tracers and to reconstruct the three-dimensional path and velocity based on calibrated sensor information.

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

Robust online tracking via adaptive samples selection with saliency detection

NASA Astrophysics Data System (ADS)

Yan, Jia; Chen, Xi; Zhu, QiuPing

2013-12-01

Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

A novel non-uniform control vector parameterization approach with time grid refinement for flight level tracking optimal control problems.

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao; Xiao, Long; Wang, Yalin; Yang, Chunhua; Gui, Weihua

2018-02-01

High quality control method is essential for the implementation of aircraft autopilot system. An optimal control problem model considering the safe aerodynamic envelop is therefore established to improve the control quality of aircraft flight level tracking. A novel non-uniform control vector parameterization (CVP) method with time grid refinement is then proposed for solving the optimal control problem. By introducing the Hilbert-Huang transform (HHT) analysis, an efficient time grid refinement approach is presented and an adaptive time grid is automatically obtained. With this refinement, the proposed method needs fewer optimization parameters to achieve better control quality when compared with uniform refinement CVP method, whereas the computational cost is lower. Two well-known flight level altitude tracking problems and one minimum time cost problem are tested as illustrations and the uniform refinement control vector parameterization method is adopted as the comparative base. Numerical results show that the proposed method achieves better performances in terms of optimization accuracy and computation cost; meanwhile, the control quality is efficiently improved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Reconfigurable Flight Control Designs With Application to the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zhenglu

1999-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the right body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

Evaluation of Grid Modification Methods for On- and Off-Track Sonic Boom Analysis

NASA Technical Reports Server (NTRS)

Nayani, Sudheer N.; Campbell, Richard L.

2013-01-01

Grid modification methods have been under development at NASA to enable better predictions of low boom pressure signatures from supersonic aircraft. As part of this effort, two new codes, Stretched and Sheared Grid - Modified (SSG) and Boom Grid (BG), have been developed in the past year. The CFD results from these codes have been compared with ones from the earlier grid modification codes Stretched and Sheared Grid (SSGRID) and Mach Cone Aligned Prism (MCAP) and also with the available experimental results. NASA's unstructured grid suite of software TetrUSS and the automatic sourcing code AUTOSRC were used for base grid generation and flow solutions. The BG method has been evaluated on three wind tunnel models. Pressure signatures have been obtained up to two body lengths below a Gulfstream aircraft wind tunnel model. Good agreement with the wind tunnel results have been obtained for both on-track and off-track (up to 53 degrees) cases. On-track pressure signatures up to ten body lengths below a Straight Line Segmented Leading Edge (SLSLE) wind tunnel model have been extracted. Good agreement with the wind tunnel results have been obtained. Pressure signatures have been obtained at 1.5 body lengths below a Lockheed Martin aircraft wind tunnel model. Good agreement with the wind tunnel results have been obtained for both on-track and off-track (up to 40 degrees) cases. Grid sensitivity studies have been carried out to investigate any grid size related issues. Methods have been evaluated for fully turbulent, mixed laminar/turbulent and fully laminar flow conditions.

First Steps Toward Ultrasound-Based Motion Compensation for Imaging and Therapy: Calibration with an Optical System and 4D PET Imaging

PubMed Central

Schwaab, Julia; Kurz, Christopher; Sarti, Cristina; Bongers, André; Schoenahl, Frédéric; Bert, Christoph; Debus, Jürgen; Parodi, Katia; Jenne, Jürgen Walter

2015-01-01

Target motion, particularly in the abdomen, due to respiration or patient movement is still a challenge in many diagnostic and therapeutic processes. Hence, methods to detect and compensate this motion are required. Diagnostic ultrasound (US) represents a non-invasive and dose-free alternative to fluoroscopy, providing more information about internal target motion than respiration belt or optical tracking. The goal of this project is to develop an US-based motion tracking for real-time motion correction in radiation therapy and diagnostic imaging, notably in 4D positron emission tomography (PET). In this work, a workflow is established to enable the transformation of US tracking data to the coordinates of the treatment delivery or imaging system – even if the US probe is moving due to respiration. It is shown that the US tracking signal is equally adequate for 4D PET image reconstruction as the clinically used respiration belt and provides additional opportunities in this concern. Furthermore, it is demonstrated that the US probe being within the PET field of view generally has no relevant influence on the image quality. The accuracy and precision of all the steps in the calibration workflow for US tracking-based 4D PET imaging are found to be in an acceptable range for clinical implementation. Eventually, we show in vitro that an US-based motion tracking in absolute room coordinates with a moving US transducer is feasible. PMID:26649277

Accuracy analysis for triangulation and tracking based on time-multiplexed structured light.

