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

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.

SU-G-BRA-17: Tracking Multiple Targets with Independent Motion in Real-Time Using a Multi-Leaf Collimator

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

Ge, Y; Keall, P; Poulsen, P

Purpose: Multiple targets with large intrafraction independent motion are often involved in advanced prostate, lung, abdominal, and head and neck cancer radiotherapy. Current standard of care treats these with the originally planned fields, jeopardizing the treatment outcomes. A real-time multi-leaf collimator (MLC) tracking method has been developed to address this problem for the first time. This study evaluates the geometric uncertainty of the multi-target tracking method. Methods: Four treatment scenarios are simulated based on a prostate IMAT plan to treat a moving prostate target and static pelvic node target: 1) real-time multi-target MLC tracking; 2) real-time prostate-only MLC tracking; 3)more » correcting for prostate interfraction motion at setup only; and 4) no motion correction. The geometric uncertainty of the treatment is assessed by the sum of the erroneously underexposed target area and overexposed healthy tissue areas for each individual target. Two patient-measured prostate trajectories of average 2 and 5 mm motion magnitude are used for simulations. Results: Real-time multi-target tracking accumulates the least uncertainty overall. As expected, it covers the static nodes similarly well as no motion correction treatment and covers the moving prostate similarly well as the real-time prostate-only tracking. Multi-target tracking reduces >90% of uncertainty for the static nodal target compared to the real-time prostate-only tracking or interfraction motion correction. For prostate target, depending on the motion trajectory which affects the uncertainty due to leaf-fitting, multi-target tracking may or may not perform better than correcting for interfraction prostate motion by shifting patient at setup, but it reduces ∼50% of uncertainty compared to no motion correction. Conclusion: The developed real-time multi-target MLC tracking can adapt for the independently moving targets better than other available treatment adaptations. This will enable PTV margin reduction to minimize health tissue toxicity while remain tumor coverage when treating advanced disease with independently moving targets involved. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship and NHMRC Project Grant No. APP1042375.« less

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.

Development of three-dimensional tracking system using astigmatic lens method for microscopes

NASA Astrophysics Data System (ADS)

Kibata, Hiroki; Ishii, Katsuhiro

2017-07-01

We have developed a three-dimensional tracking system for microscopes. Using the astigmatic lens method and a CMOS image sensor, we realize a rapid detection of a target position in a wide range. We demonstrate a target tracking using the developed system.

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

PubMed Central

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-01-01

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

PubMed

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-02-12

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

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.

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.

Application of Hybrid Along-Track Interferometry/Displaced Phase Center Antenna Method for Moving Human Target Detection in Forest Environments

DTIC Science & Technology

2016-10-01

ARL-TR-7846 ● OCT 2016 US Army Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center...Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center Antenna Method for Moving Human Target Detection...TYPE Technical Report 3. DATES COVERED (From - To) 2015–2016 4. TITLE AND SUBTITLE Application of Hybrid Along-Track Interferometry/ Displaced

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.

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.

Occlusion handling framework for tracking in smart camera networks by per-target assistance task assignment

NASA Astrophysics Data System (ADS)

Bo, Nyan Bo; Deboeverie, Francis; Veelaert, Peter; Philips, Wilfried

2017-09-01

Occlusion is one of the most difficult challenges in the area of visual tracking. We propose an occlusion handling framework to improve the performance of local tracking in a smart camera view in a multicamera network. We formulate an extensible energy function to quantify the quality of a camera's observation of a particular target by taking into account both person-person and object-person occlusion. Using this energy function, a smart camera assesses the quality of observations over all targets being tracked. When it cannot adequately observe of a target, a smart camera estimates the quality of observation of the target from view points of other assisting cameras. If a camera with better observation of the target is found, the tracking task of the target is carried out with the assistance of that camera. In our framework, only positions of persons being tracked are exchanged between smart cameras. Thus, communication bandwidth requirement is very low. Performance evaluation of our method on challenging video sequences with frequent and severe occlusions shows that the accuracy of a baseline tracker is considerably improved. We also report the performance comparison to the state-of-the-art trackers in which our method outperforms.

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.

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

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

Robust infrared targets tracking with covariance matrix representation

NASA Astrophysics Data System (ADS)

Cheng, Jian

2009-07-01

Robust infrared target tracking is an important and challenging research topic in many military and security applications, such as infrared imaging guidance, infrared reconnaissance, scene surveillance, etc. To effectively tackle the nonlinear and non-Gaussian state estimation problems, particle filtering is introduced to construct the theory framework of infrared target tracking. Under this framework, the observation probabilistic model is one of main factors for infrared targets tracking performance. In order to improve the tracking performance, covariance matrices are introduced to represent infrared targets with the multi-features. The observation probabilistic model can be constructed by computing the distance between the reference target's and the target samples' covariance matrix. Because the covariance matrix provides a natural tool for integrating multiple features, and is scale and illumination independent, target representation with covariance matrices can hold strong discriminating ability and robustness. Two experimental results demonstrate the proposed method is effective and robust for different infrared target tracking, such as the sensor ego-motion scene, and the sea-clutter scene.

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.

Three-dimensional microscope tracking system using the astigmatic lens method and a profile sensor

NASA Astrophysics Data System (ADS)

Kibata, Hiroki; Ishii, Katsuhiro

2018-03-01

We developed a three-dimensional microscope tracking system using the astigmatic lens method and a profile sensor, which provides three-dimensional position detection over a wide range at the rate of 3.2 kHz. First, we confirmed the range of target detection of the developed system, where the range of target detection was shown to be ± 90 µm in the horizontal plane and ± 9 µm in the vertical plane for a 10× objective lens. Next, we attempted to track a motion-controlled target. The developed system kept the target at the center of the field of view and in focus up to a target speed of 50 µm/s for a 20× objective lens. Finally, we tracked a freely moving target. We successfully demonstrated the tracking of a 10-µm-diameter polystyrene bead suspended in water for 40 min. The target was kept in the range of approximately 4.9 µm around the center of the field of view. In addition, the vertical direction was maintained in the range of ± 0.84 µm, which was sufficiently within the depth of focus.

IVF: exploiting intensity variation function for high-performance pedestrian tracking in forward-looking infrared imagery

NASA Astrophysics Data System (ADS)

Lamberti, Fabrizio; Sanna, Andrea; Paravati, Gianluca; Belluccini, Luca

2014-02-01

Tracking pedestrian targets in forward-looking infrared video sequences is a crucial component of a growing number of applications. At the same time, it is particularly challenging, since image resolution and signal-to-noise ratio are generally very low, while the nonrigidity of the human body produces highly variable target shapes. Moreover, motion can be quite chaotic with frequent target-to-target and target-to-scene occlusions. Hence, the trend is to design ever more sophisticated techniques, able to ensure rather accurate tracking results at the cost of a generally higher complexity. However, many of such techniques might not be suitable for real-time tracking in limited-resource environments. This work presents a technique that extends an extremely computationally efficient tracking method based on target intensity variation and template matching originally designed for targets with a marked and stable hot spot by adapting it to deal with much more complex thermal signatures and by removing the native dependency on configuration choices. Experimental tests demonstrated that, by working on multiple hot spots, the designed technique is able to achieve the robustness of other common approaches by limiting drifts and preserving the low-computational footprint of the reference method.

A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs.

PubMed

Qian, Hanwang; Fu, Pengcheng; Li, Baoqing; Liu, Jianpo; Yuan, Xiaobing

2018-01-25

Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes.

A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs

PubMed Central

Liu, Jianpo; Yuan, Xiaobing

2018-01-01

Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes. PMID:29370103

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

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.

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.

Multisensor fusion for 3D target tracking using track-before-detect particle filter

NASA Astrophysics Data System (ADS)

Moshtagh, Nima; Romberg, Paul M.; Chan, Moses W.

2015-05-01

This work presents a novel fusion mechanism for estimating the three-dimensional trajectory of a moving target using images collected by multiple imaging sensors. The proposed projective particle filter avoids the explicit target detection prior to fusion. In projective particle filter, particles that represent the posterior density (of target state in a high-dimensional space) are projected onto the lower-dimensional observation space. Measurements are generated directly in the observation space (image plane) and a marginal (sensor) likelihood is computed. The particles states and their weights are updated using the joint likelihood computed from all the sensors. The 3D state estimate of target (system track) is then generated from the states of the particles. This approach is similar to track-before-detect particle filters that are known to perform well in tracking dim and stealthy targets in image collections. Our approach extends the track-before-detect approach to 3D tracking using the projective particle filter. The performance of this measurement-level fusion method is compared with that of a track-level fusion algorithm using the projective particle filter. In the track-level fusion algorithm, the 2D sensor tracks are generated separately and transmitted to a fusion center, where they are treated as measurements to the state estimator. The 2D sensor tracks are then fused to reconstruct the system track. A realistic synthetic scenario with a boosting target was generated, and used to study the performance of the fusion mechanisms.

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.

A real-time optical tracking and measurement processing system for flying targets.

PubMed

Guo, Pengyu; Ding, Shaowen; Zhang, Hongliang; Zhang, Xiaohu

2014-01-01

Optical tracking and measurement for flying targets is unlike the close range photography under a controllable observation environment, which brings extreme conditions like diverse target changes as a result of high maneuver ability and long cruising range. This paper first designed and realized a distributed image interpretation and measurement processing system to achieve resource centralized management, multisite simultaneous interpretation and adaptive estimation algorithm selection; then proposed a real-time interpretation method which contains automatic foreground detection, online target tracking, multiple features location, and human guidance. An experiment is carried out at performance and efficiency evaluation of the method by semisynthetic video. The system can be used in the field of aerospace tests like target analysis including dynamic parameter, transient states, and optical physics characteristics, with security control.

A Real-Time Optical Tracking and Measurement Processing System for Flying Targets

PubMed Central

Guo, Pengyu; Ding, Shaowen; Zhang, Hongliang; Zhang, Xiaohu

2014-01-01

Optical tracking and measurement for flying targets is unlike the close range photography under a controllable observation environment, which brings extreme conditions like diverse target changes as a result of high maneuver ability and long cruising range. This paper first designed and realized a distributed image interpretation and measurement processing system to achieve resource centralized management, multisite simultaneous interpretation and adaptive estimation algorithm selection; then proposed a real-time interpretation method which contains automatic foreground detection, online target tracking, multiple features location, and human guidance. An experiment is carried out at performance and efficiency evaluation of the method by semisynthetic video. The system can be used in the field of aerospace tests like target analysis including dynamic parameter, transient states, and optical physics characteristics, with security control. PMID:24987748

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.

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

A Parallel Finite Set Statistical Simulator for Multi-Target Detection and Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; MacMillan, R.

2014-09-01

Finite Set Statistics (FISST) is a powerful Bayesian inference tool for the joint detection, classification and tracking of multi-target environments. FISST is capable of handling phenomena such as clutter, misdetections, and target birth and decay. Implicit within the approach are solutions to the data association and target label-tracking problems. Finally, FISST provides generalized information measures that can be used for sensor allocation across different types of tasks such as: searching for new targets, and classification and tracking of known targets. These FISST capabilities have been demonstrated on several small-scale illustrative examples. However, for implementation in a large-scale system as in the Space Situational Awareness problem, these capabilities require a lot of computational power. In this paper, we implement FISST in a parallel environment for the joint detection and tracking of multi-target systems. In this implementation, false alarms and misdetections will be modeled. Target birth and decay will not be modeled in the present paper. We will demonstrate the success of the method for as many targets as we possibly can in a desktop parallel environment. Performance measures will include: number of targets in the simulation, certainty of detected target tracks, computational time as a function of clutter returns and number of targets, among other factors.

A real-time tracking system of infrared dim and small target based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Rong, Sheng-hui; Zhou, Hui-xin; Qin, Han-lin; Wang, Bing-jian; Qian, Kun

2014-11-01

A core technology in the infrared warning system is the detection tracking of dim and small targets with complicated background. Consequently, running the detection algorithm on the hardware platform has highly practical value in the military field. In this paper, a real-time detection tracking system of infrared dim and small target which is used FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) as the core was designed and the corresponding detection tracking algorithm and the signal flow is elaborated. At the first stage, the FPGA obtain the infrared image sequence from the sensor, then it suppresses background clutter by mathematical morphology method and enhances the target intensity by Laplacian of Gaussian operator. At the second stage, the DSP obtain both the original image and the filtered image form the FPGA via the video port. Then it segments the target from the filtered image by an adaptive threshold segmentation method and gets rid of false target by pipeline filter. Experimental results show that our system can achieve higher detection rate and lower false alarm rate.

Summary of tracking and identification methods

NASA Astrophysics Data System (ADS)

Blasch, Erik; Yang, Chun; Kadar, Ivan

2014-06-01

Over the last two decades, many solutions have arisen to combine target tracking estimation with classification methods. Target tracking includes developments from linear to non-linear and Gaussian to non-Gaussian processing. Pattern recognition includes detection, classification, recognition, and identification methods. Integrating tracking and pattern recognition has resulted in numerous approaches and this paper seeks to organize the various approaches. We discuss the terminology so as to have a common framework for various standards such as the NATO STANAG 4162 - Identification Data Combining Process. In a use case, we provide a comparative example highlighting that location information (as an example) with additional mission objectives from geographical, human, social, cultural, and behavioral modeling is needed to determine identification as classification alone does not allow determining identification or intent.

A ground moving target emergency tracking method for catastrophe rescue

NASA Astrophysics Data System (ADS)

Zhou, X.; Li, D.; Li, G.

2014-11-01

In recent years, great disasters happen now and then. Disaster management test the emergency operation ability of the government and society all over the world. Immediately after the occurrence of a great disaster (e.g., earthquake), a massive nationwide rescue and relief operation need to be kicked off instantly. In order to improve the organizations efficiency of the emergency rescue, the organizers need to take charge of the information of the rescuer teams, including the real time location, the equipment with the team, the technical skills of the rescuers, and so on. One of the key factors for the success of emergency operations is the real time location of the rescuers dynamically. Real time tracking methods are used to track the professional rescuer teams now. But volunteers' participation play more and more important roles in great disasters. However, real time tracking of the volunteers will cause many problems, e.g., privacy leakage, expensive data consumption, etc. These problems may reduce the enthusiasm of volunteers' participation for catastrophe rescue. In fact, the great disaster is just small probability event, it is not necessary to track the volunteers (even rescuer teams) every time every day. In order to solve this problem, a ground moving target emergency tracking method for catastrophe rescue is presented in this paper. In this method, the handheld devices using GPS technology to provide the location of the users, e.g., smart phone, is used as the positioning equipment; an emergency tracking information database including the ID of the ground moving target (including the rescuer teams and volunteers), the communication number of the handheld devices with the moving target, and the usually living region, etc., is built in advance by registration; when catastrophe happens, the ground moving targets that living close to the disaster area will be filtered by the usually living region; then the activation short message will be sent to the selected ground moving target through the communication number of the handheld devices. The handheld devices receive and identify the activation short message, and send the current location information to the server. Therefore, the emergency tracking mode is triggered. The real time location of the filtered target can be shown on the organizer's screen, and the organizer can assign the rescue tasks to the rescuer teams and volunteers based on their real time location. The ground moving target emergency tracking prototype system is implemented using Oracle 11g, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

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.

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.

Search Radar Track-Before-Detect Using the Hough Transform.

DTIC Science & Technology

1995-03-01

before - detect processing method which allows previous data to help in target detection. The technique provides many advantages compared to...improved target detection scheme, applicable to search radars, using the Hough transform image processing technique. The system concept involves a track

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.

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.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

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 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

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

Infrared dim and small target detecting and tracking method inspired by Human Visual System

NASA Astrophysics Data System (ADS)

Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Shen, Lurong; Bai, Shengjian

2014-01-01

Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.

KU-Band rendezvous radar performance computer simulation model

NASA Technical Reports Server (NTRS)

Griffin, J. W.

1980-01-01

The preparation of a real time computer simulation model of the KU band rendezvous radar to be integrated into the shuttle mission simulator (SMS), the shuttle engineering simulator (SES), and the shuttle avionics integration laboratory (SAIL) simulator is described. To meet crew training requirements a radar tracking performance model, and a target modeling method were developed. The parent simulation/radar simulation interface requirements, and the method selected to model target scattering properties, including an application of this method to the SPAS spacecraft are described. The radar search and acquisition mode performance model and the radar track mode signal processor model are examined and analyzed. The angle, angle rate, range, and range rate tracking loops are also discussed.

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.

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.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

A Biocompatible Near-Infrared 3D Tracking System*

PubMed Central

Decker, Ryan S.; Shademan, Azad; Opfermann, Justin D.; Leonard, Simon; Kim, Peter C. W.; Krieger, Axel

2017-01-01

A fundamental challenge in soft-tissue surgery is that target tissue moves and deforms, becomes occluded by blood or other tissue, and is difficult to differentiate from surrounding tissue. We developed small biocompatible near-infrared fluorescent (NIRF) markers with a novel fused plenoptic and NIR camera tracking system, enabling 3D tracking of tools and target tissue while overcoming blood and tissue occlusion in the uncontrolled, rapidly changing surgical environment. In this work, we present the tracking system and marker design and compare tracking accuracies to standard optical tracking methods using robotic experiments. At speeds of 1 mm/s, we observe tracking accuracies of 1.61 mm, degrading only to 1.71 mm when the markers are covered in blood and tissue. PMID:28129145

Biocompatible Near-Infrared Three-Dimensional Tracking System.

PubMed

Decker, Ryan S; Shademan, Azad; Opfermann, Justin D; Leonard, Simon; Kim, Peter C W; Krieger, Axel

2017-03-01

A fundamental challenge in soft-tissue surgery is that target tissue moves and deforms, becomes occluded by blood or other tissue, and is difficult to differentiate from surrounding tissue. We developed small biocompatible near-infrared fluorescent (NIRF) markers with a novel fused plenoptic and NIR camera tracking system, enabling three-dimensional tracking of tools and target tissue while overcoming blood and tissue occlusion in the uncontrolled, rapidly changing surgical environment. In this work, we present the tracking system and marker design and compare tracking accuracies to standard optical tracking methods using robotic experiments. At speeds of 1 mm/s, we observe tracking accuracies of 1.61 mm, degrading only to 1.71 mm when the markers are covered in blood and tissue.

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.

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.

Tracking a Non-Cooperative Target Using Real-Time Stereovision-Based Control: An Experimental Study.

PubMed

Shtark, Tomer; Gurfil, Pini

2017-03-31

Tracking a non-cooperative target is a challenge, because in unfamiliar environments most targets are unknown and unspecified. Stereovision is suited to deal with this issue, because it allows to passively scan large areas and estimate the relative position, velocity and shape of objects. This research is an experimental effort aimed at developing, implementing and evaluating a real-time non-cooperative target tracking methods using stereovision measurements only. A computer-vision feature detection and matching algorithm was developed in order to identify and locate the target in the captured images. Three different filters were designed for estimating the relative position and velocity, and their performance was compared. A line-of-sight control algorithm was used for the purpose of keeping the target within the field-of-view. Extensive analytical and numerical investigations were conducted on the multi-view stereo projection equations and their solutions, which were used to initialize the different filters. This research shows, using an experimental and numerical evaluation, the benefits of using the unscented Kalman filter and the total least squares technique in the stereovision-based tracking problem. These findings offer a general and more accurate method for solving the static and dynamic stereovision triangulation problems and the concomitant line-of-sight control.

Tracking a Non-Cooperative Target Using Real-Time Stereovision-Based Control: An Experimental Study

PubMed Central

Shtark, Tomer; Gurfil, Pini

2017-01-01

Tracking a non-cooperative target is a challenge, because in unfamiliar environments most targets are unknown and unspecified. Stereovision is suited to deal with this issue, because it allows to passively scan large areas and estimate the relative position, velocity and shape of objects. This research is an experimental effort aimed at developing, implementing and evaluating a real-time non-cooperative target tracking methods using stereovision measurements only. A computer-vision feature detection and matching algorithm was developed in order to identify and locate the target in the captured images. Three different filters were designed for estimating the relative position and velocity, and their performance was compared. A line-of-sight control algorithm was used for the purpose of keeping the target within the field-of-view. Extensive analytical and numerical investigations were conducted on the multi-view stereo projection equations and their solutions, which were used to initialize the different filters. This research shows, using an experimental and numerical evaluation, the benefits of using the unscented Kalman filter and the total least squares technique in the stereovision-based tracking problem. These findings offer a general and more accurate method for solving the static and dynamic stereovision triangulation problems and the concomitant line-of-sight control. PMID:28362338

Control Method for Video Guidance Sensor System

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are commands is permitted only when the system is in the carried out. Further, acceptance of reset and diagnostic standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

Control method for video guidance sensor system

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are carried out. Further, acceptance of reset and diagnostic commands is permitted only when the system is in the standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

Water-Column Stratification Observed along an AUV-Tracked Isotherm

NASA Astrophysics Data System (ADS)

Zhang, Y.; Messié, M.; Ryan, J. P.; Kieft, B.; Stanway, M. J.; Hobson, B.; O'Reilly, T. C.; Raanan, B. Y.; Smith, J. M.; Chavez, F.

2016-02-01

Studies of marine physical, chemical and microbiological processes benefit from observing in a Lagrangian frame of reference, i.e. drifting with ambient water. Because these processes can be organized relative to specific density or temperature ranges, maintaining observing platforms within targeted environmental ranges is an important observing strategy. We have developed a novel method to enable a Tethys-class long-range autonomous underwater vehicle (AUV) (which has a propeller and a buoyancy engine) to track a target isotherm in buoyancy-controlled drift mode. In this mode, the vehicle shuts off its propeller and autonomously detects the isotherm and stays with it by actively controlling the vehicle's buoyancy. In the June 2015 CANON (Controlled, Agile, and Novel Observing Network) Experiment in Monterey Bay, California, AUV Makai tracked a target isotherm for 13 hours to study the coastal upwelling system. The tracked isotherm started from 33 m depth, shoaled to 10 m, and then deepened to 29 m. The thickness of the tracked isotherm layer (within 0.3°C error from the target temperature) increased over this duration, reflecting weakened stratification around the isotherm. During Makai's isotherm tracking, another long-range AUV, Daphne, acoustically tracked Makai on a circular yo-yo trajectory, measuring water-column profiles in Makai's vicinity. A wave glider also acoustically tracked Makai, providing sea surface measurements on the track. The presented method is a new approach for studying water-column stratification, but requires careful analysis of the temporal and spatial variations mingled in the vehicles' measurements. We will present a synthesis of the water column's stratification in relation to the upwelling conditions, based on the in situ measurements by the mobile platforms, as well as remote sensing and mooring data.

The first clinical implementation of electromagnetic transponder-guided MLC tracking

PubMed Central

Keall, Paul J.; Colvill, Emma; O’Brien, Ricky; Ng, Jin Aun; Poulsen, Per Rugaard; Eade, Thomas; Kneebone, Andrew; Booth, Jeremy T.

2014-01-01

Purpose: We report on the clinical process, quality assurance, and geometric and dosimetric results of the first clinical implementation of electromagnetic transponder-guided MLC tracking which occurred on 28 November 2013 at the Northern Sydney Cancer Centre. Methods: An electromagnetic transponder-based positioning system (Calypso) was modified to send the target position output to in-house-developed MLC tracking code, which adjusts the leaf positions to optimally align the treatment beam with the real-time target position. Clinical process and quality assurance procedures were developed and performed. The first clinical implementation of electromagnetic transponder-guided MLC tracking was for a prostate cancer patient being treated with dual-arc VMAT (RapidArc). For the first fraction of the first patient treatment of electromagnetic transponder-guided MLC tracking we recorded the in-room time and transponder positions, and performed dose reconstruction to estimate the delivered dose and also the dose received had MLC tracking not been used. Results: The total in-room time was 21 min with 2 min of beam delivery. No additional time was needed for MLC tracking and there were no beam holds. The average prostate position from the initial setup was 1.2 mm, mostly an anterior shift. Dose reconstruction analysis of the delivered dose with MLC tracking showed similar isodose and target dose volume histograms to the planned treatment and a 4.6% increase in the fractional rectal V60. Dose reconstruction without motion compensation showed a 30% increase in the fractional rectal V60 from that planned, even for the small motion. Conclusions: The real-time beam-target correction method, electromagnetic transponder-guided MLC tracking, has been translated to the clinic. This achievement represents a milestone in improving geometric and dosimetric accuracy, and by inference treatment outcomes, in cancer radiotherapy. PMID:24506591

A new method of small target detection based on neural network

NASA Astrophysics Data System (ADS)

Hu, Jing; Hu, Yongli; Lu, Xinxin

2018-02-01

The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

Four-dimensional dose distributions of step-and-shoot IMRT delivered with real-time tumor tracking for patients with irregular breathing: Constant dose rate vs dose rate regulation

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

Yang Xiaocheng; Han-Oh, Sarah; Gui Minzhi

2012-09-15

Purpose: Dose-rate-regulated tracking (DRRT) is a tumor tracking strategy that programs the MLC to track the tumor under regular breathing and adapts to breathing irregularities during delivery using dose rate regulation. Constant-dose-rate tracking (CDRT) is a strategy that dynamically repositions the beam to account for intrafractional 3D target motion according to real-time information of target location obtained from an independent position monitoring system. The purpose of this study is to illustrate the differences in the effectiveness and delivery accuracy between these two tracking methods in the presence of breathing irregularities. Methods: Step-and-shoot IMRT plans optimized at a reference phase weremore » extended to remaining phases to generate 10-phased 4D-IMRT plans using segment aperture morphing (SAM) algorithm, where both tumor displacement and deformation were considered. A SAM-based 4D plan has been demonstrated to provide better plan quality than plans not considering target deformation. However, delivering such a plan requires preprogramming of the MLC aperture sequence. Deliveries of the 4D plans using DRRT and CDRT tracking approaches were simulated assuming the breathing period is either shorter or longer than the planning day, for 4 IMRT cases: two lung and two pancreatic cases with maximum GTV centroid motion greater than 1 cm were selected. In DRRT, dose rate was regulated to speed up or slow down delivery as needed such that each planned segment is delivered at the planned breathing phase. In CDRT, MLC is separately controlled to follow the tumor motion, but dose rate was kept constant. In addition to breathing period change, effect of breathing amplitude variation on target and critical tissue dose distribution is also evaluated. Results: Delivery of preprogrammed 4D plans by the CDRT method resulted in an average of 5% increase in target dose and noticeable increase in organs at risk (OAR) dose when patient breathing is either 10% faster or slower than the planning day. In contrast, DRRT method showed less than 1% reduction in target dose and no noticeable change in OAR dose under the same breathing period irregularities. When {+-}20% variation of target motion amplitude was present as breathing irregularity, the two delivery methods show compatible plan quality if the dose distribution of CDRT delivery is renormalized. Conclusions: Delivery of 4D-IMRT treatment plans, stemmed from 3D step-and-shoot IMRT and preprogrammed using SAM algorithm, is simulated for two dynamic MLC-based real-time tumor tracking strategies: with and without dose-rate regulation. Comparison of cumulative dose distribution indicates that the preprogrammed 4D plan is more accurately and efficiently conformed using the DRRT strategy, as it compensates the interplay between patient breathing irregularity and tracking delivery without compromising the segment-weight modulation.« less

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

Electromagnetic guided couch and multileaf collimator tracking on a TrueBeam accelerator

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

Hansen, Rune; Ravkilde, Thomas; Worm, Esben Schjødt

2016-05-15

Purpose: Couch and MLC tracking are two promising methods for real-time motion compensation during radiation therapy. So far, couch and MLC tracking experiments have mainly been performed by different research groups, and no direct comparison of couch and MLC tracking of volumetric modulated arc therapy (VMAT) plans has been published. The Varian TrueBeam 2.0 accelerator includes a prototype tracking system with selectable couch or MLC compensation. This study provides a direct comparison of the two tracking types with an otherwise identical setup. Methods: Several experiments were performed to characterize the geometric and dosimetric performance of electromagnetic guided couch and MLCmore » tracking on a TrueBeam accelerator equipped with a Millennium MLC. The tracking system latency was determined without motion prediction as the time lag between sinusoidal target motion and the compensating motion of the couch or MLC as recorded by continuous MV portal imaging. The geometric and dosimetric tracking accuracies were measured in tracking experiments with motion phantoms that reproduced four prostate and four lung tumor trajectories. The geometric tracking error in beam’s eye view was determined as the distance between an embedded gold marker and a circular MLC aperture in continuous MV images. The dosimetric tracking error was quantified as the measured 2%/2 mm gamma failure rate of a low and a high modulation VMAT plan delivered with the eight motion trajectories using a static dose distribution as reference. Results: The MLC tracking latency was approximately 146 ms for all sinusoidal period lengths while the couch tracking latency increased from 187 to 246 ms with decreasing period length due to limitations in the couch acceleration. The mean root-mean-square geometric error was 0.80 mm (couch tracking), 0.52 mm (MLC tracking), and 2.75 mm (no tracking) parallel to the MLC leaves and 0.66 mm (couch), 1.14 mm (MLC), and 2.41 mm (no tracking) perpendicular to the leaves. The motion-induced gamma failure rate was in mean 0.1% (couch tracking), 8.1% (MLC tracking), and 30.4% (no tracking) for prostate motion and 2.9% (couch), 2.4% (MLC), and 41.2% (no tracking) for lung tumor motion. The residual tracking errors were mainly caused by inadequate adaptation to fast lung tumor motion for couch tracking and to prostate motion perpendicular to the MLC leaves for MLC tracking. Conclusions: Couch and MLC tracking markedly improved the geometric and dosimetric accuracies of VMAT delivery. However, the two tracking types have different strengths and weaknesses. While couch tracking can correct perfectly for slowly moving targets such as the prostate, MLC tracking may have considerably larger dose errors for persistent target shift perpendicular to the MLC leaves. Advantages of MLC tracking include faster dynamics with better adaptation to fast moving targets, the avoidance of moving the patient, and the potential to track target rotations and deformations.« less

Two-Camera Acquisition and Tracking of a Flying Target

NASA Technical Reports Server (NTRS)

Biswas, Abhijit; Assad, Christopher; Kovalik, Joseph M.; Pain, Bedabrata; Wrigley, Chris J.; Twiss, Peter

2008-01-01

A method and apparatus have been developed to solve the problem of automated acquisition and tracking, from a location on the ground, of a luminous moving target in the sky. The method involves the use of two electronic cameras: (1) a stationary camera having a wide field of view, positioned and oriented to image the entire sky; and (2) a camera that has a much narrower field of view (a few degrees wide) and is mounted on a two-axis gimbal. The wide-field-of-view stationary camera is used to initially identify the target against the background sky. So that the approximate position of the target can be determined, pixel locations on the image-detector plane in the stationary camera are calibrated with respect to azimuth and elevation. The approximate target position is used to initially aim the gimballed narrow-field-of-view camera in the approximate direction of the target. Next, the narrow-field-of view camera locks onto the target image, and thereafter the gimbals are actuated as needed to maintain lock and thereby track the target with precision greater than that attainable by use of the stationary camera.

Reading color barcodes using visual snakes.

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

Schaub, Hanspeter

2004-05-01

Statistical pressure snakes are used to track a mono-color target in an unstructured environment using a video camera. The report discusses an algorithm to extract a bar code signal that is embedded within the target. The target is assumed to be rectangular in shape, with the bar code printed in a slightly different saturation and value in HSV color space. Thus, the visual snake, which primarily weighs hue tracking errors, will not be deterred by the presence of the color bar codes in the target. The bar code is generate with the standard 3 of 9 method. Using this method,more » the numeric bar codes reveal if the target is right-side-up or up-side-down.« less

Covert enaction at work: Recording the continuous movements of visuospatial attention to visible or imagined targets by means of Steady-State Visual Evoked Potentials (SSVEPs).

PubMed

Gregori Grgič, Regina; Calore, Enrico; de'Sperati, Claudio

2016-01-01

Whereas overt visuospatial attention is customarily measured with eye tracking, covert attention is assessed by various methods. Here we exploited Steady-State Visual Evoked Potentials (SSVEPs) - the oscillatory responses of the visual cortex to incoming flickering stimuli - to record the movements of covert visuospatial attention in a way operatively similar to eye tracking (attention tracking), which allowed us to compare motion observation and motion extrapolation with and without eye movements. Observers fixated a central dot and covertly tracked a target oscillating horizontally and sinusoidally. In the background, the left and the right halves of the screen flickered at two different frequencies, generating two SSVEPs in occipital regions whose size varied reciprocally as observers attended to the moving target. The two signals were combined into a single quantity that was modulated at the target frequency in a quasi-sinusoidal way, often clearly visible in single trials. The modulation continued almost unchanged when the target was switched off and observers mentally extrapolated its motion in imagery, and also when observers pointed their finger at the moving target during covert tracking, or imagined doing so. The amplitude of modulation during covert tracking was ∼25-30% of that measured when observers followed the target with their eyes. We used 4 electrodes in parieto-occipital areas, but similar results were achieved with a single electrode in Oz. In a second experiment we tested ramp and step motion. During overt tracking, SSVEPs were remarkably accurate, showing both saccadic-like and smooth pursuit-like modulations of cortical responsiveness, although during covert tracking the modulation deteriorated. Covert tracking was better with sinusoidal motion than ramp motion, and better with moving targets than stationary ones. The clear modulation of cortical responsiveness recorded during both overt and covert tracking, identical for motion observation and motion extrapolation, suggests to include covert attention movements in enactive theories of mental imagery. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar.

PubMed

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-09-09

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar's estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method.

SU-E-J-188: Theoretical Estimation of Margin Necessary for Markerless Motion Tracking

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

Patel, R; Block, A; Harkenrider, M

2015-06-15

Purpose: To estimate the margin necessary to adequately cover the target using markerless motion tracking (MMT) of lung lesions given the uncertainty in tracking and the size of the target. Methods: Simulations were developed in Matlab to determine the effect of tumor size and tracking uncertainty on the margin necessary to achieve adequate coverage of the target. For simplicity, the lung tumor was approximated by a circle on a 2D radiograph. The tumor was varied in size from a diameter of 0.1 − 30 mm in increments of 0.1 mm. From our previous studies using dual energy markerless motion tracking,more » we estimated tracking uncertainties in x and y to have a standard deviation of 2 mm. A Gaussian was used to simulate the deviation between the tracked location and true target location. For each size tumor, 100,000 deviations were randomly generated, the margin necessary to achieve at least 95% coverage 95% of the time was recorded. Additional simulations were run for varying uncertainties to demonstrate the effect of the tracking accuracy on the margin size. Results: The simulations showed an inverse relationship between tumor size and margin necessary to achieve 95% coverage 95% of the time using the MMT technique. The margin decreased exponentially with target size. An increase in tracking accuracy expectedly showed a decrease in margin size as well. Conclusion: In our clinic a 5 mm expansion of the internal target volume (ITV) is used to define the planning target volume (PTV). These simulations show that for tracking accuracies in x and y better than 2 mm, the margin required is less than 5 mm. This simple simulation can provide physicians with a guideline estimation for the margin necessary for use of MMT clinically based on the accuracy of their tracking and the size of the tumor.« less

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

PubMed

Lu, Xiaodong; Xie, Yuting; Zhou, Jun

2018-05-27

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

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.

Detection and Tracking of Moving Targets Behind Cluttered Environments Using Compressive Sensing

NASA Astrophysics Data System (ADS)

Dang, Vinh Quang

Detection and tracking of moving targets (target's motion, vibration, etc.) in cluttered environments have been receiving much attention in numerous applications, such as disaster search-and-rescue, law enforcement, urban warfare, etc. One of the popular techniques is the use of stepped frequency continuous wave radar due to its low cost and complexity. However, the stepped frequency radar suffers from long data acquisition time. This dissertation focuses on detection and tracking of moving targets and vibration rates of stationary targets behind cluttered medium such as wall using stepped frequency radar enhanced by compressive sensing. The application of compressive sensing enables the reconstruction of the target space using fewer random frequencies, which decreases the acquisition time. Hardware-accelerated parallelization on GPU is investigated for the Orthogonal Matching Pursuit reconstruction algorithm. For simulation purpose, two hybrid methods have been developed to calculate the scattered fields from the targets through the wall approaching the antenna system, and to convert the incoming fields into voltage signals at terminals of the receive antenna. The first method is developed based on the plane wave spectrum approach for calculating the scattered fields of targets behind the wall. The method uses Fast Multiple Method (FMM) to calculate scattered fields on a particular source plane, decomposes them into plane wave components, and propagates the plane wave spectrum through the wall by integrating wall transmission coefficients before constructing the fields on a desired observation plane. The second method allows one to calculate the complex output voltage at terminals of a receiving antenna which fully takes into account the antenna effects. This method adopts the concept of complex antenna factor in Electromagnetic Compatibility (EMC) community for its calculation.