PubMed

Wagner, Benjamin; Stüber, Patrick; Wissel, Tobias; Bruder, Ralf; Schweikard, Achim; Ernst, Floris

2014-08-01

The authors' research group is currently developing a new optical head tracking system for intracranial radiosurgery. This tracking system utilizes infrared laser light to measure features of the soft tissue on the patient's forehead. These features are intended to offer highly accurate registration with respect to the rigid skull structure by means of compensating for the soft tissue. In this context, the system also has to be able to quickly generate accurate reconstructions of the skin surface. For this purpose, the authors have developed a laser scanning device which uses time-multiplexed structured light to triangulate surface points. The accuracy of the authors' laser scanning device is analyzed and compared for different triangulation methods. These methods are given by the Linear-Eigen method and a nonlinear least squares method. Since Microsoft's Kinect camera represents an alternative for fast surface reconstruction, the authors' results are also compared to the triangulation accuracy of the Kinect device. Moreover, the authors' laser scanning device was used for tracking of a rigid object to determine how this process is influenced by the remaining triangulation errors. For this experiment, the scanning device was mounted to the end-effector of a robot to be able to calculate a ground truth for the tracking. The analysis of the triangulation accuracy of the authors' laser scanning device revealed a root mean square (RMS) error of 0.16 mm. In comparison, the analysis of the triangulation accuracy of the Kinect device revealed a RMS error of 0.89 mm. It turned out that the remaining triangulation errors only cause small inaccuracies for the tracking of a rigid object. Here, the tracking accuracy was given by a RMS translational error of 0.33 mm and a RMS rotational error of 0.12°. This paper shows that time-multiplexed structured light can be used to generate highly accurate reconstructions of surfaces. Furthermore, the reconstructed point sets can be used for high-accuracy tracking of objects, meeting the strict requirements of intracranial radiosurgery.

Laser vision seam tracking system based on image processing and continuous convolution operator tracker

NASA Astrophysics Data System (ADS)

Zou, Yanbiao; Chen, Tao

2018-06-01

To address the problem of low welding precision caused by the poor real-time tracking performance of common welding robots, a novel seam tracking system with excellent real-time tracking performance and high accuracy is designed based on the morphological image processing method and continuous convolution operator tracker (CCOT) object tracking algorithm. The system consists of a six-axis welding robot, a line laser sensor, and an industrial computer. This work also studies the measurement principle involved in the designed system. Through the CCOT algorithm, the weld feature points are determined in real time from the noise image during the welding process, and the 3D coordinate values of these points are obtained according to the measurement principle to control the movement of the robot and the torch in real time. Experimental results show that the sensor has a frequency of 50 Hz. The welding torch runs smoothly with a strong arc light and splash interference. Tracking error can reach ±0.2 mm, and the minimal distance between the laser stripe and the welding molten pool can reach 15 mm, which can significantly fulfill actual welding requirements.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

PubMed Central

Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-01-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area. PMID:29082079

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

PubMed

Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-10-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Fast calibration of electromagnetically tracked oblique-viewing rigid endoscopes.

PubMed

Liu, Xinyang; Rice, Christina E; Shekhar, Raj

2017-10-01

The oblique-viewing (i.e., angled) rigid endoscope is a commonly used tool in conventional endoscopic surgeries. The relative rotation between its two moveable parts, the telescope and the camera head, creates a rotation offset between the actual and the projection of an object in the camera image. A calibration method tailored to compensate such offset is needed. We developed a fast calibration method for oblique-viewing rigid endoscopes suitable for clinical use. In contrast to prior approaches based on optical tracking, we used electromagnetic (EM) tracking as the external tracking hardware to improve compactness and practicality. Two EM sensors were mounted on the telescope and the camera head, respectively, with considerations to minimize EM tracking errors. Single-image calibration was incorporated into the method, and a sterilizable plate, laser-marked with the calibration pattern, was also developed. Furthermore, we proposed a general algorithm to estimate the rotation center in the camera image. Formulas for updating the camera matrix in terms of clockwise and counterclockwise rotations were also developed. The proposed calibration method was validated using a conventional [Formula: see text], 5-mm laparoscope. Freehand calibrations were performed using the proposed method, and the calibration time averaged 2 min and 8 s. The calibration accuracy was evaluated in a simulated clinical setting with several surgical tools present in the magnetic field of EM tracking. The root-mean-square re-projection error averaged 4.9 pixel (range 2.4-8.5 pixel, with image resolution of [Formula: see text] for rotation angles ranged from [Formula: see text] to [Formula: see text]. We developed a method for fast and accurate calibration of oblique-viewing rigid endoscopes. The method was also designed to be performed in the operating room and will therefore support clinical translation of many emerging endoscopic computer-assisted surgical systems.

Automated Identification of the Heart Wall Throughout the Entire Cardiac Cycle Using Optimal Cardiac Phase for Extracted Features

NASA Astrophysics Data System (ADS)

Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

2011-07-01

In most methods for evaluation of cardiac function based on echocardiography, the heart wall is currently identified manually by an operator. However, this task is very time-consuming and suffers from inter- and intraobserver variability. The present paper proposes a method that uses multiple features of ultrasonic echo signals for automated identification of the heart wall region throughout an entire cardiac cycle. In addition, the optimal cardiac phase to select a frame of interest, i.e., the frame for the initiation of tracking, was determined. The heart wall region at the frame of interest in this cardiac phase was identified by the expectation-maximization (EM) algorithm, and heart wall regions in the following frames were identified by tracking each point classified in the initial frame as the heart wall region using the phased tracking method. The results for two subjects indicate the feasibility of the proposed method in the longitudinal axis view of the heart.

Distributed multi-sensor particle filter for bearings-only tracking

NASA Astrophysics Data System (ADS)

Zhang, Jungen; Ji, Hongbing

2012-02-01

In this article, the classical bearings-only tracking (BOT) problem for a single target is addressed, which belongs to the general class of non-linear filtering problems. Due to the fact that the radial distance observability of the target is poor, the algorithm-based sequential Monte-Carlo (particle filtering, PF) methods generally show instability and filter divergence. A new stable distributed multi-sensor PF method is proposed for BOT. The sensors process their measurements at their sites using a hierarchical PF approach, which transforms the BOT problem from Cartesian coordinate to the logarithmic polar coordinate and separates the observable components from the unobservable components of the target. In the fusion centre, the target state can be estimated by utilising the multi-sensor optimal information fusion rule. Furthermore, the computation of a theoretical Cramer-Rao lower bound is given for the multi-sensor BOT problem. Simulation results illustrate that the proposed tracking method can provide better performances than the traditional PF method.

Visual Target Tracking in the Presence of Unknown Observer Motion

NASA Technical Reports Server (NTRS)

Williams, Stephen; Lu, Thomas

2009-01-01

Much attention has been given to the visual tracking problem due to its obvious uses in military surveillance. However, visual tracking is complicated by the presence of motion of the observer in addition to the target motion, especially when the image changes caused by the observer motion are large compared to those caused by the target motion. Techniques for estimating the motion of the observer based on image registration techniques and Kalman filtering are presented and simulated. With the effects of the observer motion removed, an additional phase is implemented to track individual targets. This tracking method is demonstrated on an image stream from a buoy-mounted or periscope-mounted camera, where large inter-frame displacements are present due to the wave action on the camera. This system has been shown to be effective at tracking and predicting the global position of a planar vehicle (boat) being observed from a single, out-of-plane camera. Finally, the tracking system has been extended to a multi-target scenario.

Opinions in Federated Search: University of Lugano at TREC 2014 Federated Web Search Track

DTIC Science & Technology

2014-11-01

Opinions in Federated Search : University of Lugano at TREC 2014 Federated Web Search Track Anastasia Giachanou 1 , Ilya Markov 2 and Fabio Crestani 1...ranking based on sentiment using the retrieval-interpolated diversification method. Keywords: federated search , resource selection, vertical selection...performance. Federated search , also known as Distributed Information Retrieval (DIR), o↵ers the means of simultaneously searching multiple information

The research on the mean shift algorithm for target tracking

NASA Astrophysics Data System (ADS)

CAO, Honghong

2017-06-01

The traditional mean shift algorithm for target tracking is effective and high real-time, but there still are some shortcomings. The traditional mean shift algorithm is easy to fall into local optimum in the tracking process, the effectiveness of the method is weak when the object is moving fast. And the size of the tracking window never changes, the method will fail when the size of the moving object changes, as a result, we come up with a new method. We use particle swarm optimization algorithm to optimize the mean shift algorithm for target tracking, Meanwhile, SIFT (scale-invariant feature transform) and affine transformation make the size of tracking window adaptive. At last, we evaluate the method by comparing experiments. Experimental result indicates that the proposed method can effectively track the object and the size of the tracking window changes.