TH-AB-202-05: BEST IN PHYSICS (JOINT IMAGING-THERAPY): First Online Ultrasound-Guided MLC Tracking for Real-Time Motion Compensation in Radiotherapy

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

Ipsen, S; Bruder, R; Schweikard, A

Purpose: While MLC tracking has been successfully used for motion compensation of moving targets, current real-time target localization methods rely on correlation models with x-ray imaging or implanted electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging yields volumetric data in real-time (4D) without ionizing radiation. We report the first results of online 4D ultrasound-guided MLC tracking in a phantom. Methods: A real-time tracking framework was installed on a 4D ultrasound station (Vivid7 dimension, GE) and used to detect a 2mm spherical lead marker inside a water tank. The volumetric frame rate was 21.3Hz (47ms). The marker wasmore » rigidly attached to a motion stage programmed to reproduce nine tumor trajectories (five prostate, four lung). The 3D marker position from ultrasound was used for real-time MLC aperture adaption. The tracking system latency was measured and compensated by prediction for lung trajectories. To measure geometric accuracy, anterior and lateral conformal fields with 10cm circular aperture were delivered for each trajectory. The tracking error was measured as the difference between marker position and MLC aperture in continuous portal imaging. For dosimetric evaluation, 358° VMAT fields were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using a 3%/3 mm γ-test. Results: The tracking system latency was 170ms. The mean root-mean-square tracking error was 1.01mm (0.75mm prostate, 1.33mm lung). Tracking reduced the mean γ-failure rate from 13.9% to 4.6% for prostate and from 21.8% to 0.6% for lung with high-modulation VMAT plans and from 5% (prostate) and 18% (lung) to 0% with low modulation. Conclusion: Real-time ultrasound tracking was successfully integrated with MLC tracking for the first time and showed similar accuracy and latency as other methods while holding the potential to measure target motion non-invasively. SI was supported by the Graduate School for Computing in Medicine and Life Science, German Excellence Initiative [grant DFG GSC 235/1].« less

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%.

Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy.

PubMed

Morel, Paul; Wu, Xiaodong; Blin, Guillaume; Vialette, Stéphane; Flynn, Ryan; Hyer, Daniel; Wang, Dongxu

2015-01-01

This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution. The method proposed in this study adapts the weight (MU) of the delivering pencil beam to that of the target spot; it will actually hit during patient/target motion. The target spot that a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D) CT. After the adapted delivery, the required total weight [Monitor Unit (MU)] for this target spot is then subtracted from the planned value. With continuous patient motion and continuous spot scanning, the planned doses to all target spots will eventually be all fulfilled. In a proof-of-principle test, a lung case was presented with realistic temporal and motion parameters; the resultant dose distribution using spot weight adaptation was compared to that without using this method. The impact of the real-time patient/target position tracking or prediction was also investigated. For moderate motion (i.e., mean amplitude 0.5 cm), D95% to the planning target volume (PTV) was only 81.5% of the prescription (RX) dose; with spot weight adaptation PTV D95% achieves 97.7% RX. For large motion amplitude (i.e., 1.5 cm), without spot weight adaptation PTV D95% is only 42.9% of RX; with spot weight adaptation, PTV D95% achieves 97.7% RX. Larger errors in patient/target position tracking or prediction led to worse final target coverage; an error of 3 mm or smaller in patient/target position tracking is preferred. The proposed spot weight adaptation method was able to deliver the planned dose distribution and maintain target coverage when patient motion was involved. The successful implementation of this method would rely on accurate monitoring or prediction of patient/target motion.

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.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Black, Jonathan T.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored, circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retroreflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Videogrammetry Using Projected Circular Targets: Proof-of-Concept Test

NASA Technical Reports Server (NTRS)

Black, Jonathan T.; Pappa, Richard S.

2003-01-01

Videogrammetry is the science of calculating 3D object coordinates as a function of time from image sequences. It expands the method of photogrammetry to multiple time steps enabling the object to be characterized dynamically. Photogrammetry achieves the greatest accuracy with high contrast, solid-colored circular targets. The high contrast is most often effected using retro-reflective targets attached to the measurement article. Knowledge of the location of each target allows those points to be tracked in a sequence of images, thus yielding dynamic characterization of the overall object. For ultra-lightweight and inflatable gossamer structures (e.g. solar sails, inflatable antennae, sun shields, etc.) where it may be desirable to avoid physically attaching retro-targets, a high-density grid of projected circular targets - called dot projection - is a viable alternative. Over time the object changes shape or position independently of the dots. Dynamic behavior, such as deployment or vibration, can be characterized by tracking the overall 3D shape of the object instead of tracking specific object points. To develop this method, an oscillating rigid object was measured using both retro- reflective targets and dot projection. This paper details these tests, compares the results, and discusses the overall accuracy of dot projection videogrammetry.

Performance of two quantitative PCR methods for microbial source tracking of human sewage and implications for microbial risk assessment in recreational waters

EPA Science Inventory

Before new, rapid quantitative PCR (qPCR) methods for recreational water quality assessment and microbial source tracking (MST) can be useful in a regulatory context, an understanding of the ability of the method to detect a DNA target (marker) when the contaminant soure has been...

Bias estimation for moving optical sensor measurements with targets of opportunity

NASA Astrophysics Data System (ADS)

Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

2014-06-01

Integration of space based sensors into a Ballistic Missile Defense System (BMDS) allows for detection and tracking of threats over a larger area than ground based sensors [1]. This paper examines the effect of sensor bias error on the tracking quality of a Space Tracking and Surveillance System (STSS) for the highly non-linear problem of tracking a ballistic missile. The STSS constellation consists of two or more satellites (on known trajectories) for tracking ballistic targets. Each satellite is equipped with an IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant or slowly varying bias error present in each sensor's line of sight measurements. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. The measurements provided by these sensors are assumed time-coincident (synchronous) and perfectly associated. The line of sight (LOS) measurements from the sensors can be fused into measurements which are the Cartesian target position, i.e., linear in the target state. We evaluate the Cramér-Rao Lower Bound (CRLB) on the covariance of the bias estimates, which serves as a quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the (unknown) trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

Use of fluorescent ANTS to examine the BBB-permeability of polysaccharide

PubMed Central

Christopher, Kevin; Makani, Vishruti; Judy, Wesley; Lee, Erica; Chiaia, Nicolas; Kim, Dong Shik; Park, Joshua

2015-01-01

Recently, some polysaccharides showed therapeutic potentials for the treatment of neurodegenerative diseases while the most important property, their permeability to the blood brain barrier (BBB) that sheathes the brain and spinal cord, is not yet determined. The determination has been delayed by the difficulty in tracking a target polysaccharide among endogenous polysaccharides in animal. We developed an easy way to examine the BBB-permeability and, possibly, tissue distribution of a target polysaccharide in animal. We tagged a polysaccharide with fluorescent 8-aminonaphthalene-1,3,6-trisulfonic acid disodium salt (ANTS) for tracking. We also developed a simple method to separate ANTS-tagged polysaccharide from unconjugated free ANTS using 75% ethanol. After ANTS-polysaccharide was intra-nasally administered into animals, we could quantify the amounts of ANTS-polysaccharide in the brain and the serum by fluorocytometry. We could also separate free ANTS-polysaccharide from serum proteins using trichloroacetic acid (TCA) and 75% ethanol. Our method will help to track a polysaccharide in animal easily. • ANTS-labeling is less tedious than but as powerful as radiolabeling for tracking a target polysaccharide in animal. • Our simple method can separate structurally intact ANTS-polysaccharide from animal serum and tissues. • This method is good for the fluorometry-based measurement of ANTS-conjugated macromolecules in tissues. PMID:25914873

A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images.

PubMed

Yao, Libo; Liu, Yong; He, You

2018-06-22

The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search.

PubMed

Liu, Meiqin; Zhang, Duo; Zhang, Senlin; Zhang, Qunfei

2017-12-04

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

PubMed Central

Zhang, Senlin; Zhang, Qunfei

2017-01-01

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme. PMID:29207541

TH-AB-BRA-08: Simulated Tumor Tracking in An MRI Linac for Lung Tumor Lesions Using the Monaco Treatment Planning System

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

Al-Ward, S; Kim, A; McCann, C

2016-06-15

Purpose: To simulate tumor tracking in an Elekta MRI-linac (MRL) and to compare this tracking method with our current ITV approach in terms of OAR sparing for lung cancer patients. Methods: Five SABR-NSCLC patients with central lung tumors were selected for reasons of potential enhancement of tumor-tissue delineation using MRI. The Monaco TPS was used to compare the current clinical ITV approach to a simulated, novel tracking method which used a 7MV MRL beam in the presence of an orthogonal 1.5 T magnetic field (4D-MRL method). In the simulated tracking scenario, achieved using the virtual couch shift (VCS), the PTVmore » was defined using an isotropic 5mm margin applied to the GTV of each phase, as acquired from an 8-phase amplitude-binned 4DCT. These VCS plans were optimized and weighted on each phase. The dose weighting was performed using the patient-specific breathing traces. The doses were accumulated on the inhale phase. The two methods were compared by assessing the OAR DVHs. Results: The 4D-MRL method resulted in a reduced target volume (by an average of 29% over all patients). The benefits of using an MRL tracking system depended on the tumor motion amplitude and the relative OAR motion (ROM) to the target. The reduction in mean doses to parallel organs was up to 3 Gy for the heart and 2.1 Gy for the lung. The reductions in maximum doses to serial organs were up to 9.4 Gy, 5.6 Gy, and 8.7 Gy for the esophagus, spinal cord, and the trachea, respectively. Serial organs benefited from MRL tracking when the ROM was ≥ 0.3 cm despite small tumor motion amplitude in some cases. Conclusions: This work demonstrated the potential benefit for an MRL tracking system to spare OARs in SABR-NSCLC patients with central tumors. The benefits are embodied in the target volume reduction. This project was made possible with the financial support of Elekta.« less

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

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.

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight

PubMed Central

Guo, Siqiu; Zhang, Tao; Song, Yulong

2018-01-01

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios. PMID:29690610

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

PubMed

Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

2018-04-23

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

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.

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

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

Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system

PubMed Central

2010-01-01

Background Cell motility is a critical parameter in many physiological as well as pathophysiological processes. In time-lapse video microscopy, manual cell tracking remains the most common method of analyzing migratory behavior of cell populations. In addition to being labor-intensive, this method is susceptible to user-dependent errors regarding the selection of "representative" subsets of cells and manual determination of precise cell positions. Results We have quantitatively analyzed these error sources, demonstrating that manual cell tracking of pancreatic cancer cells lead to mis-calculation of migration rates of up to 410%. In order to provide for objective measurements of cell migration rates, we have employed multi-target tracking technologies commonly used in radar applications to develop fully automated cell identification and tracking system suitable for high throughput screening of video sequences of unstained living cells. Conclusion We demonstrate that our automatic multi target tracking system identifies cell objects, follows individual cells and computes migration rates with high precision, clearly outperforming manual procedures. PMID:20377897

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.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

PubMed Central

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-01-01

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

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.

Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

PubMed

Su, Housheng; Li, Zhenghao; Ye, Yanyan

2017-11-01

This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*

PubMed Central

Nakhmani, Arie; Tannenbaum, Allen

2012-01-01

Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a particle filter. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by particle filtering allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion. PMID:22506088

Fault-tolerant feature-based estimation of space debris rotational motion during active removal missions

NASA Astrophysics Data System (ADS)

Biondi, Gabriele; Mauro, Stefano; Pastorelli, Stefano; Sorli, Massimo

2018-05-01

One of the key functionalities required by an Active Debris Removal mission is the assessment of the target kinematics and inertial properties. Passive sensors, such as stereo cameras, are often included in the onboard instrumentation of a chaser spacecraft for capturing sequential photographs and for tracking features of the target surface. A plenty of methods, based on Kalman filtering, are available for the estimation of the target's state from feature positions; however, to guarantee the filter convergence, they typically require continuity of measurements and the capability of tracking a fixed set of pre-defined features of the object. These requirements clash with the actual tracking conditions: failures in feature detection often occur and the assumption of having some a-priori knowledge about the shape of the target could be restrictive in certain cases. The aim of the presented work is to propose a fault-tolerant alternative method for estimating the angular velocity and the relative magnitudes of the principal moments of inertia of the target. Raw data regarding the positions of the tracked features are processed to evaluate corrupted values of a 3-dimentional parameter which entirely describes the finite screw motion of the debris and which primarily is invariant on the particular set of considered features of the object. Missing values of the parameter are completely restored exploiting the typical periodicity of the rotational motion of an uncontrolled satellite: compressed sensing techniques, typically adopted for recovering images or for prognostic applications, are herein used in a completely original fashion for retrieving a kinematic signal that appears sparse in the frequency domain. Due to its invariance about the features, no assumptions are needed about the target's shape and continuity of the tracking. The obtained signal is useful for the indirect evaluation of an attitude signal that feeds an unscented Kalman filter for the estimation of the global rotational state of the target. The results of the computer simulations showed a good robustness of the method and its potential applicability for general motion conditions of the target.

Airborne target tracking algorithm against oppressive decoys in infrared imagery

NASA Astrophysics Data System (ADS)

Sun, Xiechang; Zhang, Tianxu

2009-10-01

This paper presents an approach for tracking airborne target against oppressive infrared decoys. Oppressive decoy lures infrared guided missile by its high infrared radiation. Traditional tracking algorithms have degraded stability even come to tracking failure when airborne target continuously throw out many decoys. The proposed approach first determines an adaptive tracking window. The center of the tracking window is set at a predicted target position which is computed based on uniform motion model. Different strategies are applied for determination of tracking window size according to target state. The image within tracking window is segmented and multi features of candidate targets are extracted. The most similar candidate target is associated to the tracking target by using a decision function, which calculates a weighted sum of normalized feature differences between two comparable targets. Integrated intensity ratio of association target and tracking target, and target centroid are examined to estimate target state in the presence of decoys. The tracking ability and robustness of proposed approach has been validated by processing available real-world and simulated infrared image sequences containing airborne targets and oppressive decoys.

Design and preliminary accuracy studies of an MRI-guided transrectal prostate intervention system.

PubMed

Krieger, Axel; Csoma, Csaba; Iordachital, Iulian I; Guion, Peter; Singh, Anurag K; Fichtinger, Gabor; Whitcomb, Louis L

2007-01-01

This paper reports a novel system for magnetic resonance imaging (MRI) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery. The system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration and subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders and mechanical scales. Targeting accuracy of the system is evaluated in prostate phantom experiments. Achieved targeting accuracy and procedure times were found to compare favorably with existing systems using passive and active tracking methods. Moreover, the portable design of the system using only standard MRI image sequences and minimal custom scanner interfacing allows the system to be easily used on different MRI scanners.

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.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

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.

The small low SNR target tracking using sparse representation information

NASA Astrophysics Data System (ADS)

Yin, Lifan; Zhang, Yiqun; Wang, Shuo; Sun, Chenggang

2017-11-01

Tracking small targets, such as missile warheads, from a remote distance is a difficult task since the targets are "points" which are similar to sensor's noise points. As a result, traditional tracking algorithms only use the information contained in point measurement, such as the position information and intensity information, as characteristics to identify targets from noise points. But in fact, as a result of the diffusion of photon, any small target is not a point in the focal plane array and it occupies an area which is larger than one sensor cell. So, if we can take the geometry characteristic into account as a new dimension of information, it will be of helpful in distinguishing targets from noise points. In this paper, we use a novel method named sparse representation (SR) to depict the geometry information of target intensity and define it as the SR information of target. Modeling the intensity spread and solving its SR coefficients, the SR information is represented by establishing its likelihood function. Further, the SR information likelihood is incorporated in the conventional Probability Hypothesis Density (PHD) filter algorithm with point measurement. To illustrate the different performances of algorithm with or without the SR information, the detection capability and estimation error have been compared through simulation. Results demonstrate the proposed method has higher estimation accuracy and probability of detecting target than the conventional algorithm without the SR information.

Evaluation of tracking accuracy of the CyberKnife system using a webcam and printed calibrated grid.

PubMed

Sumida, Iori; Shiomi, Hiroya; Higashinaka, Naokazu; Murashima, Yoshikazu; Miyamoto, Youichi; Yamazaki, Hideya; Mabuchi, Nobuhisa; Tsuda, Eimei; Ogawa, Kazuhiko

2016-03-08

Tracking accuracy for the CyberKnife's Synchrony system is commonly evaluated using a film-based verification method. We have evaluated a verification system that uses a webcam and a printed calibrated grid to verify tracking accuracy over three different motion patterns. A box with an attached printed calibrated grid and four fiducial markers was attached to the motion phantom. A target marker was positioned at the grid's center. The box was set up using the other three markers. Target tracking accuracy was evaluated under three conditions: 1) stationary; 2) sinusoidal motion with different amplitudes of 5, 10, 15, and 20 mm for the same cycle of 4 s and different cycles of 2, 4, 6, and 8 s with the same amplitude of 15 mm; and 3) irregular breathing patterns in six human volunteers breathing normally. Infrared markers were placed on the volunteers' abdomens, and their trajectories were used to simulate the target motion. All tests were performed with one-dimensional motion in craniocaudal direction. The webcam captured the grid's motion and a laser beam was used to simulate the CyberKnife's beam. Tracking error was defined as the difference between the grid's center and the laser beam. With a stationary target, mean tracking error was measured at 0.4 mm. For sinusoidal motion, tracking error was less than 2 mm for any amplitude and breathing cycle. For the volunteers' breathing patterns, the mean tracking error range was 0.78-1.67 mm. Therefore, accurate lesion targeting requires individual quality assurance for each patient.

Novel branching particle method for tracking

NASA Astrophysics Data System (ADS)

Ballantyne, David J.; Chan, Hubert Y.; Kouritzin, Michael A.

2000-07-01

Particle approximations are used to track a maneuvering signal given only a noisy, corrupted sequence of observations, as are encountered in target tracking and surveillance. The signal exhibits nonlinearities that preclude the optimal use of a Kalman filter. It obeys a stochastic differential equation (SDE) in a seven-dimensional state space, one dimension of which is a discrete maneuver type. The maneuver type switches as a Markov chain and each maneuver identifies a unique SDE for the propagation of the remaining six state parameters. Observations are constructed at discrete time intervals by projecting a polygon corresponding to the target state onto two dimensions and incorporating the noise. A new branching particle filter is introduced and compared with two existing particle filters. The filters simulate a large number of independent particles, each of which moves with the stochastic law of the target. Particles are weighted, redistributed, or branched, depending on the method of filtering, based on their accordance with the current observation from the sequence. Each filter provides an approximated probability distribution of the target state given all back observations. All three particle filters converge to the exact conditional distribution as the number of particles goes to infinity, but differ in how well they perform with a finite number of particles. Using the exactly known ground truth, the root-mean-squared (RMS) errors in target position of the estimated distributions from the three filters are compared. The relative tracking power of the filters is quantified for this target at varying sizes, particle counts, and levels of observation noise.

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.

Research on the method of precise alignment technology of atmospheric laser communication

NASA Astrophysics Data System (ADS)

Chen, Wen-jian; Gao, Wei; Duan, Yuan-yuan; Ma, Shi-wei; Chen, Jian

2016-10-01

Atmosphere laser communication takes advantage of laser as the carrier transmitting the voice, data, and image information in the atmosphere. Because of its high reliability, strong anti-interference ability, the advantages of easy installation, it has great potential and development space in the communications field. In the process of establish communication, the capture, targeting and tracking of the communication signal is the key technology. This paper introduce a method of targeting the signal spot in the process of atmosphere laser communication, which through the way of making analog signal addition and subtraction directly and normalized to obtain the target azimuth information to drive the servo system to achieve precise alignment of tracking.

Incorporating Target Priorities in the Sensor Tasking Reward Function

NASA Astrophysics Data System (ADS)

Gehly, S.; Bennett, J.

2016-09-01

Orbital debris tracking poses many challenges, most fundamentally the need to track a large number of objects from a limited number of sensors. The use of information theoretic sensor allocation provides a means to efficiently collect data on the multitarget system. An additional need of the community is the ability to specify target priorities, driven both by user needs and environmental factors such as collision warnings. This research develops a method to incorporate target priorities in the sensor tasking reward function, allowing for several applications in different tasking modes such as catalog maintenance, calibration, and collision monitoring. A set of numerical studies is included to demonstrate the functionality of the method.

Motor Practice Effects and Sensorimotor Integration in Adults who Stutter: Evidence from Visuomotor Tracking Performance

PubMed Central

Tumanova, Victoria; Zebrowski, Patricia M.; Goodman, Shawn S.; Arenas, Richard M.

2015-01-01

Purpose The purpose of this study was to utilize a visuomotor tracking task, with both the jaw and hand, to add to the literature regarding non-speech motor practice and sensorimotor integration (outside of auditory-motor integration domain) in adults who do (PWS) and do not (PWNS) stutter. Method Participants were 15 PWS (14 males, mean age = 27.0) and 15 PWNS (14 males, mean age = 27.2). Participants tracked both predictable and unpredictable moving targets separately with their jaw and their dominant hand, and accuracy was assessed by calculating phase and amplitude difference between the participant and the target. Motor practice effect was examined by comparing group performance over consecutive tracking trials of predictable conditions as well as within the first trial of same conditions. Results Results showed that compared to PWNS, PWS were not significantly different in matching either the phase (timing) or the amplitude of the target in both jaw and hand tracking of predictable and unpredictable targets. Further, there were no significant between-group differences in motor practice effects for either jaw or hand tracking. Both groups showed improved tracking accuracy within and between the trials. Conclusion Our findings revealed no statistically significant differences in non-speech motor practice effects and integration of sensorimotor feedback between PWS and PWNS, at least in the context of the visuomotor tracking tasks employed in the study. In general, both talker groups exhibited practice effects (i.e., increased accuracy over time) within and between tracking trials during both jaw and hand tracking. Implications for these results are discussed. PMID:25990027

Kernelized correlation tracking with long-term motion cues

NASA Astrophysics Data System (ADS)

Lv, Yunqiu; Liu, Kai; Cheng, Fei

2018-04-01

Robust object tracking is a challenging task in computer vision due to interruptions such as deformation, fast motion and especially, occlusion of tracked object. When occlusions occur, image data will be unreliable and is insufficient for the tracker to depict the object of interest. Therefore, most trackers are prone to fail under occlusion. In this paper, an occlusion judgement and handling method based on segmentation of the target is proposed. If the target is occluded, the speed and direction of it must be different from the objects occluding it. Hence, the value of motion features are emphasized. Considering the efficiency and robustness of Kernelized Correlation Filter Tracking (KCF), it is adopted as a pre-tracker to obtain a predicted position of the target. By analyzing long-term motion cues of objects around this position, the tracked object is labelled. Hence, occlusion could be detected easily. Experimental results suggest that our tracker achieves a favorable performance and effectively handles occlusion and drifting problems.

Characterization of single α-tracks by photoresist detection and AFM analysis-focus on biomedical science and technology

NASA Astrophysics Data System (ADS)

Falzone, Nadia; Myhra, Sverre; Chakalova, Radka; Hill, Mark A.; Thomson, James; Vallis, Katherine A.

2013-11-01

The interactions between energetic ions and biological and/or organic target materials have recently attracted theoretical and experimental attention, due to their implications for detector and device technologies, and for therapeutic applications. Most of the attention has focused on detection of the primary ionization tracks, and their effects, while recoil target atom tracks remain largely unexplored. Detection of tracks by a negative tone photoresist (SU-8), followed by standard development, in combination with analysis by atomic force microscopy, shows that both primary and recoil tracks are revealed as conical spikes, and can be characterized at high spatial resolution. The methodology has the potential to provide detailed information about single impact events, which may lead to more effective and informative detector technologies and advanced therapeutic procedures. In comparison with current characterization methods the advantageous features include: greater spatial resolution by an order of magnitude (20 nm) detection of single primary and associated recoil tracks; increased range of fluence (to 2.5 × 109 cm-2) sensitivity to impacts at grazing angle incidence; and better definition of the lateral interaction volume in target materials.

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 tracking in thermal images using adaptive particle filters with online random forest learning

NASA Astrophysics Data System (ADS)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

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.

Visual tracking using objectness-bounding box regression and correlation filters

NASA Astrophysics Data System (ADS)

Mbelwa, Jimmy T.; Zhao, Qingjie; Lu, Yao; Wang, Fasheng; Mbise, Mercy

2018-03-01

Visual tracking is a fundamental problem in computer vision with extensive application domains in surveillance and intelligent systems. Recently, correlation filter-based tracking methods have shown a great achievement in terms of robustness, accuracy, and speed. However, such methods have a problem of dealing with fast motion (FM), motion blur (MB), illumination variation (IV), and drifting caused by occlusion (OCC). To solve this problem, a tracking method that integrates objectness-bounding box regression (O-BBR) model and a scheme based on kernelized correlation filter (KCF) is proposed. The scheme based on KCF is used to improve the tracking performance of FM and MB. For handling drift problem caused by OCC and IV, we propose objectness proposals trained in bounding box regression as prior knowledge to provide candidates and background suppression. Finally, scheme KCF as a base tracker and O-BBR are fused to obtain a state of a target object. Extensive experimental comparisons of the developed tracking method with other state-of-the-art trackers are performed on some of the challenging video sequences. Experimental comparison results show that our proposed tracking method outperforms other state-of-the-art tracking methods in terms of effectiveness, accuracy, and robustness.

SU-E-J-160: 4D Dynamic Arc of Non-Modulated Variable-Dose-Rate Fields for Lung SBRT: A Feasibility Study.

PubMed

Yi, B; Yang, X; Niu, Y; Yu, C

2012-06-01

Conformal SBRT plans for Lung cancer with static gantry angles are ideal candidates for applying motion tracking because of: (1) better dosimetric conformity with reduced target margin and (2) easier and more faithful target tracking without intensity modulation. This work is to demonstrate that by delivering the target tracking during gantry rotation, we can significantly improve delivery efficiency without negatively affecting plan quality. A lung SBRT plan with static beams was created using CT images of the reference breathing phase. It is converted to an arc plan with variable dose rate followed by the conversion to a 4D plan with the segment aperture morphing (SAM) method (Gui 2010) with considerations of both target location and shape changes as depicted by the 4D CT. Gantry angle ranges were determined from the clinical monitor units, with the 22.2 MU/degree, which is chosen to maximize the dose rate. All segments of the dynamic 4D plan were merged into a single arc with variable dose rate. Each segment occupying 1/10 of the breathing period delivers 6.6 MUs at a dose rate of 1000 MU/min. Delivery time was measured and compared to the planned. The dose distributions of the single phase 3D plan and the arc 4D plan showed little difference. The delivered time for the 4D arc plan agreed with the calculated time, and is almost the same as delivering the 3D plan without target tracking. A 12 Gy treatment takes less than 2.5 min. The feasibility of a novel 4D delivery method where a 3D SBRT plan is converted into 4D arc delivery has been demonstrated. In addition to realizing the conventional target tracking benefits, our method further improves delivery efficiency, which is important for maintaining the geometric relationship between the target motion and the breathing surrogate during treatment. This study is supported by NIH_Grant_1R01CA133539-01 A2. © 2012 American Association of Physicists in Medicine.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes

NASA Astrophysics Data System (ADS)

Bjerre, Troels; Crijns, Sjoerd; Rosenschöld, Per Munck af; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-01

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes.

PubMed

Bjerre, Troels; Crijns, Sjoerd; af Rosenschöld, Per Munck; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-21

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Man-in-the-loop study of filtering in airborne head tracking tasks

NASA Technical Reports Server (NTRS)

Lifshitz, S.; Merhav, S. J.

1992-01-01

A human-factors study is conducted of problems due to vibrations during the use of a helmet-mounted display (HMD) in tracking tasks whose major factors are target motion and head vibration. A method is proposed for improving aiming accuracy in such tracking tasks on the basis of (1) head-motion measurement and (2) the shifting of the reticle in the HMD in ways that inhibit much of the involuntary apparent motion of the reticle, relative to the target, and the nonvoluntary motion of the teleoperated device. The HMD inherently furnishes the visual feedback required by this scheme.

Research on infrared dim-point target detection and tracking under sea-sky-line complex background

NASA Astrophysics Data System (ADS)

Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

2011-08-01

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

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.

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.

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

Automatically Detect and Track Multiple Fish Swimming in Shallow Water with Frequent Occlusion

PubMed Central

Qian, Zhi-Ming; Cheng, Xi En; Chen, Yan Qiu

2014-01-01

Due to its universality, swarm behavior in nature attracts much attention of scientists from many fields. Fish schools are examples of biological communities that demonstrate swarm behavior. The detection and tracking of fish in a school are of important significance for the quantitative research on swarm behavior. However, different from other biological communities, there are three problems in the detection and tracking of fish school, that is, variable appearances, complex motion and frequent occlusion. To solve these problems, we propose an effective method of fish detection and tracking. In this method, first, the fish head region is positioned through extremum detection and ellipse fitting; second, The Kalman filtering and feature matching are used to track the target in complex motion; finally, according to the feature information obtained by the detection and tracking, the tracking problems caused by frequent occlusion are processed through trajectory linking. We apply this method to track swimming fish school of different densities. The experimental results show that the proposed method is both accurate and reliable. PMID:25207811

A comparison of error bounds for a nonlinear tracking system with detection probability Pd < 1.

PubMed

Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin

2012-12-14

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds.

A Comparison of Error Bounds for a Nonlinear Tracking System with Detection Probability Pd < 1

PubMed Central

Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin

2012-01-01

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds. PMID:23242274

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.

Evaluation of tracking accuracy of the CyberKnife system using a webcam and printed calibrated grid

PubMed Central

Shiomi, Hiroya; Higashinaka, Naokazu; Murashima, Yoshikazu; Miyamoto, Youichi; Yamazaki, Hideya; Mabuchi, Nobuhisa; Tsuda, Eimei; Ogawa, Kazuhiko

2016-01-01

Tracking accuracy for the CyberKnife's Synchrony system is commonly evaluated using a film‐based verification method. We have evaluated a verification system that uses a webcam and a printed calibrated grid to verify tracking accuracy over three different motion patterns. A box with an attached printed calibrated grid and four fiducial markers was attached to the motion phantom. A target marker was positioned at the grid's center. The box was set up using the other three markers. Target tracking accuracy was evaluated under three conditions: 1) stationary; 2) sinusoidal motion with different amplitudes of 5, 10, 15, and 20 mm for the same cycle of 4 s and different cycles of 2, 4, 6, and 8 s with the same amplitude of 15 mm; and 3) irregular breathing patterns in six human volunteers breathing normally. Infrared markers were placed on the volunteers’ abdomens, and their trajectories were used to simulate the target motion. All tests were performed with one‐dimensional motion in craniocaudal direction. The webcam captured the grid's motion and a laser beam was used to simulate the CyberKnife's beam. Tracking error was defined as the difference between the grid's center and the laser beam. With a stationary target, mean tracking error was measured at 0.4 mm. For sinusoidal motion, tracking error was less than 2 mm for any amplitude and breathing cycle. For the volunteers’ breathing patterns, the mean tracking error range was 0.78‐1.67 mm. Therefore, accurate lesion targeting requires individual quality assurance for each patient. PACS number(s): 87.55.D‐, 87.55.km, 87.55.Qr, 87.56.Fc PMID:27074474

An automated method for the evaluation of the pointing accuracy of sun-tracking devices

NASA Astrophysics Data System (ADS)

Baumgartner, Dietmar J.; Rieder, Harald E.; Pötzi, Werner; Freislich, Heinrich; Strutzmann, Heinz

2016-04-01

The accuracy of measurements of solar radiation (direct and diffuse radiation) depends significantly on the accuracy of the operational sun-tracking device. Thus rigid targets for instrument performance and operation are specified for international monitoring networks, such as e.g., the Baseline Surface Radiation Network (BSRN) operating under the auspices of the World Climate Research Program (WCRP). Sun-tracking devices fulfilling these accuracy targets are available from various instrument manufacturers, however none of the commercially available systems comprises a secondary accuracy control system, allowing platform operators to independently validate the pointing accuracy of sun-tracking sensors during operation. Here we present KSO-STREAMS (KSO-SunTRackEr Accuracy Monitoring System), a fully automated, system independent and cost-effective method for evaluating the pointing accuracy of sun-tracking devices. We detail the monitoring system setup, its design and specifications and results from its application to the sun-tracking system operated at the Austrian RADiation network (ARAD) site Kanzelhöhe Observatory (KSO). Results from KSO-STREAMS (for mid-March to mid-June 2015) show that the tracking accuracy of the device operated at KSO lies well within BSRN specifications (i.e. 0.1 degree accuracy). We contrast results during clear-sky and partly cloudy conditions documenting sun-tracking performance at manufacturer specified accuracies for active tracking (0.02 degrees) and highlight accuracies achieved during passive tracking i.e. periods with less than 300 W m-2 direct radiation. Furthermore we detail limitations to tracking surveillance during overcast conditions and periods of partial solar limb coverage by clouds.

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.

An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration.

PubMed

Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Zhao, Zishu; Li, Yuankun

2017-07-26

In this paper, we propose a novel automatic multi-target registration framework for non-planar infrared-visible videos. Previous approaches usually analyzed multiple targets together and then estimated a global homography for the whole scene, however, these cannot achieve precise multi-target registration when the scenes are non-planar. Our framework is devoted to solving the problem using feature matching and multi-target tracking. The key idea is to analyze and register each target independently. We present a fast and robust feature matching strategy, where only the features on the corresponding foreground pairs are matched. Besides, new reservoirs based on the Gaussian criterion are created for all targets, and a multi-target tracking method is adopted to determine the relationships between the reservoirs and foreground blobs. With the matches in the corresponding reservoir, the homography of each target is computed according to its moving state. We tested our framework on both public near-planar and non-planar datasets. The results demonstrate that the proposed framework outperforms the state-of-the-art global registration method and the manual global registration matrix in all tested datasets.

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.

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

Towards large scale multi-target tracking

NASA Astrophysics Data System (ADS)

Vo, Ba-Ngu; Vo, Ba-Tuong; Reuter, Stephan; Lam, Quang; Dietmayer, Klaus

2014-06-01

Multi-target tracking is intrinsically an NP-hard problem and the complexity of multi-target tracking solutions usually do not scale gracefully with problem size. Multi-target tracking for on-line applications involving a large number of targets is extremely challenging. This article demonstrates the capability of the random finite set approach to provide large scale multi-target tracking algorithms. In particular it is shown that an approximate filter known as the labeled multi-Bernoulli filter can simultaneously track one thousand five hundred targets in clutter on a standard laptop computer.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Sequential bearings-only-tracking initiation with particle filtering method.

PubMed

Liu, Bin; Hao, Chengpeng

2013-01-01

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.

A Universal Method for Fishing Target Proteins from Mixtures of Biomolecules using Isothermal Titration Calorimetry

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

Zhou, X.; Sun, Q; Kini, R

2008-01-01

The most challenging tasks in biology include the identification of (1) the orphan receptor for a ligand, (2) the ligand for an orphan receptor protein, and (3) the target protein(s) for a given drug or a lead compound that are critical for the pharmacological or side effects. At present, several approaches are available, including cell- or animal-based assays, affinity labeling, solid-phase binding assays, surface plasmon resonance, and nuclear magnetic resonance. Most of these techniques are not easy to apply when the target protein is unknown and the compound is not amenable to labeling, chemical modification, or immobilization. Here we demonstratemore » a new universal method for fishing orphan target proteins from a complex mixture of biomolecules using isothermal titration calorimetry (ITC) as a tracking tool. We took snake venom, a crude mixture of several hundred proteins/peptides, as a model to demonstrate our proposed ITC method in tracking the isolation and purification of two distinct target proteins, a major component and a minor component. Identities of fished out target proteins were confirmed by amino acid sequencing and inhibition assays. This method has the potential to make a significant advancement in the area of identifying orphan target proteins and inhibitor screening in drug discovery and characterization.« less

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks

PubMed Central

Alzarok, Hamza; Fletcher, Simon; Longstaff, Andrew P.

2017-01-01

The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot with an overall tracking error of 0.25 mm. Also, the effectiveness of CRCHT technique in saving up to 60% of the overall time required for image processing. PMID:28067860

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.

Tracking moving targets behind a scattering medium via speckle correlation.

PubMed

Guo, Chengfei; Liu, Jietao; Wu, Tengfei; Zhu, Lei; Shao, Xiaopeng

2018-02-01

Tracking moving targets behind a scattering medium is a challenge, and it has many important applications in various fields. Owing to the multiple scattering, instead of the object image, only a random speckle pattern can be received on the camera when light is passing through highly scattering layers. Significantly, an important feature of a speckle pattern has been found, and it showed the target information can be derived from the speckle correlation. In this work, inspired by the notions used in computer vision and deformation detection, by specific simulations and experiments, we demonstrate a simple object tracking method, in which by using the speckle correlation, the movement of a hidden object can be tracked in the lateral direction and axial direction. In addition, the rotation state of the moving target can also be recognized by utilizing the autocorrelation of a speckle. This work will be beneficial for biomedical applications in the fields of quantitative analysis of the working mechanisms of a micro-object and the acquisition of dynamical information of the micro-object motion.

Ultrasonic ranging for the oculometer

NASA Technical Reports Server (NTRS)

Guy, W. J.