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots.

PubMed

Lee, Tae-Jae; Yi, Dong-Hoon; Cho, Dong-Il Dan

2016-03-01

This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%.

Infrared small target enhancement: grey level mapping based on improved sigmoid transformation and saliency histogram

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian

2018-06-01

Infrared (IR) small target enhancement plays a significant role in modern infrared search and track (IRST) systems and is the basic technique of target detection and tracking. In this paper, a coarse-to-fine grey level mapping method using improved sigmoid transformation and saliency histogram is designed to enhance IR small targets under different backgrounds. For the stage of rough enhancement, the intensity histogram is modified via an improved sigmoid function so as to narrow the regular intensity range of background as much as possible. For the part of further enhancement, a linear transformation is accomplished based on a saliency histogram constructed by averaging the cumulative saliency values provided by a saliency map. Compared with other typical methods, the presented method can achieve both better visual performances and quantitative evaluations.

Sweep excitation with order tracking: A new tactic for beam crack analysis

NASA Astrophysics Data System (ADS)

Wei, Dongdong; Wang, KeSheng; Zhang, Mian; Zuo, Ming J.

2018-04-01

Crack detection in beams and beam-like structures is an important issue in industry and has attracted numerous investigations. A local crack leads to global system dynamics changes and produce non-linear vibration responses. Many researchers have studied these non-linearities for beam crack diagnosis. However, most reported methods are based on impact excitation and constant frequency excitation. Few studies have focused on crack detection through external sweep excitation which unleashes abundant dynamic characteristics of the system. Together with a signal resampling technique inspired by Computed Order Tracking, this paper utilize vibration responses under sweep excitations to diagnose crack status of beams. A data driven method for crack depth evaluation is proposed and window based harmonics extracting approaches are studied. The effectiveness of sweep excitation and the proposed method is experimentally validated.

Bicycle Guidelines and Crash Rates on Cycle Tracks in the United States

PubMed Central

Morency, Patrick; Miranda-Moreno, Luis F.; Willett, Walter C.; Dennerlein, Jack T.

2013-01-01

Objectives. We studied state-adopted bicycle guidelines to determine whether cycle tracks (physically separated, bicycle-exclusive paths adjacent to sidewalks) were recommended, whether they were built, and their crash rate. Methods. We analyzed and compared US bicycle facility guidelines published between 1972 and 1999. We identified 19 cycle tracks in the United States and collected extensive data on cycle track design, usage, and crash history from local communities. We used bicycle counts and crash data to estimate crash rates. Results. A bicycle facility guideline written in 1972 endorsed cycle tracks but American Association of State Highway and Transportation Officials (AASHTO) guidelines (1974–1999) discouraged or did not include cycle tracks and did not cite research about crash rates on cycle tracks. For the 19 US cycle tracks we examined, the overall crash rate was 2.3 (95% confidence interval = 1.7, 3.0) per 1 million bicycle kilometers. Conclusions. AASHTO bicycle guidelines are not explicitly based on rigorous or up-to-date research. Our results show that the risk of bicycle–vehicle crashes is lower on US cycle tracks than published crashes rates on roadways. This study and previous investigations support building cycle tracks. PMID:23678920

Human-tracking strategies for a six-legged rescue robot based on distance and view

NASA Astrophysics Data System (ADS)

Pan, Yang; Gao, Feng; Qi, Chenkun; Chai, Xun

2016-03-01

Human tracking is an important issue for intelligent robotic control and can be used in many scenarios, such as robotic services and human-robot cooperation. Most of current human-tracking methods are targeted for mobile/tracked robots, but few of them can be used for legged robots. Two novel human-tracking strategies, view priority strategy and distance priority strategy, are proposed specially for legged robots, which enable them to track humans in various complex terrains. View priority strategy focuses on keeping humans in its view angle arrange with priority, while its counterpart, distance priority strategy, focuses on keeping human at a reasonable distance with priority. To evaluate these strategies, two indexes(average and minimum tracking capability) are defined. With the help of these indexes, the view priority strategy shows advantages compared with distance priority strategy. The optimization is done in terms of these indexes, which let the robot has maximum tracking capability. The simulation results show that the robot can track humans with different curves like square, circular, sine and screw paths. Two novel control strategies are proposed which specially concerning legged robot characteristics to solve human tracking problems more efficiently in rescue circumstances.

Single-camera visual odometry to track a surgical X-ray C-arm base.

PubMed

Esfandiari, Hooman; Lichti, Derek; Anglin, Carolyn

2017-12-01

This study provides a framework for a single-camera odometry system for localizing a surgical C-arm base. An application-specific monocular visual odometry system (a downward-looking consumer-grade camera rigidly attached to the C-arm base) is proposed in this research. The cumulative dead-reckoning estimation of the base is extracted based on frame-to-frame homography estimation. Optical-flow results are utilized to feed the odometry. Online positional and orientation parameters are then reported. Positional accuracy of better than 2% (of the total traveled distance) for most of the cases and 4% for all the cases studied and angular accuracy of better than 2% (of absolute cumulative changes in orientation) were achieved with this method. This study provides a robust and accurate tracking framework that not only can be integrated with the current C-arm joint-tracking system (i.e. TC-arm) but also is capable of being employed for similar applications in other fields (e.g. robotics).

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy.

PubMed

Li, Hua; Chen, Hsin-Chen; Dolly, Steven; Li, Harold; Fischer-Valuck, Benjamin; Victoria, James; Dempsey, James; Ruan, Su; Anastasio, Mark; Mazur, Thomas; Gach, Michael; Kashani, Rojano; Green, Olga; Rodriguez, Vivian; Gay, Hiram; Thorstad, Wade; Mutic, Sasa

2016-08-01

For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

Lagrangian Particle Tracking Simulation for Warm-Rain Processes in Quasi-One-Dimensional Domain

NASA Astrophysics Data System (ADS)

Kunishima, Y.; Onishi, R.

2017-12-01

Conventional cloud simulations are based on the Euler method and compute each microphysics process in a stochastic way assuming infinite numbers of particles within each numerical grid. They therefore cannot provide the Lagrangian statistics of individual particles in cloud microphysics (i.e., aerosol particles, cloud particles, and rain drops) nor discuss the statistical fluctuations due to finite number of particles. We here simulate the entire precipitation process of warm-rain, with tracking individual particles. We use the Lagrangian Cloud Simulator (LCS), which is based on the Euler-Lagrangian framework. In that framework, flow motion and scalar transportation are computed with the Euler method, and particle motion with the Lagrangian one. The LCS tracks particle motions and collision events individually with considering the hydrodynamic interaction between approaching particles with a superposition method, that is, it can directly represent the collisional growth of cloud particles. It is essential for trustworthy collision detection to take account of the hydrodynamic interaction. In this study, we newly developed a stochastic model based on the Twomey cloud condensation nuclei (CCN) activation for the Lagrangian tracking simulation and integrated it into the LCS. Coupling with the Euler computation for water vapour and temperature fields, the initiation and condensational growth of water droplets were computed in the Lagrangian way. We applied the integrated LCS for a kinematic simulation of warm-rain processes in a vertically-elongated domain of, at largest, 0.03×0.03×3000 (m3) with horizontal periodicity. Aerosol particles with a realistic number density, 5×107 (m3), were evenly distributed over the domain at the initial state. Prescribed updraft at the early stage initiated development of a precipitating cloud. We have confirmed that the obtained bulk statistics fairly agree with those from a conventional spectral-bin scheme for a vertical column domain. The centre of the discussion will be the Lagrangian statistics which is collected from the individual behaviour of the tracked particles.

Application of a novel Kalman filter based block matching method to ultrasound images for hand tendon displacement estimation.