1981-01-01

Ultrasonic tracking techniques are investigated for an oculometer. Two methods are reported in detail. The first is based on measurements of time from the start of a transmit burst to a received echo. Knowing the sound velocity, distance can be calculated. In the second method, a continuous signal is transmitted. Target movement causes phase shifting of the echo. By accumulating these phase shifts, tracking from a set point can be achieved. Both systems have problems with contoured targets, but work well on flat plates and the back of a human head. Also briefly reported is an evaluation of an ultrasonic ranging system. Interface circuits make this system compatible with the echo time design. While the system is consistently accurate, it has a beam too narrow for oculometer use. Finally, comments are provided on a tracking system using the Doppler frequency shift to give range data.

Automatic Association of Chats and Video Tracks for Activity Learning and Recognition in Aerial Video Surveillance

PubMed Central

Hammoud, Riad I.; Sahin, Cem S.; Blasch, Erik P.; Rhodes, Bradley J.; Wang, Tao

2014-01-01

We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets of interest (TOIs) by movement type and geolocation; and (3) a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV). VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports. PMID:25340453

Automatic association of chats and video tracks for activity learning and recognition in aerial video surveillance.

PubMed

Hammoud, Riad I; Sahin, Cem S; Blasch, Erik P; Rhodes, Bradley J; Wang, Tao

2014-10-22

We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets of interest (TOIs) by movement type and geolocation; and (3) a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV). VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat Sensors 2014, 14 19844 messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports.

The first clinical implementation of electromagnetic transponder-guided MLC tracking.

PubMed

Keall, Paul J; Colvill, Emma; O'Brien, Ricky; Ng, Jin Aun; Poulsen, Per Rugaard; Eade, Thomas; Kneebone, Andrew; Booth, Jeremy T

2014-02-01

We report on the clinical process, quality assurance, and geometric and dosimetric results of the first clinical implementation of electromagnetic transponder-guided MLC tracking which occurred on 28 November 2013 at the Northern Sydney Cancer Centre. An electromagnetic transponder-based positioning system (Calypso) was modified to send the target position output to in-house-developed MLC tracking code, which adjusts the leaf positions to optimally align the treatment beam with the real-time target position. Clinical process and quality assurance procedures were developed and performed. The first clinical implementation of electromagnetic transponder-guided MLC tracking was for a prostate cancer patient being treated with dual-arc VMAT (RapidArc). For the first fraction of the first patient treatment of electromagnetic transponder-guided MLC tracking we recorded the in-room time and transponder positions, and performed dose reconstruction to estimate the delivered dose and also the dose received had MLC tracking not been used. The total in-room time was 21 min with 2 min of beam delivery. No additional time was needed for MLC tracking and there were no beam holds. The average prostate position from the initial setup was 1.2 mm, mostly an anterior shift. Dose reconstruction analysis of the delivered dose with MLC tracking showed similar isodose and target dose volume histograms to the planned treatment and a 4.6% increase in the fractional rectal V60. Dose reconstruction without motion compensation showed a 30% increase in the fractional rectal V60 from that planned, even for the small motion. The real-time beam-target correction method, electromagnetic transponder-guided MLC tracking, has been translated to the clinic. This achievement represents a milestone in improving geometric and dosimetric accuracy, and by inference treatment outcomes, in cancer radiotherapy.

Interacting multiple model forward filtering and backward smoothing for maneuvering target tracking

NASA Astrophysics Data System (ADS)

Nandakumaran, N.; Sutharsan, S.; Tharmarasa, R.; Lang, Tom; McDonald, Mike; Kirubarajan, T.

2009-08-01

The Interacting Multiple Model (IMM) estimator has been proven to be effective in tracking agile targets. Smoothing or retrodiction, which uses measurements beyond the current estimation time, provides better estimates of target states. Various methods have been proposed for multiple model smoothing in the literature. In this paper, a new smoothing method, which involves forward filtering followed by backward smoothing while maintaining the fundamental spirit of the IMM, is proposed. The forward filtering is performed using the standard IMM recursion, while the backward smoothing is performed using a novel interacting smoothing recursion. This backward recursion mimics the IMM estimator in the backward direction, where each mode conditioned smoother uses standard Kalman smoothing recursion. Resulting algorithm provides improved but delayed estimates of target states. Simulation studies are performed to demonstrate the improved performance with a maneuvering target scenario. The comparison with existing methods confirms the improved smoothing accuracy. This improvement results from avoiding the augmented state vector used by other algorithms. In addition, the new technique to account for model switching in smoothing is a key in improving the performance.

A real-time dynamic-MLC control algorithm for delivering IMRT to targets undergoing 2D rigid motion in the beam's eye view.

PubMed

McMahon, Ryan; Berbeco, Ross; Nishioka, Seiko; Ishikawa, Masayori; Papiez, Lech

2008-09-01

An MLC control algorithm for delivering intensity modulated radiation therapy (IMRT) to targets that are undergoing two-dimensional (2D) rigid motion in the beam's eye view (BEV) is presented. The goal of this method is to deliver 3D-derived fluence maps over a moving patient anatomy. Target motion measured prior to delivery is first used to design a set of planned dynamic-MLC (DMLC) sliding-window leaf trajectories. During actual delivery, the algorithm relies on real-time feedback to compensate for target motion that does not agree with the motion measured during planning. The methodology is based on an existing one-dimensional (ID) algorithm that uses on-the-fly intensity calculations to appropriately adjust the DMLC leaf trajectories in real-time during exposure delivery [McMahon et al., Med. Phys. 34, 3211-3223 (2007)]. To extend the 1D algorithm's application to 2D target motion, a real-time leaf-pair shifting mechanism has been developed. Target motion that is orthogonal to leaf travel is tracked by appropriately shifting the positions of all MLC leaves. The performance of the tracking algorithm was tested for a single beam of a fractionated IMRT treatment, using a clinically derived intensity profile and a 2D target trajectory based on measured patient data. Comparisons were made between 2D tracking, 1D tracking, and no tracking. The impact of the tracking lag time and the frequency of real-time imaging were investigated. A study of the dependence of the algorithm's performance on the level of agreement between the motion measured during planning and delivery was also included. Results demonstrated that tracking both components of the 2D motion (i.e., parallel and orthogonal to leaf travel) results in delivered fluence profiles that are superior to those that track the component of motion that is parallel to leaf travel alone. Tracking lag time effects may lead to relatively large intensity delivery errors compared to the other sources of error investigated. However, the algorithm presented is robust in the sense that it does not rely on a high level of agreement between the target motion measured during treatment planning and delivery.

Effects of measurement unobservability on neural extended Kalman filter tracking

NASA Astrophysics Data System (ADS)

Stubberud, Stephen C.; Kramer, Kathleen A.

2009-05-01

An important component of tracking fusion systems is the ability to fuse various sensors into a coherent picture of the scene. When multiple sensor systems are being used in an operational setting, the types of data vary. A significant but often overlooked concern of multiple sensors is the incorporation of measurements that are unobservable. An unobservable measurement is one that may provide information about the state, but cannot recreate a full target state. A line of bearing measurement, for example, cannot provide complete position information. Often, such measurements come from passive sensors such as a passive sonar array or an electronic surveillance measure (ESM) system. Unobservable measurements will, over time, result in the measurement uncertainty to grow without bound. While some tracking implementations have triggers to protect against the detrimental effects, many maneuver tracking algorithms avoid discussing this implementation issue. One maneuver tracking technique is the neural extended Kalman filter (NEKF). The NEKF is an adaptive estimation algorithm that estimates the target track as it trains a neural network on line to reduce the error between the a priori target motion model and the actual target dynamics. The weights of neural network are trained in a similar method to the state estimation/parameter estimation Kalman filter techniques. The NEKF has been shown to improve target tracking accuracy through maneuvers and has been use to predict target behavior using the new model that consists of the a priori model and the neural network. The key to the on-line adaptation of the NEKF is the fact that the neural network is trained using the same residuals as the Kalman filter for the tracker. The neural network weights are treated as augmented states to the target track. Through the state-coupling function, the weights are coupled to the target states. Thus, if the measurements cause the states of the target track to be unobservable, then the weights of the neural network have unobservable modes as well. In recent analysis, the NEKF was shown to have a significantly larger growth in the eigenvalues of the error covariance matrix than the standard EKF tracker when the measurements were purely bearings-only. This caused detrimental effects to the ability of the NEKF to model the target dynamics. In this work, the analysis is expanded to determine the detrimental effects of bearings-only measurements of various uncertainties on the performance of the NEKF when these unobservable measurements are interlaced with completely observable measurements. This analysis provides the ability to put implementation limitations on the NEKF when bearings-only sensors are present.

Tracking and recognition of multiple human targets moving in a wireless pyroelectric infrared sensor network.

PubMed

Xiong, Ji; Li, Fangmin; Zhao, Ning; Jiang, Na

2014-04-22

With characteristics of low-cost and easy deployment, the distributed wireless pyroelectric infrared sensor network has attracted extensive interest, which aims to make it an alternate infrared video sensor in thermal biometric applications for tracking and identifying human targets. In these applications, effectively processing signals collected from sensors and extracting the features of different human targets has become crucial. This paper proposes the application of empirical mode decomposition and the Hilbert-Huang transform to extract features of moving human targets both in the time domain and the frequency domain. Moreover, the support vector machine is selected as the classifier. The experimental results demonstrate that by using this method the identification rates of multiple moving human targets are around 90%.

Splitting attention reduces temporal resolution from 7 Hz for tracking one object to <3 Hz when tracking three.

PubMed

Holcombe, Alex O; Chen, Wei-Ying

2013-01-09

Overall performance when tracking moving targets is known to be poorer for larger numbers of targets, but the specific effect on tracking's temporal resolution has never been investigated. We document a broad range of display parameters for which visual tracking is limited by temporal frequency (the interval between when a target is at each location and a distracter moves in and replaces it) rather than by object speed. We tested tracking of one, two, and three moving targets while the eyes remained fixed. Variation of the number of distracters and their speed revealed both speed limits and temporal frequency limits on tracking. The temporal frequency limit fell from 7 Hz with one target to 4 Hz with two targets and 2.6 Hz with three targets. The large size of this performance decrease implies that in the two-target condition participants would have done better by tracking only one of the two targets and ignoring the other. These effects are predicted by serial models involving a single tracking focus that must switch among the targets, sampling the position of only one target at a time. If parallel processing theories are to explain why dividing the tracking resource reduces temporal resolution so markedly, supplemental assumptions will be required.

The research and application of visual saliency and adaptive support vector machine in target tracking field.

PubMed

Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

2013-01-01

The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

Loop shaping design for tracking performance in machine axes.

PubMed

Schinstock, Dale E; Wei, Zhouhong; Yang, Tao

2006-01-01

A modern interpretation of classical loop shaping control design methods is presented in the context of tracking control for linear motor stages. Target applications include noncontacting machines such as laser cutters and markers, water jet cutters, and adhesive applicators. The methods are directly applicable to the common PID controller and are pertinent to many electromechanical servo actuators other than linear motors. In addition to explicit design techniques a PID tuning algorithm stressing the importance of tracking is described. While the theory behind these techniques is not new, the analysis of their application to modern systems is unique in the research literature. The techniques and results should be important to control practitioners optimizing PID controller designs for tracking and in comparing results from classical designs to modern techniques. The methods stress high-gain controller design and interpret what this means for PID. Nothing in the methods presented precludes the addition of feedforward control methods for added improvements in tracking. Laboratory results from a linear motor stage demonstrate that with large open-loop gain very good tracking performance can be achieved. The resultant tracking errors compare very favorably to results from similar motions on similar systems that utilize much more complicated controllers.

Data association approaches in bearings-only multi-target tracking

NASA Astrophysics Data System (ADS)

Xu, Benlian; Wang, Zhiquan

2008-03-01

According to requirements of time computation complexity and correctness of data association of the multi-target tracking, two algorithms are suggested in this paper. The proposed Algorithm 1 is developed from the modified version of dual Simplex method, and it has the advantage of direct and explicit form of the optimal solution. The Algorithm 2 is based on the idea of Algorithm 1 and rotational sort method, it combines not only advantages of Algorithm 1, but also reduces the computational burden, whose complexity is only 1/ N times that of Algorithm 1. Finally, numerical analyses are carried out to evaluate the performance of the two data association algorithms.

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

Tracking a convoy of multiple targets using acoustic sensor data

NASA Astrophysics Data System (ADS)

Damarla, T. R.

2003-08-01

In this paper we present an algorithm to track a convoy of several targets in a scene using acoustic sensor array data. The tracking algorithm is based on template of the direction of arrival (DOA) angles for the leading target. Often the first target is the closest target to the sensor array and hence the loudest with good signal to noise ratio. Several steps were used to generate a template of the DOA angle for the leading target, namely, (a) the angle at the present instant should be close to the angle at the previous instant and (b) the angle at the present instant should be within error bounds of the predicted value based on the previous values. Once the template of the DOA angles of the leading target is developed, it is used to predict the DOA angle tracks of the remaining targets. In order to generate the tracks for the remaining targets, a track is established if the angles correspond to the initial track values of the first target. Second the time delay between the first track and the remaining tracks are estimated at the highest correlation points between the first track and the remaining tracks. As the vehicles move at different speeds the tracks either compress or expand depending on whether a target is moving fast or slow compared to the first target. The expansion and compression ratios are estimated and used to estimate the predicted DOA angle values of the remaining targets. Based on these predicted DOA angles of the remaining targets the DOA angles obtained from the MVDR or Incoherent MUSIC will be appropriately assigned to proper tracks. Several other rules were developed to avoid mixing the tracks. The algorithm is tested on data collected at Aberdeen Proving Ground with a convoy of 3, 4 and 5 vehicles. Some of the vehicles are tracked and some are wheeled vehicles. The tracking algorithm results are found to be good. The results will be presented at the conference and in the paper.

PROBLEM OF FORMING IN A MAN-OPERATOR A HABIT OF TRACKING A MOVING TARGET,

DTIC Science & Technology

Cybernetics stimulated the large-scale use of the method of functional analogy which makes it possible to compare technical and human activity systems...interesting and highly efficient human activity because of the psychological control factor involved in its operation. The human tracking system is

Robotic Follow Algorithm

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

2005-03-30

The Robotic Follow Algorithm enables allows any robotic vehicle to follow a moving target while reactively choosing a route around nearby obstacles. The robotic follow behavior can be used with different camera systems and can be used with thermal or visual tracking as well as other tracking methods such as radio frequency tags.

Correlation Filter Learning Toward Peak Strength for Visual Tracking.

PubMed

Sui, Yao; Wang, Guanghui; Zhang, Li

2018-04-01

This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance. This paper aims at solving this issue and proposes a novel algorithm to learn the correlation filter. The proposed approach, by imposing an elastic net constraint on the filter, can adaptively eliminate those distractive features in the correlation filtering. A new peak strength metric is proposed to measure the discriminative capability of the learned correlation filter. It is demonstrated that the proposed approach effectively strengthens the peak of the correlation response, leading to more discriminative performance than previous methods. Extensive experiments on a challenging visual tracking benchmark demonstrate that the proposed tracker outperforms most state-of-the-art methods.

Infrared small target tracking based on SOPC

NASA Astrophysics Data System (ADS)

Hu, Taotao; Fan, Xiang; Zhang, Yu-Jin; Cheng, Zheng-dong; Zhu, Bin

2011-01-01

The paper presents a low cost FPGA based solution for a real-time infrared small target tracking system. A specialized architecture is presented based on a soft RISC processor capable of running kernel based mean shift tracking algorithm. Mean shift tracking algorithm is realized in NIOS II soft-core with SOPC (System on a Programmable Chip) technology. Though mean shift algorithm is widely used for target tracking, the original mean shift algorithm can not be directly used for infrared small target tracking. As infrared small target only has intensity information, so an improved mean shift algorithm is presented in this paper. How to describe target will determine whether target can be tracked by mean shift algorithm. Because color target can be tracked well by mean shift algorithm, imitating color image expression, spatial component and temporal component are advanced to describe target, which forms pseudo-color image. In order to improve the processing speed parallel technology and pipeline technology are taken. Two RAM are taken to stored images separately by ping-pong technology. A FLASH is used to store mass temp data. The experimental results show that infrared small target is tracked stably in complicated background.

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.

Visual servoing for a US-guided therapeutic HIFU system by coagulated lesion tracking: a phantom study.

PubMed

Seo, Joonho; Koizumi, Norihiro; Funamoto, Takakazu; Sugita, Naohiko; Yoshinaka, Kiyoshi; Nomiya, Akira; Homma, Yukio; Matsumoto, Yoichiro; Mitsuishi, Mamoru

2011-06-01

Applying ultrasound (US)-guided high-intensity focused ultrasound (HIFU) therapy for kidney tumours is currently very difficult, due to the unclearly observed tumour area and renal motion induced by human respiration. In this research, we propose new methods by which to track the indistinct tumour area and to compensate the respiratory tumour motion for US-guided HIFU treatment. For tracking indistinct tumour areas, we detect the US speckle change created by HIFU irradiation. In other words, HIFU thermal ablation can coagulate tissue in the tumour area and an intraoperatively created coagulated lesion (CL) is used as a spatial landmark for US visual tracking. Specifically, the condensation algorithm was applied to robust and real-time CL speckle pattern tracking in the sequence of US images. Moreover, biplanar US imaging was used to locate the three-dimensional position of the CL, and a three-actuator system drives the end-effector to compensate for the motion. Finally, we tested the proposed method by using a newly devised phantom model that enables both visual tracking and a thermal response by HIFU irradiation. In the experiment, after generation of the CL in the phantom kidney, the end-effector successfully synchronized with the phantom motion, which was modelled by the captured motion data for the human kidney. The accuracy of the motion compensation was evaluated by the error between the end-effector and the respiratory motion, the RMS error of which was approximately 2 mm. This research shows that a HIFU-induced CL provides a very good landmark for target motion tracking. By using the CL tracking method, target motion compensation can be realized in the US-guided robotic HIFU system. Copyright © 2011 John Wiley & Sons, Ltd.

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.

Robust infrared target tracking using discriminative and generative approaches

NASA Astrophysics Data System (ADS)

Asha, C. S.; Narasimhadhan, A. V.

2017-09-01

The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

An effective and robust method for tracking multiple fish in video image based on fish head detection.

PubMed

Qian, Zhi-Ming; Wang, Shuo Hong; Cheng, Xi En; Chen, Yan Qiu

2016-06-23

Fish tracking is an important step for video based analysis of fish behavior. Due to severe body deformation and mutual occlusion of multiple swimming fish, accurate and robust fish tracking from video image sequence is a highly challenging problem. The current tracking methods based on motion information are not accurate and robust enough to track the waving body and handle occlusion. In order to better overcome these problems, we propose a multiple fish tracking method based on fish head detection. The shape and gray scale characteristics of the fish image are employed to locate the fish head position. For each detected fish head, we utilize the gray distribution of the head region to estimate the fish head direction. Both the position and direction information from fish detection are then combined to build a cost function of fish swimming. Based on the cost function, global optimization method can be applied to associate the target between consecutive frames. Results show that our method can accurately detect the position and direction information of fish head, and has a good tracking performance for dozens of fish. The proposed method can successfully obtain the motion trajectories for dozens of fish so as to provide more precise data to accommodate systematic analysis of fish behavior.