PubMed

Lai, Ting-Yu; Chen, Hsiao-I; Shih, Cho-Chiang; Kuo, Li-Chieh; Hsu, Hsiu-Yun; Huang, Chih-Chung

2016-01-01

Information about tendon displacement is important for allowing clinicians to not only quantify preoperative tendon injuries but also to identify any adhesive scaring between tendon and adjacent tissue. The Fisher-Tippett (FT) similarity measure has recently been shown to be more accurate than the Laplacian sum of absolute differences (SAD) and Gaussian sum of squared differences (SSD) similarity measures for tracking tendon displacement in ultrasound B-mode images. However, all of these similarity measures can easily be influenced by the quality of the ultrasound image, particularly its signal-to-noise ratio. Ultrasound images of injured hands are unfortunately often of poor quality due to the presence of adhesive scars. The present study investigated a novel Kalman-filter scheme for overcoming this problem. Three state-of-the-art tracking methods (FT, SAD, and SSD) were used to track the displacements of phantom and cadaver tendons, while FT was used to track human tendons. These three tracking methods were combined individually with the proposed Kalman-filter (K1) scheme and another Kalman-filter scheme used in a previous study to optimize the displacement trajectories of the phantom and cadaver tendons. The motion of the human extensor digitorum communis tendon was measured in the present study using the FT-K1 scheme. The experimental results indicated that SSD exhibited better accuracy in the phantom experiments, whereas FT exhibited better performance for tracking real tendon motion in the cadaver experiments. All three tracking methods were influenced by the signal-to-noise ratio of the images. On the other hand, the K1 scheme was able to optimize the tracking trajectory of displacement in all experiments, even from a location with a poor image quality. The human experimental data indicated that the normal tendons were displaced more than the injured tendons, and that the motion ability of the injured tendon was restored after appropriate rehabilitation sessions. The obtained results show the potential for applying the proposed FT-K1 method in clinical applications for evaluating the tendon injury level after metacarpal fractures and assessing the recovery of an injured tendon during rehabilitation.

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera

PubMed Central

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions. PMID:29261719

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera.

PubMed

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions.

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

PubMed

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Adaptive control of servo system based on LuGre model

NASA Astrophysics Data System (ADS)

Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

2018-03-01

This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

PubMed Central

Wang, Lijuan; Wu, Lifeng; Guan, Yong; Wang, Guohui

2015-01-01

We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model. PMID:25690553

Study on robot motion control for intelligent welding processes based on the laser tracking sensor

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

2017-06-01

A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

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

Crijns, Wouter, E-mail: wouter.crijns@uzleuven.be; Depuydt, Tom; Haustermans, Karin

Purpose: To evaluate three different plan adaptation strategies using 3D film-stack dose measurements of both focal boost and hypofractionated prostate VMAT treatments. The adaptation strategies (a couch shift, geometric tracking, and dosimetric tracking) were applied for three realistic intrafraction prostate motions. Methods: A focal boost (35 × 2.2 and 35 × 2.7 Gy) and a hypofractionated (5 × 7.25 Gy) prostate VMAT plan were created for a heterogeneous phantom that allows for internal prostate motion. For these plans geometric tracking and dosimetric tracking were evaluated by ionization chamber (IC) point dose measurements (zero-D) and measurements using a stack of EBT3more » films (3D). The geometric tracking applied translations, rotations, and scaling of the MLC aperture in response to realistic prostate motions. The dosimetric tracking additionally corrected the monitor units to resolve variations due to difference in depth, tissue heterogeneity, and MLC-aperture. The tracking was based on the positions of four fiducial points only. The film measurements were compared to the gold standard (i.e., IC measurements) and the planned dose distribution. Additionally, the 3D measurements were converted to dose volume histograms, tumor control probability, and normal tissue complication probability parameters (DVH/TCP/NTCP) as a direct estimate of clinical relevance of the proposed tracking. Results: Compared to the planned dose distribution, measurements without prostate motion and tracking showed already a reduced homogeneity of the dose distribution. Adding prostate motion further blurs the DVHs for all treatment approaches. The clinical practice (no tracking) delivered the dose distribution inside the PTV but off target (CTV), resulting in boost dose errors up to 10%. The geometric and dosimetric tracking corrected the dose distribution’s position. Moreover, the dosimetric tracking could achieve the planned boost DVH, but not the DVH of the more homogeneously irradiated prostate. A drawback of both the geometric and dosimetric tracking was a reduced MLC blocking caused by the rotational component of the MLC aperture corrections. Because of the used CTV to PTV margins and the high doses in the considered fractionation schemes, the TCP differed less than 0.02 from the planned value for all targets and all correction methods. The rectal NTCP constraints, however, could not be realized using any of these methods. Conclusions: The geometric and dosimetric tracking use only a limited input, but they deposit the dose distribution with higher geometric accuracy than the clinical practice. The latter case has boost dose errors up to 10%. The increased accuracy has a modest impact [Δ(NT)CP < 0.02] because of the applied margins and the high dose levels used. To allow further margin reduction tracking methods are vital. The proposed methodology could further be improved by implementing a rotational correction using collimator rotations.« less

Tracking B-Cell Repertoires and Clonal Histories in Normal and Malignant Lymphocytes.