The performance of matched-field track-before-detect methods using shallow-water Pacific data.

PubMed

Tantum, Stacy L; Nolte, Loren W; Krolik, Jeffrey L; Harmanci, Kerem

2002-07-01

Matched-field track-before-detect processing, which extends the concept of matched-field processing to include modeling of the source dynamics, has recently emerged as a promising approach for maintaining the track of a moving source. In this paper, optimal Bayesian and minimum variance beamforming track-before-detect algorithms which incorporate a priori knowledge of the source dynamics in addition to the underlying uncertainties in the ocean environment are presented. A Markov model is utilized for the source motion as a means of capturing the stochastic nature of the source dynamics without assuming uniform motion. In addition, the relationship between optimal Bayesian track-before-detect processing and minimum variance track-before-detect beamforming is examined, revealing how an optimal tracking philosophy may be used to guide the modification of existing beamforming techniques to incorporate track-before-detect capabilities. Further, the benefits of implementing an optimal approach over conventional methods are illustrated through application of these methods to shallow-water Pacific data collected as part of the SWellEX-1 experiment. The results show that incorporating Markovian dynamics for the source motion provides marked improvement in the ability to maintain target track without the use of a uniform velocity hypothesis.

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.

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

The role of "rescue saccades" in tracking objects through occlusions.

PubMed

Zelinsky, Gregory J; Todor, Andrei

2010-12-29

We hypothesize that our ability to track objects through occlusions is mediated by timely assistance from gaze in the form of "rescue saccades"-eye movements to tracked objects that are in danger of being lost due to impending occlusion. Observers tracked 2-4 target sharks (out of 9) for 20 s as they swam through a rendered 3D underwater scene. Targets were either allowed to enter into occlusions (occlusion trials) or not (no occlusion trials). Tracking accuracy with 2-3 targets was ≥ 92% regardless of target occlusion but dropped to 74% on occlusion trials with four targets (no occlusion trials remained accurate; 83%). This pattern was mirrored in the frequency of rescue saccades. Rescue saccades accompanied approximatlely 50% of the Track 2-3 target occlusions, but only 34% of the Track 4 occlusions. Their frequency also decreased with increasing distance between a target and the nearest other object, suggesting that it is the potential for target confusion that summons a rescue saccade, not occlusion itself. These findings provide evidence for a tracking system that monitors for events that might cause track loss (e.g., occlusions) and requests help from the oculomotor system to resolve these momentary crises. As the number of crises increase with the number of targets, some requests for help go unsatisfied, resulting in degraded tracking.

System considerations for detection and tracking of small targets using passive sensors

NASA Astrophysics Data System (ADS)

DeBell, David A.

1991-08-01

Passive sensors provide only a few discriminants to assist in threat assessment of small targets. Tracking of the small targets provides additional discriminants. This paper discusses the system considerations for tracking small targets using passive sensors, in particular EO sensors. Tracking helps establish good versus bad detections. Discussed are the requirements to be placed on the sensor system's accuracy, with respect to knowledge of the sightline direction. The detection of weak targets sets a requirement for two levels of tracking in order to reduce processor throughput. A system characteristic is the need to track all detections. For low thresholds, this can mean a heavy track burden. Therefore, thresholds must be adaptive in order not to saturate the processors. Second-level tracks must develop a range estimate in order to assess threat. Sensor platform maneuvers are required if the targets are moving. The need for accurate pointing, good stability, and a good update rate will be shown quantitatively, relating to track accuracy and track association.

Dynamic tumor tracking using the Elekta Agility MLC

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

Fast, Martin F., E-mail: martin.fast@icr.ac.uk; Nill, Simeon, E-mail: simeon.nill@icr.ac.uk; Bedford, James L.

2014-11-01

Purpose: To evaluate the performance of the Elekta Agility multileaf collimator (MLC) for dynamic real-time tumor tracking. Methods: The authors have developed a new control software which interfaces to the Agility MLC to dynamically program the movement of individual leaves, the dynamic leaf guides (DLGs), and the Y collimators (“jaws”) based on the actual target trajectory. A motion platform was used to perform dynamic tracking experiments with sinusoidal trajectories. The actual target positions reported by the motion platform at 20, 30, or 40 Hz were used as shift vectors for the MLC in beams-eye-view. The system latency of the MLCmore » (i.e., the average latency comprising target device reporting latencies and MLC adjustment latency) and the geometric tracking accuracy were extracted from a sequence of MV portal images acquired during irradiation for the following treatment scenarios: leaf-only motion, jaw + leaf motion, and DLG + leaf motion. Results: The portal imager measurements indicated a clear dependence of the system latency on the target position reporting frequency. Deducting the effect of the target frequency, the leaf adjustment latency was measured to be 38 ± 3 ms for a maximum target speed v of 13 mm/s. The jaw + leaf adjustment latency was 53 ± 3 at a similar speed. The system latency at a target position frequency of 30 Hz was in the range of 56–61 ms for the leaves (v ≤ 31 mm/s), 71–78 ms for the jaw + leaf motion (v ≤ 25 mm/s), and 58–72 ms for the DLG + leaf motion (v ≤ 59 mm/s). The tracking accuracy showed a similar dependency on the target position frequency and the maximum target speed. For the leaves, the root-mean-squared error (RMSE) was between 0.6–1.5 mm depending on the maximum target speed. For the jaw + leaf (DLG + leaf) motion, the RMSE was between 0.7–1.5 mm (1.9–3.4 mm). Conclusions: The authors have measured the latency and geometric accuracy of the Agility MLC, facilitating its future use for clinical tracking applications.« less

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.

Motion tracing system for ultrasound guided HIFU

NASA Astrophysics Data System (ADS)

Xiao, Xu; Jiang, Tingyi; Corner, George; Huang, Zhihong

2017-03-01

One main limitation in HIFU treatment is the abdominal movement in liver and kidney caused by respiration. The study has set up a tracking model which mainly compromises of a target carrying box and a motion driving balloon. A real-time B-mode ultrasound guidance method suitable for tracking of the abdominal organ motion in 2D was established and tested. For the setup, the phantoms mimicking moving organs are carefully prepared with agar surrounding round-shaped egg-white as the target of focused ultrasound ablation. Physiological phantoms and animal tissues are driven moving reciprocally along the main axial direction of the ultrasound image probe with slightly motion perpendicular to the axial direction. The moving speed and range could be adjusted by controlling the inflation and deflation speed and amount of the balloon driven by a medical ventilator. A 6-DOF robotic arm was used to position the focused ultrasound transducer. The overall system was trying to estimate to simulate the actual movement caused by human respiration. HIFU ablation experiments using phantoms and animal organs were conducted to test the tracking effect. Ultrasound strain elastography was used to post estimate the efficiency of the tracking algorithms and system. In moving state, the axial size of the lesion (perpendicular to the movement direction) are averagely 4mm, which is one third larger than the lesion got when the target was not moving. This presents the possibility of developing a low-cost real-time method of tracking organ motion during HIFU treatment in liver or kidney.

The research of radar target tracking observed information linear filter method

NASA Astrophysics Data System (ADS)

Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

2018-05-01

Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

Tracking and Recognition of Multiple Human Targets Moving in a Wireless Pyroelectric Infrared Sensor Network

PubMed Central

Xiong, Ji; Li, Fangmin; Zhao, Ning; Jiang, Na

2014-01-01

With characteristics of low-cost and easy deployment, the distributed wireless pyroelectric infrared sensor network has attracted extensive interest, which aims to make it an alternate infrared video sensor in thermal biometric applications for tracking and identifying human targets. In these applications, effectively processing signals collected from sensors and extracting the features of different human targets has become crucial. This paper proposes the application of empirical mode decomposition and the Hilbert-Huang transform to extract features of moving human targets both in the time domain and the frequency domain. Moreover, the support vector machine is selected as the classifier. The experimental results demonstrate that by using this method the identification rates of multiple moving human targets are around 90%. PMID:24759117

Infrared measurement and composite tracking algorithm for air-breathing hypersonic vehicles

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Gao, Changsheng; Jing, Wuxing

2018-03-01

Air-breathing hypersonic vehicles have capabilities of hypersonic speed and strong maneuvering, and thus pose a significant challenge to conventional tracking methodologies. To achieve desirable tracking performance for hypersonic targets, this paper investigates the problems related to measurement model design and tracking model mismatching. First, owing to the severe aerothermal effect of hypersonic motion, an infrared measurement model in near space is designed and analyzed based on target infrared radiation and an atmospheric model. Second, using information from infrared sensors, a composite tracking algorithm is proposed via a combination of the interactive multiple models (IMM) algorithm, fitting dynamics model, and strong tracking filter. During the procedure, the IMMs algorithm generates tracking data to establish a fitting dynamics model of the target. Then, the strong tracking unscented Kalman filter is employed to estimate the target states for suppressing the impact of target maneuvers. Simulations are performed to verify the feasibility of the presented composite tracking algorithm. The results demonstrate that the designed infrared measurement model effectively and continuously observes hypersonic vehicles, and the proposed composite tracking algorithm accurately and stably tracks these targets.

AGATE: Adversarial Game Analysis for Tactical Evaluation

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.

2013-01-01

AGATE generates a set of ranked strategies that enables an autonomous vehicle to track/trail another vehicle that is trying to break the contact using evasive tactics. The software is efficient (can be run on a laptop), scales well with environmental complexity, and is suitable for use onboard an autonomous vehicle. The software will run in near-real-time (2 Hz) on most commercial laptops. Existing software is usually run offline in a planning mode, and is not used to control an unmanned vehicle actively. JPL has developed a system for AGATE that uses adversarial game theory (AGT) methods (in particular, leader-follower and pursuit-evasion) to enable an autonomous vehicle (AV) to maintain tracking/ trailing operations on a target that is employing evasive tactics. The AV trailing, tracking, and reacquisition operations are characterized by imperfect information, and are an example of a non-zero sum game (a positive payoff for the AV is not necessarily an equal loss for the target being tracked and, potentially, additional adversarial boats). Previously, JPL successfully applied the Nash equilibrium method for onboard control of an autonomous ground vehicle (AGV) travelling over hazardous terrain.

Calibration and evaluation of a magnetically tracked ICE probe for guidance of left atrial ablation therapy

NASA Astrophysics Data System (ADS)

Linte, Cristian A.; Rettmann, Maryam E.; Dilger, Ben; Gunawan, Mia S.; Arunachalam, Shivaram P.; Holmes, David R., III; Packer, Douglas L.; Robb, Richard A.

2012-02-01

The novel prototype system for advanced visualization for image-guided left atrial ablation therapy developed in our laboratory permits ready integration of multiple imaging modalities, surgical instrument tracking, interventional devices and electro-physiologic data. This technology allows subject-specific procedure planning and guidance using 3D dynamic, patient-specific models of the patient's heart, augmented with real-time intracardiac echocardiography (ICE). In order for the 2D ICE images to provide intuitive visualization for accurate catheter to surgical target navigation, the transducer must be tracked, so that the acquired images can be appropriately presented with respect to the patient-specific anatomy. Here we present the implementation of a previously developed ultrasound calibration technique for a magnetically tracked ICE transducer, along with a series of evaluation methods to ensure accurate imaging and faithful representation of the imaged structures. Using an engineering-designed phantom, target localization accuracy is assessed by comparing known target locations with their transformed locations inferred from the tracked US images. In addition, the 3D volume reconstruction accuracy is also estimated by comparing a truth volume to that reconstructed from sequential 2D US images. Clinically emulating validation studies are conducted using a patient-specific left atrial phantom. Target localization error of clinically-relevant surgical targets represented by nylon fiducials implanted within the endocardial wall of the phantom was assessed. Our studies have demonstrated 2.4 +/- 0.8 mm target localization error in the engineering-designed evaluation phantoms, 94.8 +/- 4.6 % volume reconstruction accuracy, and 3.1 +/- 1.2 mm target localization error in the left atrial-mimicking phantom. These results are consistent with those disseminated in the literature and also with the accuracy constraints imposed by the employed technology and the clinical application.

Feature extraction algorithm for space targets based on fractal theory

NASA Astrophysics Data System (ADS)

Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

2007-11-01

In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

Improved GGIW-PHD filter for maneuvering non-ellipsoidal extended targets or group targets tracking based on sub-random matrices.

PubMed

Liang, Zhibing; Liu, Fuxian; Gao, Jiale

2018-01-01

For non-ellipsoidal extended targets and group targets tracking (NETT and NGTT), using an ellipsoid to approximate the target extension may not be accurate enough because of the lack of shape and orientation information. In consideration of this, we model a non-ellipsoidal extended target or target group as a combination of multiple ellipsoidal sub-objects, each represented by a random matrix. Based on these models, an improved gamma Gaussian inverse Wishart probability hypothesis density (GGIW-PHD) filter is proposed to estimate the measurement rates, kinematic states, and extension states of the sub-objects for each extended target or target group. For maneuvering NETT and NGTT, a multi-model (MM) approach based GGIW-PHD (MM-GGIW-PHD) filter is proposed. The common and the individual dynamics of the sub-objects belonging to the same extended target or target group are described by means of the combination between the overall maneuver model and the sub-object models. For the merging of updating components, an improved merging criterion and a new merging method are derived. A specific implementation of prediction partition with pseudo-likelihood method is presented. Two scenarios for non-maneuvering and maneuvering NETT and NGTT are simulated. The results demonstrate the effectiveness of the proposed algorithms.

Improved GGIW-PHD filter for maneuvering non-ellipsoidal extended targets or group targets tracking based on sub-random matrices

PubMed Central

Liu, Fuxian; Gao, Jiale

2018-01-01

For non-ellipsoidal extended targets and group targets tracking (NETT and NGTT), using an ellipsoid to approximate the target extension may not be accurate enough because of the lack of shape and orientation information. In consideration of this, we model a non-ellipsoidal extended target or target group as a combination of multiple ellipsoidal sub-objects, each represented by a random matrix. Based on these models, an improved gamma Gaussian inverse Wishart probability hypothesis density (GGIW-PHD) filter is proposed to estimate the measurement rates, kinematic states, and extension states of the sub-objects for each extended target or target group. For maneuvering NETT and NGTT, a multi-model (MM) approach based GGIW-PHD (MM-GGIW-PHD) filter is proposed. The common and the individual dynamics of the sub-objects belonging to the same extended target or target group are described by means of the combination between the overall maneuver model and the sub-object models. For the merging of updating components, an improved merging criterion and a new merging method are derived. A specific implementation of prediction partition with pseudo-likelihood method is presented. Two scenarios for non-maneuvering and maneuvering NETT and NGTT are simulated. The results demonstrate the effectiveness of the proposed algorithms. PMID:29444144

Multi-channel, passive, short-range anti-aircraft defence system

NASA Astrophysics Data System (ADS)

Gapiński, Daniel; Krzysztofik, Izabela; Koruba, Zbigniew

2018-01-01

The paper presents a novel method for tracking several air targets simultaneously. The developed concept concerns a multi-channel, passive, short-range anti-aircraft defence system based on the programmed selection of air targets and an algorithm of simultaneous synchronisation of several modified optical scanning seekers. The above system is supposed to facilitate simultaneous firing of several self-guided infrared rocket missiles at many different air targets. From the available information, it appears that, currently, there are no passive self-guided seekers that fulfil such tasks. This paper contains theoretical discussions and simulations of simultaneous detection and tracking of many air targets by mutually integrated seekers of several rocket missiles. The results of computer simulation research have been presented in a graphical form.

Target attribute-based false alarm rejection in small infrared target detection

NASA Astrophysics Data System (ADS)

Kim, Sungho

2012-11-01

Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

Real-time target tracking of soft tissues in 3D ultrasound images based on robust visual information and mechanical simulation.

PubMed

Royer, Lucas; Krupa, Alexandre; Dardenne, Guillaume; Le Bras, Anthony; Marchand, Eric; Marchal, Maud

2017-01-01

In this paper, we present a real-time approach that allows tracking deformable structures in 3D ultrasound sequences. Our method consists in obtaining the target displacements by combining robust dense motion estimation and mechanical model simulation. We perform evaluation of our method through simulated data, phantom data, and real-data. Results demonstrate that this novel approach has the advantage of providing correct motion estimation regarding different ultrasound shortcomings including speckle noise, large shadows and ultrasound gain variation. Furthermore, we show the good performance of our method with respect to state-of-the-art techniques by testing on the 3D databases provided by MICCAI CLUST'14 and CLUST'15 challenges. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time adaptive methods for treatment of mobile organs by MRI-controlled high-intensity focused ultrasound.

PubMed

de Senneville, Baudouin Denis; Mougenot, Charles; Moonen, Chrit T W

2007-02-01

Focused ultrasound (US) is a unique and noninvasive technique for local deposition of thermal energy deep inside the body. MRI guidance offers the additional benefits of excellent target visualization and continuous temperature mapping. However, treating a moving target poses severe problems because 1) motion-related thermometry artifacts must be corrected, 2) the US focal point must be relocated according to the target displacement. In this paper a complete MRI-compatible, high-intensity focused US (HIFU) system is described together with adaptive methods that allow continuous MR thermometry and therapeutic US with real-time tracking of a moving target, online motion correction of the thermometry maps, and regional temperature control based on the proportional, integral, and derivative method. The hardware is based on a 256-element phased-array transducer with rapid electronic displacement of the focal point. The exact location of the target during US firing is anticipated using automatic analysis of periodic motions. The methods were tested with moving phantoms undergoing either rigid body or elastic periodical motions. The results show accurate tracking of the focal point. Focal and regional temperature control is demonstrated with a performance similar to that obtained with stationary phantoms. Copyright (c) 2007 Wiley-Liss, Inc.

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.

Position estimation and driving of an autonomous vehicle by monocular vision

NASA Astrophysics Data System (ADS)

Hanan, Jay C.; Kayathi, Pavan; Hughlett, Casey L.

2007-04-01

Automatic adaptive tracking in real-time for target recognition provided autonomous control of a scale model electric truck. The two-wheel drive truck was modified as an autonomous rover test-bed for vision based guidance and navigation. Methods were implemented to monitor tracking error and ensure a safe, accurate arrival at the intended science target. Some methods are situation independent relying only on the confidence error of the target recognition algorithm. Other methods take advantage of the scenario of combined motion and tracking to filter out anomalies. In either case, only a single calibrated camera was needed for position estimation. Results from real-time autonomous driving tests on the JPL simulated Mars yard are presented. Recognition error was often situation dependent. For the rover case, the background was in motion and may be characterized to provide visual cues on rover travel such as rate, pitch, roll, and distance to objects of interest or hazards. Objects in the scene may be used as landmarks, or waypoints, for such estimations. As objects are approached, their scale increases and their orientation may change. In addition, particularly on rough terrain, these orientation and scale changes may be unpredictable. Feature extraction combined with the neural network algorithm was successful in providing visual odometry in the simulated Mars environment.

Feasibility Study for Markerless Tracking of Lung Tumors in Stereotactic Body Radiotherapy

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

Richter, Anne, E-mail: richter_a3@klinik.uni-wuerzburg.d; Wilbert, Juergen; Baier, Kurt

2010-10-01

Purpose: To evaluate the feasibility and accuracy of a method for markerless tracking of lung tumors in electronic portal imaging device (EPID) movies and to analyze intra- and interfractional variations in tumor motion. Methods and Materials: EPID movies were acquired during stereotactic body radiotherapy (SBRT) given to 40 patients with 49 pulmonary targets and retrospectively analyzed. Tumor visibility and tracking accuracy were determined by three observers. Tumor motion of 30 targets was analyzed in detail via four-dimensional computed tomography (4DCT) and EPID in the superior-inferior direction for intra- and interfractional variations. Results: Tumor visibility was sufficient for markerless tracking inmore » 47% of the EPID movies. Tumor size and visibility in the DRR were correlated with visibility in the EPID images. The difference between automatic and manual tracking was a maximum of 2 mm for 98.3% in the x direction and 89.4% in the y direction. Motion amplitudes in 4DCT images (range, 0.7-17.9 mm; median, 4.9 mm) were closely correlated with amplitudes in the EPID movies. Intrafractional and interfractional variability of tumor motion amplitude were of similar magnitude: 1 mm on average to a maximum of 4 mm. A change in moving average of more than {+-}1 mm, {+-}2 mm, and {+-}4 mm were observed in 47.1%, 17.1%, and 4.5% of treatment time for all trajectories, respectively. Mean tumor velocity was 3.4 mm/sec, to a maximum 61 mm/sec. Conclusions: Tracking of pulmonary tumors in EPID images without implanted markers was feasible in 47% of all treatment beams. 4DCT is representative of the evaluation of mean breathing motion on average, but larger deviations occurred in target motion between treatment planning and delivery effort a monitoring during delivery.« less

Real-time target tracking and locating system for UAV

NASA Astrophysics Data System (ADS)

Zhang, Chao; Tang, Linbo; Fu, Huiquan; Li, Maowen

2017-07-01

In order to achieve real-time target tracking and locating for UAV, a reliable processing system is built on the embedded platform. Firstly, the video image is acquired in real time by the photovoltaic system on the UAV. When the target information is known, KCF tracking algorithm is adopted to track the target. Then, the servo is controlled to rotate with the target, when the target is in the center of the image, the laser ranging module is opened to obtain the distance between the UAV and the target. Finally, to combine with UAV flight parameters obtained by BeiDou navigation system, through the target location algorithm to calculate the geodetic coordinates of the target. The results show that the system is stable for real-time tracking of targets and positioning.

Improving detection of low SNR targets using moment-based detection

NASA Astrophysics Data System (ADS)

Young, Shannon R.; Steward, Bryan J.; Hawks, Michael; Gross, Kevin C.

2016-05-01

Increases in the number of cameras deployed, frame rate, and detector array sizes have led to a dramatic increase in the volume of motion imagery data that is collected. Without a corresponding increase in analytical manpower, much of the data is not analyzed to full potential. This creates a need for fast, automated, and robust methods for detecting signals of interest. Current approaches fall into two categories: detect-before-track (DBT), which are fast but often poor at detecting dim targets, and track-before-detect (TBD) methods which can offer better performance but are typically much slower. This research seeks to contribute to the near real time detection of low SNR, unresolved moving targets through an extension of earlier work on higher order moments anomaly detection, a method that exploits both spatial and temporal information but is still computationally efficient and massively parallelizable. It was found that intelligent selection of parameters can improve probability of detection by as much as 25% compared to earlier work with higherorder moments. The present method can reduce detection thresholds by 40% compared to the Reed-Xiaoli anomaly detector for low SNR targets (for a given probability of detection and false alarm).

WE-G-213CD-03: A Dual Complementary Verification Method for Dynamic Tumor Tracking on Vero SBRT.

PubMed

Poels, K; Depuydt, T; Verellen, D; De Ridder, M

2012-06-01

to use complementary cine EPID and gimbals log file analysis for in-vivo tracking accuracy monitoring. A clinical prototype of dynamic tracking (DT) was installed on the Vero SBRT system. This prototype version allowed tumor tracking by gimballed linac rotations using an internal-external correspondence model. The DT prototype software allowed the detailed logging of all applied gimbals rotations during tracking. The integration of an EPID on the vero system allowed the acquisition of cine EPID images during DT. We quantified the tracking error on cine EPID (E-EPID) by subtracting the target center (fiducial marker detection) and the field centroid. Dynamic gimbals log file information was combined with orthogonal x-ray verification images to calculate the in-vivo tracking error (E-kVLog). The correlation between E-kVLog and E-EPID was calculated for validation of the gimbals log file. Further, we investigated the sensitivity of the log file tracking error by introducing predefined systematic tracking errors. As an application we calculate gimbals log file tracking error for dynamic hidden target tests to investigate gravity effects and decoupled gimbals rotation from gantry rotation. Finally, calculating complementary cine EPID and log file tracking errors evaluated the clinical accuracy of dynamic tracking. A strong correlation was found between log file and cine EPID tracking error distribution during concurrent measurements (R=0.98). We found sensitivity in the gimbals log files to detect a systematic tracking error up to 0.5 mm. Dynamic hidden target tests showed no gravity influence on tracking performance and high degree of decoupled gimbals and gantry rotation during dynamic arc dynamic tracking. A submillimetric agreement between clinical complementary tracking error measurements was found. Redundancy of the internal gimbals log file with x-ray verification images with complementary independent cine EPID images was implemented to monitor the accuracy of gimballed tumor tracking on Vero SBRT. Research was financially supported by the Flemish government (FWO), Hercules Foundation and BrainLAB AG. © 2012 American Association of Physicists in Medicine.

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.

A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking.

PubMed

Zhou, Jie; Liang, Yan; Shen, Qiang; Feng, Xiaoxue; Pan, Quan

2018-04-18

A biomimetic distributed infection-immunity model (BDIIM), inspired by the immune mechanism of an infected organism, is proposed in order to achieve a high-efficiency wake-up control strategy based on multi-sensor fusion for target tracking. The resultant BDIIM consists of six sub-processes reflecting the infection-immunity mechanism: occurrence probabilities of direct-infection (DI) and cross-infection (CI), immunity/immune-deficiency of DI and CI, pathogen amount of DI and CI, immune cell production, immune memory, and pathogen accumulation under immunity state. Furthermore, a corresponding relationship between the BDIIM and sensor wake-up control is established to form the collaborative wake-up method. Finally, joint surveillance and target tracking are formulated in the simulation, in which we show that the energy cost and position tracking error are reduced to 50.8% and 78.9%, respectively. Effectiveness of the proposed BDIIM algorithm is shown, and this model is expected to have a significant role in guiding the performance improvement of multi-sensor networks.

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.

Adaptive block online learning target tracking based on super pixel segmentation

NASA Astrophysics Data System (ADS)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

Bayesian Tracking within a Feedback Sensing Environment: Estimating Interacting, Spatially Constrained Complex Dynamical Systems from Multiple Sources of Controllable Devices

DTIC Science & Technology

2014-07-25

composition of simple temporal structures to a speaker diarization task with the goal of segmenting conference audio in the presence of an unknown number of...application domains including neuroimaging, diverse document selection, speaker diarization , stock modeling, and target tracking. We detail each of...recall performance than competing methods in a task of discovering articles preferred by the user • a gold-standard speaker diarization method, as

Commissioning of the Active-Target Time Projection Chamber

NASA Astrophysics Data System (ADS)

Bradt, J.; Bazin, D.; Abu-Nimeh, F.; Ahn, T.; Ayyad, Y.; Beceiro Novo, S.; Carpenter, L.; Cortesi, M.; Kuchera, M. P.; Lynch, W. G.; Mittig, W.; Rost, S.; Watwood, N.; Yurkon, J.

2017-12-01

The Active-Target Time Projection Chamber (AT-TPC) was recently built and commissioned at the National Superconducting Cyclotron Laboratory at Michigan State University. This gas-filled detector uses an active-target design where the gas acts as both the tracking medium and the reaction target. Operating inside a 2T solenoidal magnetic field, the AT-TPC records charged particle tracks that can be reconstructed to very good energy and angular resolutions. The near- 4 π solid angle coverage and thick target of the detector are well-suited to experiments with low secondary beam intensities. In this paper, the design and instrumentation of theAT-TPC are described along with the methods used to analyze the data it produces. A simulation of the detector's performance and some results from its commissioning with a radioactive 46Ar beam are also presented.

Space-based IR tracking bias removal using background star observations

NASA Astrophysics Data System (ADS)

Clemons, T. M., III; Chang, K. C.

2009-05-01

This paper provides the results of a proposed methodology for removing sensor bias from a space-based infrared (IR) tracking system through the use of stars detected in the background field of the tracking sensor. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with a narrow-view IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. As known stars are detected during the target tracking process, the instantaneous sensor pointing error can be calculated as the difference between star detection reading and the known position of the star. The system then utilizes a separate bias filter to estimate the bias value based on these detections and correct the target line of sight measurements to improve the target state vector. The target state vector is estimated through a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. Scenarios are created using Satellite Toolkit(C) for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide a potential solution to bias correction while simultaneously tracking a target.

A particle filter for multi-target tracking in track before detect context

NASA Astrophysics Data System (ADS)

Amrouche, Naima; Khenchaf, Ali; Berkani, Daoud

2016-10-01

The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm's successful performance is demonstrated using a simulated two target example.

Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase

PubMed Central

Lu, Kelin; Zhou, Rui

2016-01-01

A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications. PMID:27537883

Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase.

PubMed

Lu, Kelin; Zhou, Rui

2016-08-15

A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications.

Space-time interface-tracking with topology change (ST-TC)

NASA Astrophysics Data System (ADS)

Takizawa, Kenji; Tezduyar, Tayfun E.; Buscher, Austin; Asada, Shohei

2014-10-01

To address the computational challenges associated with contact between moving interfaces, such as those in cardiovascular fluid-structure interaction (FSI), parachute FSI, and flapping-wing aerodynamics, we introduce a space-time (ST) interface-tracking method that can deal with topology change (TC). In cardiovascular FSI, our primary target is heart valves. The method is a new version of the deforming-spatial-domain/stabilized space-time (DSD/SST) method, and we call it ST-TC. It includes a master-slave system that maintains the connectivity of the "parent" mesh when there is contact between the moving interfaces. It is an efficient, practical alternative to using unstructured ST meshes, but without giving up on the accurate representation of the interface or consistent representation of the interface motion. We explain the method with conceptual examples and present 2D test computations with models representative of the classes of problems we are targeting.

The development of a super-fine-grained nuclear emulsion

NASA Astrophysics Data System (ADS)

Asada, Takashi; Naka, Tatsuhiro; Kuwabara, Ken-ichi; Yoshimoto, Masahiro

2017-06-01

A nuclear emulsion with micronized crystals is required for the tracking detection of submicron ionizing particles, which are one of the targets of dark-matter detection and other techniques. We found that a new production method, called the PVA—gelatin mixing method (PGMM), could effectively control crystal size from 20 nm to 50 nm. We called the two types of emulsion produced with the new method the nano imaging tracker and the ultra-nano imaging tracker. Their composition and spatial resolution were measured, and the results indicate that these emulsions detect extremely short tracks.

Robust Fusion of Color and Depth Data for RGB-D Target Tracking Using Adaptive Range-Invariant Depth Models and Spatio-Temporal Consistency Constraints.

PubMed

Xiao, Jingjing; Stolkin, Rustam; Gao, Yuqing; Leonardis, Ales

2017-09-06

This paper presents a novel robust method for single target tracking in RGB-D images, and also contributes a substantial new benchmark dataset for evaluating RGB-D trackers. While a target object's color distribution is reasonably motion-invariant, this is not true for the target's depth distribution, which continually varies as the target moves relative to the camera. It is therefore nontrivial to design target models which can fully exploit (potentially very rich) depth information for target tracking. For this reason, much of the previous RGB-D literature relies on color information for tracking, while exploiting depth information only for occlusion reasoning. In contrast, we propose an adaptive range-invariant target depth model, and show how both depth and color information can be fully and adaptively fused during the search for the target in each new RGB-D image. We introduce a new, hierarchical, two-layered target model (comprising local and global models) which uses spatio-temporal consistency constraints to achieve stable and robust on-the-fly target relearning. In the global layer, multiple features, derived from both color and depth data, are adaptively fused to find a candidate target region. In ambiguous frames, where one or more features disagree, this global candidate region is further decomposed into smaller local candidate regions for matching to local-layer models of small target parts. We also note that conventional use of depth data, for occlusion reasoning, can easily trigger false occlusion detections when the target moves rapidly toward the camera. To overcome this problem, we show how combining target information with contextual information enables the target's depth constraint to be relaxed. Our adaptively relaxed depth constraints can robustly accommodate large and rapid target motion in the depth direction, while still enabling the use of depth data for highly accurate reasoning about occlusions. For evaluation, we introduce a new RGB-D benchmark dataset with per-frame annotated attributes and extensive bias analysis. Our tracker is evaluated using two different state-of-the-art methodologies, VOT and object tracking benchmark, and in both cases it significantly outperforms four other state-of-the-art RGB-D trackers from the literature.

Precision Control and Maneuvering of the Phoenix Autonomous Underwater Vehicle for Entering a Recovery Tube

DTIC Science & Technology

1996-09-01

T1wo such modes have buen iinrylvni teted: a full target-track mode0 and a target- edge-track mode. Whun using thc full target-track mode the sonai ...direction is reversed. Rather than tracking across the target all the way to the opposing edge, however, the sonai is scanned only until three returns

Advances in Doppler recognition for ground moving target indication

NASA Astrophysics Data System (ADS)

Kealey, Paul G.; Jahangir, Mohammed

2006-05-01

Ground Moving Target Indication (GMTI) radar provides a day/night, all-weather, wide-area surveillance capability to detect moving vehicles and personnel. Current GMTI radar sensors are limited to only detecting and tracking targets. The exploitation of GMTI data would be greatly enhanced by a capability to recognize accurately the detections as significant classes of target. Doppler classification exploits the differential internal motion of targets, e.g. due to the tracks, limbs and rotors. Recently, the QinetiQ Bayesian Doppler classifier has been extended to include a helicopter class in addition to wheeled, tracked and personnel classes. This paper presents the performance for these four classes using a traditional low-resolution GMTI surveillance waveform with an experimental radar system. We have determined the utility of an "unknown output decision" for enhancing the accuracy of the declared target classes. A confidence method has been derived, using a threshold of the difference in certainties, to assign uncertain classifications into an "unknown class". The trade-off between fraction of targets declared and accuracy of the classifier has been measured. To determine the operating envelope of a Doppler classification algorithm requires a detailed understanding of the Signal-to-Noise Ratio (SNR) performance of the algorithm. In this study the SNR dependence of the QinetiQ classifier has been determined.

A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression.

PubMed

Lee, Sunghoon Ivan; Mortazavi, Bobak; Hoffman, Haydn A; Lu, Derek S; Li, Charles; Paak, Brian H; Garst, Jordan H; Razaghy, Mehrdad; Espinal, Marie; Park, Eunjeong; Lu, Daniel C; Sarrafzadeh, Majid

2016-01-01

Predicting the functional outcomes of spinal cord disorder patients after medical treatments, such as a surgical operation, has always been of great interest. Accurate posttreatment prediction is especially beneficial for clinicians, patients, care givers, and therapists. This paper introduces a prediction method for postoperative functional outcomes by a novel use of Gaussian process regression. The proposed method specifically considers the restricted value range of the target variables by modeling the Gaussian process based on a truncated Normal distribution, which significantly improves the prediction results. The prediction has been made in assistance with target tracking examinations using a highly portable and inexpensive handgrip device, which greatly contributes to the prediction performance. The proposed method has been validated through a dataset collected from a clinical cohort pilot involving 15 patients with cervical spinal cord disorder. The results show that the proposed method can accurately predict postoperative functional outcomes, Oswestry disability index and target tracking scores, based on the patient's preoperative information with a mean absolute error of 0.079 and 0.014 (out of 1.0), respectively.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Joint Target Detection and Tracking Filter for Chilbolton Advanced Meteorological Radar Data Processing

NASA Astrophysics Data System (ADS)

Pak, A.; Correa, J.; Adams, M.; Clark, D.; Delande, E.; Houssineau, J.; Franco, J.; Frueh, C.

2016-09-01

Recently, the growing number of inactive Resident Space Objects (RSOs), or space debris, has provoked increased interest in the field of Space Situational Awareness (SSA) and various investigations of new methods for orbital object tracking. In comparison with conventional tracking scenarios, state estimation of an orbiting object entails additional challenges, such as orbit determination and orbital state and covariance propagation in the presence of highly nonlinear system dynamics. The sensors which are available for detecting and tracking space debris are prone to multiple clutter measurements. Added to this problem, is the fact that it is unknown whether or not a space debris type target is present within such sensor measurements. Under these circumstances, traditional single-target filtering solutions such as Kalman Filters fail to produce useful trajectory estimates. The recent Random Finite Set (RFS) based Finite Set Statistical (FISST) framework has yielded filters which are more appropriate for such situations. The RFS based Joint Target Detection and Tracking (JoTT) filter, also known as the Bernoulli filter, is a single target, multiple measurements filter capable of dealing with cluttered and time-varying backgrounds as well as modeling target appearance and disappearance in the scene. Therefore, this paper presents the application of the Gaussian mixture-based JoTT filter for processing measurements from Chilbolton Advanced Meteorological Radar (CAMRa) which contain both defunct and operational satellites. The CAMRa is a fully-steerable radar located in southern England, which was recently modified to be used as a tracking asset in the European Space Agency SSA program. The experiments conducted show promising results regarding the capability of such filters in processing cluttered radar data. The work carried out in this paper was funded by the USAF Grant No. FA9550-15-1-0069, Chilean Conicyt - Fondecyt grant number 1150930, EU Erasmus Mundus MSc Scholarship, Defense Science and Technology Laboratory (DSTL), U. K., and the Chilean Conicyt, Fondecyt project grant number 1150930.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

A Fast MEANSHIFT Algorithm-Based Target Tracking System

PubMed Central

Sun, Jian

2012-01-01

Tracking moving targets in complex scenes using an active video camera is a challenging task. Tracking accuracy and efficiency are two key yet generally incompatible aspects of a Target Tracking System (TTS). A compromise scheme will be studied in this paper. A fast mean-shift-based Target Tracking scheme is designed and realized, which is robust to partial occlusion and changes in object appearance. The physical simulation shows that the image signal processing speed is >50 frame/s. PMID:22969397

Rover mast calibration, exact camera pointing, and camara handoff for visual target tracking

NASA Technical Reports Server (NTRS)

Kim, Won S.; Ansar, Adnan I.; Steele, Robert D.