PubMed

Weston-Bell, Nicola J; Cowan, Graeme; Sahota, Surinder S

2017-01-01

Methods for tracking B-cell repertoires and clonal history in normal and malignant B-cells based on immunoglobulin variable region (IGV) gene analysis have developed rapidly with the advent of massive parallel next-generation sequencing (mpNGS) protocols. mpNGS permits a depth of analysis of IGV genes not hitherto feasible, and presents challenges of bioinformatics analysis, which can be readily met by current pipelines. This strategy offers a potential resolution of B-cell usage at a depth that may capture fully the natural state, in a given biological setting. Conventional methods based on RT-PCR amplification and Sanger sequencing are also available where mpNGS is not accessible. Each method offers distinct advantages. Conventional methods for IGV gene sequencing are readily adaptable to most laboratories and provide an ease of analysis to capture salient features of B-cell use. This chapter describes two methods in detail for analysis of IGV genes, mpNGS and conventional RT-PCR with Sanger sequencing.

Eye gaze tracking based on the shape of pupil image

NASA Astrophysics Data System (ADS)

Wang, Rui; Qiu, Jian; Luo, Kaiqing; Peng, Li; Han, Peng

2018-01-01

Eye tracker is an important instrument for research in psychology, widely used in attention, visual perception, reading and other fields of research. Because of its potential function in human-computer interaction, the eye gaze tracking has already been a topic of research in many fields over the last decades. Nowadays, with the development of technology, non-intrusive methods are more and more welcomed. In this paper, we will present a method based on the shape of pupil image to estimate the gaze point of human eyes without any other intrusive devices such as a hat, a pair of glasses and so on. After using the ellipse fitting algorithm to deal with the pupil image we get, we can determine the direction of the fixation by the shape of the pupil.The innovative aspect of this method is to utilize the new idea of the shape of the pupil so that we can avoid much complicated algorithm. The performance proposed is very helpful for the study of eye gaze tracking, which just needs one camera without infrared light to know the changes in the shape of the pupil to determine the direction of the eye gazing, no additional condition is required.

Generic framework for vessel detection and tracking based on distributed marine radar image data

NASA Astrophysics Data System (ADS)

Siegert, Gregor; Hoth, Julian; Banyś, Paweł; Heymann, Frank

2018-04-01

Situation awareness is understood as a key requirement for safe and secure shipping at sea. The primary sensor for maritime situation assessment is still the radar, with the AIS being introduced as supplemental service only. In this article, we present a framework to assess the current situation picture based on marine radar image processing. Essentially, the framework comprises a centralized IMM-JPDA multi-target tracker in combination with a fully automated scheme for track management, i.e., target acquisition and track depletion. This tracker is conditioned on measurements extracted from radar images. To gain a more robust and complete situation picture, we are exploiting the aspect angle diversity of multiple marine radars, by fusing them a priori to the tracking process. Due to the generic structure of the proposed framework, different techniques for radar image processing can be implemented and compared, namely the BLOB detector and SExtractor. The overall framework performance in terms of multi-target state estimation will be compared for both methods based on a dedicated measurement campaign in the Baltic Sea with multiple static and mobile targets given.

Video tracking analysis of behavioral patterns during estrus in goats

PubMed Central

ENDO, Natsumi; RAHAYU, Larasati Puji; ARAKAWA, Toshiya; TANAKA, Tomomi

2015-01-01

Here, we report a new method for measuring behavioral patterns during estrus in goats based on video tracking analysis. Data were collected from cycling goats, which were in estrus (n = 8) or not in estrus (n = 8). An observation pen (2.5 m × 2.5 m) was set up in the corner of the female paddock with one side adjacent to a male paddock. The positions and movements of goats were tracked every 0.5 sec for 10 min by using a video tracking software, and the trajectory data were used for the analysis. There were no significant differences in the durations of standing and walking or the total length of movement. However, the number of approaches to a male and the duration of staying near the male were higher in goats in estrus than in goats not in estrus. The proposed evaluation method may be suitable for detailed monitoring of behavioral changes during estrus in goats. PMID:26560676