2005-01-01

This paper presents three technical elements that we have developed to improve the accuracy of the visual target tracking for single-sol approach-and-instrument placement in future Mars rover missions. An accurate, straightforward method of rover mast calibration is achieved by using a total station, a camera calibration target, and four prism targets mounted on the rover. The method was applied to Rocky8 rover mast calibration and yielded a 1.1-pixel rms residual error. Camera pointing requires inverse kinematic solutions for mast pan and tilt angles such that the target image appears right at the center of the camera image. Two issues were raised. Mast camera frames are in general not parallel to the masthead base frame. Further, the optical axis of the camera model in general does not pass through the center of the image. Despite these issues, we managed to derive non-iterative closed-form exact solutions, which were verified with Matlab routines. Actual camera pointing experiments aver 50 random target image paints yielded less than 1.3-pixel rms pointing error. Finally, a purely geometric method for camera handoff using stereo views of the target has been developed. Experimental test runs show less than 2.5 pixels error on high-resolution Navcam for Pancam-to-Navcam handoff, and less than 4 pixels error on lower-resolution Hazcam for Navcam-to-Hazcam handoff.

A Bayesian approach to tracking patients having changing pharmacokinetic parameters

NASA Technical Reports Server (NTRS)

Bayard, David S.; Jelliffe, Roger W.

2004-01-01

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.

An MRI-Compatible Robotic System With Hybrid Tracking for MRI-Guided Prostate Intervention

PubMed Central

Krieger, Axel; Iordachita, Iulian I.; Guion, Peter; Singh, Anurag K.; Kaushal, Aradhana; Ménard, Cynthia; Pinto, Peter A.; Camphausen, Kevin; Fichtinger, Gabor

2012-01-01

This paper reports the development, evaluation, and first clinical trials of the access to the prostate tissue (APT) II system—a scanner independent system for magnetic resonance imaging (MRI)-guided transrectal prostate interventions. The system utilizes novel manipulator mechanics employing a steerable needle channel and a novel six degree-of-freedom hybrid tracking method, comprising passive fiducial tracking for initial registration and subsequent incremental motion measurements. Targeting accuracy of the system in prostate phantom experiments and two clinical human-subject procedures is shown to compare favorably with existing systems using passive and active tracking methods. The portable design of the APT II system, using only standard MRI image sequences and minimal custom scanner interfacing, allows the system to be easily used on different MRI scanners. PMID:22009867

SU-G-BRA-05: Application of a Feature-Based Tracking Algorithm to KV X-Ray Fluoroscopic Images Toward Marker-Less Real-Time Tumor Tracking

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

Nakamura, M; Matsuo, Y; Mukumoto, N

Purpose: To detect target position on kV X-ray fluoroscopic images using a feature-based tracking algorithm, Accelerated-KAZE (AKAZE), for markerless real-time tumor tracking (RTTT). Methods: Twelve lung cancer patients treated with RTTT on the Vero4DRT (Mitsubishi Heavy Industries, Japan, and Brainlab AG, Feldkirchen, Germany) were enrolled in this study. Respiratory tumor movement was greater than 10 mm. Three to five fiducial markers were implanted around the lung tumor transbronchially for each patient. Before beam delivery, external infrared (IR) markers and the fiducial markers were monitored for 20 to 40 s with the IR camera every 16.7 ms and with an orthogonalmore » kV x-ray imaging subsystem every 80 or 160 ms, respectively. Target positions derived from the fiducial markers were determined on the orthogonal kV x-ray images, which were used as the ground truth in this study. Meanwhile, tracking positions were identified by AKAZE. Among a lot of feature points, AKAZE found high-quality feature points through sequential cross-check and distance-check between two consecutive images. Then, these 2D positional data were converted to the 3D positional data by a transformation matrix with a predefined calibration parameter. Root mean square error (RMSE) was calculated to evaluate the difference between 3D tracking and target positions. A total of 393 frames was analyzed. The experiment was conducted on a personal computer with 16 GB RAM, Intel Core i7-2600, 3.4 GHz processor. Results: Reproducibility of the target position during the same respiratory phase was 0.6 +/− 0.6 mm (range, 0.1–3.3 mm). Mean +/− SD of the RMSEs was 0.3 +/− 0.2 mm (range, 0.0–1.0 mm). Median computation time per frame was 179 msec (range, 154–247 msec). Conclusion: AKAZE successfully and quickly detected the target position on kV X-ray fluoroscopic images. Initial results indicate that the differences between 3D tracking and target position would be clinically acceptable.« less

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

Track-structure simulations for charged particles.

PubMed

Dingfelder, Michael

2012-11-01

Monte Carlo track-structure simulations provide a detailed and accurate picture of radiation transport of charged particles through condensed matter of biological interest. Liquid water serves as a surrogate for soft tissue and is used in most Monte Carlo track-structure codes. Basic theories of radiation transport and track-structure simulations are discussed and differences compared to condensed history codes highlighted. Interaction cross sections for electrons, protons, alpha particles, and light and heavy ions are required input data for track-structure simulations. Different calculation methods, including the plane-wave Born approximation, the dielectric theory, and semi-empirical approaches are presented using liquid water as a target. Low-energy electron transport and light ion transport are discussed as areas of special interest.

Forward-backward multiplicity correlations of target fragments in nucleus-emulsion collisions at a few hundred MeV/u

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hai; Chen, Yan-Ling; Wang, Guo-Rong; Li, Wang-Dong; Wang, Qing; Yao, Ji-Jie; Zhou, Jian-Guo; Li, Rong; Li, Jun-Sheng; Li, Hui-Ling

2015-01-01

The forward-backward multiplicity and correlations of a target evaporated fragment (black track particle) and target recoiled proton (grey track particle) emitted from 150 A MeV 4He, 290 A MeV 12C, 400 A MeV 12C, 400 A MeV 20Ne and 500 A MeV 56Fe induced different types of nuclear emulsion target interactions are investigated. It is found that the forward and backward averaged multiplicity of a grey, black and heavily ionized track particle increases with the increase of the target size. The averaged multiplicity of a forward black track particle, backward black track particle, and backward grey track particle do not depend on the projectile size and energy, but the averaged multiplicity of a forward grey track particle increases with an increase of projectile size and energy. The backward grey track particle multiplicity distribution follows an exponential decay law and the decay constant decreases with an increase of target size. The backward-forward multiplicity correlations follow linear law which is independent of the projectile size and energy, and the saturation effect is observed in some heavy target data sets.

Data fusion for target tracking and classification with wireless sensor network

NASA Astrophysics Data System (ADS)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Tracking Subpixel Targets with Critically Sampled Optical Sensors

DTIC Science & Technology

2012-09-01

5 [32]. The Viterbi algorithm is a dynamic programming method for calculating the MAP in O(tn2) time . The most common use of this algorithm is in the... method to detect subpixel point targets using the sensor’s PSF as an identifying characteristic. Using matched filtering theory, a measure is defined to...ocean surface beneath the cloud will have a different distribution. While the basic methods will adapt to changes in cloud cover over time , it is also

Detection and tracking of a moving target using SAR images with the particle filter-based track-before-detect algorithm.

PubMed

Gao, Han; Li, Jingwen

2014-06-19

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.

Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

PubMed Central

Gao, Han; Li, Jingwen

2014-01-01

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

A method for optical ground station reduce alignment error in satellite-ground quantum experiments

NASA Astrophysics Data System (ADS)

He, Dong; Wang, Qiang; Zhou, Jian-Wei; Song, Zhi-Jun; Zhong, Dai-Jun; Jiang, Yu; Liu, Wan-Sheng; Huang, Yong-Mei

2018-03-01

A satellite dedicated for quantum science experiments, has been developed and successfully launched from Jiuquan, China, on August 16, 2016. Two new optical ground stations (OGSs) were built to cooperate with the satellite to complete satellite-ground quantum experiments. OGS corrected its pointing direction by satellite trajectory error to coarse tracking system and uplink beacon sight, therefore fine tracking CCD and uplink beacon optical axis alignment accuracy was to ensure that beacon could cover the quantum satellite in all time when it passed the OGSs. Unfortunately, when we tested specifications of the OGSs, due to the coarse tracking optical system was commercial telescopes, the change of position of the target in the coarse CCD was up to 600μrad along with the change of elevation angle. In this paper, a method of reduce alignment error between beacon beam and fine tracking CCD is proposed. Firstly, OGS fitted the curve of target positions in coarse CCD along with the change of elevation angle. Secondly, OGS fitted the curve of hexapod secondary mirror positions along with the change of elevation angle. Thirdly, when tracking satellite, the fine tracking error unloaded on the real-time zero point position of coarse CCD which computed by the firstly calibration data. Simultaneously the positions of the hexapod secondary mirror were adjusted by the secondly calibration data. Finally the experiment result is proposed. Results show that the alignment error is less than 50μrad.

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

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.

Guided filter and convolutional network based tracking for infrared dim moving target

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Qin, Hanlin; Rong, Shenghui; Zhao, Dong; Du, Juan

2017-09-01

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier's parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.

Advanced cell therapies: targeting, tracking and actuation of cells with magnetic particles.

PubMed

Connell, John J; Patrick, P Stephen; Yu, Yichao; Lythgoe, Mark F; Kalber, Tammy L

2015-01-01

Regenerative medicine would greatly benefit from a new platform technology that enabled measurable, controllable and targeting of stem cells to a site of disease or injury in the body. Superparamagnetic iron-oxide nanoparticles offer attractive possibilities in biomedicine and can be incorporated into cells, affording a safe and reliable means of tagging. This review describes three current and emerging methods to enhance regenerative medicine using magnetic particles to guide therapeutic cells to a target organ; track the cells using MRI and assess their spatial localization with high precision and influence the behavior of the cell using magnetic actuation. This approach is complementary to the systemic injection of cell therapies, thus expanding the horizon of stem cell therapeutics.

Robust Visual Tracking Revisited: From Correlation Filter to Template Matching.

PubMed

Liu, Fanghui; Gong, Chen; Huang, Xiaolin; Zhou, Tao; Yang, Jie; Tao, Dacheng

2018-06-01

In this paper, we propose a novel matching based tracker by investigating the relationship between template matching and the recent popular correlation filter based trackers (CFTs). Compared to the correlation operation in CFTs, a sophisticated similarity metric termed mutual buddies similarity is proposed to exploit the relationship of multiple reciprocal nearest neighbors for target matching. By doing so, our tracker obtains powerful discriminative ability on distinguishing target and background as demonstrated by both empirical and theoretical analyses. Besides, instead of utilizing single template with the improper updating scheme in CFTs, we design a novel online template updating strategy named memory, which aims to select a certain amount of representative and reliable tracking results in history to construct the current stable and expressive template set. This scheme is beneficial for the proposed tracker to comprehensively understand the target appearance variations, recall some stable results. Both qualitative and quantitative evaluations on two benchmarks suggest that the proposed tracking method performs favorably against some recently developed CFTs and other competitive trackers.

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters.

PubMed

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-09-07

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers.

Research of maneuvering target prediction and tracking technology based on IMM algorithm

NASA Astrophysics Data System (ADS)

Cao, Zheng; Mao, Yao; Deng, Chao; Liu, Qiong; Chen, Jing

2016-09-01

Maneuvering target prediction and tracking technology is widely used in both military and civilian applications, the study of those technologies is all along the hotspot and difficulty. In the Electro-Optical acquisition-tracking-pointing system (ATP), the primary traditional maneuvering targets are ballistic target, large aircraft and other big targets. Those targets have the features of fast velocity and a strong regular trajectory and Kalman Filtering and polynomial fitting have good effects when they are used to track those targets. In recent years, the small unmanned aerial vehicles developed rapidly for they are small, nimble and simple operation. The small unmanned aerial vehicles have strong maneuverability in the observation system of ATP although they are close-in, slow and small targets. Moreover, those vehicles are under the manual operation, therefore, the acceleration of them changes greatly and they move erratically. So the prediction and tracking precision is low when traditional algorithms are used to track the maneuvering fly of those targets, such as speeding up, turning, climbing and so on. The interacting multiple model algorithm (IMM) use multiple models to match target real movement trajectory, there are interactions between each model. The IMM algorithm can switch model based on a Markov chain to adapt to the change of target movement trajectory, so it is suitable to solve the prediction and tracking problems of the small unmanned aerial vehicles because of the better adaptability of irregular movement. This paper has set up model set of constant velocity model (CV), constant acceleration model (CA), constant turning model (CT) and current statistical model. And the results of simulating and analyzing the real movement trajectory data of the small unmanned aerial vehicles show that the prediction and tracking technology based on the interacting multiple model algorithm can get relatively lower tracking error and improve tracking precision comparing with traditional algorithms.

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

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

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.

Management of three-dimensional intrafraction motion through real-time DMLC tracking.

PubMed

Sawant, Amit; Venkat, Raghu; Srivastava, Vikram; Carlson, David; Povzner, Sergey; Cattell, Herb; Keall, Paul

2008-05-01

Tumor tracking using a dynamic multileaf collimator (DMLC) represents a promising approach for intrafraction motion management in thoracic and abdominal cancer radiotherapy. In this work, we develop, empirically demonstrate, and characterize a novel 3D tracking algorithm for real-time, conformal, intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT)-based radiation delivery to targets moving in three dimensions. The algorithm obtains real-time information of target location from an independent position monitoring system and dynamically calculates MLC leaf positions to account for changes in target position. Initial studies were performed to evaluate the geometric accuracy of DMLC tracking of 3D target motion. In addition, dosimetric studies were performed on a clinical linac to evaluate the impact of real-time DMLC tracking for conformal, step-and-shoot (S-IMRT), dynamic (D-IMRT), and VMAT deliveries to a moving target. The efficiency of conformal and IMRT delivery in the presence of tracking was determined. Results show that submillimeter geometric accuracy in all three dimensions is achievable with DMLC tracking. Significant dosimetric improvements were observed in the presence of tracking for conformal and IMRT deliveries to moving targets. A gamma index evaluation with a 3%-3 mm criterion showed that deliveries without DMLC tracking exhibit between 1.7 (S-IMRT) and 4.8 (D-IMRT) times more dose points that fail the evaluation compared to corresponding deliveries with tracking. The efficiency of IMRT delivery, as measured in the lab, was observed to be significantly lower in case of tracking target motion perpendicular to MLC leaf travel compared to motion parallel to leaf travel. Nevertheless, these early results indicate that accurate, real-time DMLC tracking of 3D tumor motion is feasible and can potentially result in significant geometric and dosimetric advantages leading to more effective management of intrafraction motion.

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.

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.

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.

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.

Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature

PubMed Central

Li, Zhiyong; Li, Pengfei; Yu, Xiaoping; Hashem, Mervat

2014-01-01

It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches' color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment. PMID:24592185

Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter.

PubMed

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-11-23

The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effect where there exists arbitrary PHD mass shifting in the presence of missed detections. To address this issue in the Gaussian mixture (GM) implementation of the CPHD filter, this paper presents an improved GM-CPHD filter, which incorporates a weight redistribution scheme into the filtering process to modify the updated weights of the Gaussian components when missed detections occur. In addition, an efficient gating strategy that can adaptively adjust the gate sizes according to the number of missed detections of each Gaussian component is also presented to further improve the computational efficiency of the proposed filter. Simulation results demonstrate that the proposed method offers favorable performance in terms of both estimation accuracy and robustness to clutter and detection uncertainty over the existing methods.

Multiple hypothesis tracking for the cyber domain

NASA Astrophysics Data System (ADS)

Schwoegler, Stefan; Blackman, Sam; Holsopple, Jared; Hirsch, Michael J.

2011-09-01

This paper discusses how methods used for conventional multiple hypothesis tracking (MHT) can be extended to domain-agnostic tracking of entities from non-kinematic constraints such as those imposed by cyber attacks in a potentially dense false alarm background. MHT is widely recognized as the premier method to avoid corrupting tracks with spurious data in the kinematic domain but it has not been extensively applied to other problem domains. The traditional approach is to tightly couple track maintenance (prediction, gating, filtering, probabilistic pruning, and target confirmation) with hypothesis management (clustering, incompatibility maintenance, hypothesis formation, and Nassociation pruning). However, by separating the domain specific track maintenance portion from the domain agnostic hypothesis management piece, we can begin to apply the wealth of knowledge gained from ground and air tracking solutions to the cyber (and other) domains. These realizations led to the creation of Raytheon's Multiple Hypothesis Extensible Tracking Architecture (MHETA). In this paper, we showcase MHETA for the cyber domain, plugging in a well established method, CUBRC's INFormation Engine for Real-time Decision making, (INFERD), for the association portion of the MHT. The result is a CyberMHT. We demonstrate the power of MHETA-INFERD using simulated data. Using metrics from both the tracking and cyber domains, we show that while no tracker is perfect, by applying MHETA-INFERD, advanced nonkinematic tracks can be captured in an automated way, perform better than non-MHT approaches, and decrease analyst response time to cyber threats.

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

PubMed

Yun, Sangdoo; Choi, Jongwon; Yoo, Youngjoon; Yun, Kimin; Choi, Jin Young

2018-06-01

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

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

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.

Visuomotor Tracking Ability of Young Adult Speakers.

ERIC Educational Resources Information Center

Moon, Jerald B.; And Others

1993-01-01

Twenty-five normal young adult speakers tracked sinusoidal and unpredictable target signals using lower lip and jaw movement and fundamental frequency modulation. Tracking accuracy varied as a function of target frequency and articulator used to track. Results show the potential of visuomotor tracking tasks in the assessment of speech articulatory…

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

Mark Tracking: Position/orientation measurements using 4-circle mark and its tracking experiments

NASA Technical Reports Server (NTRS)

Kanda, Shinji; Okabayashi, Keijyu; Maruyama, Tsugito; Uchiyama, Takashi

1994-01-01

Future space robots require position and orientation tracking with visual feedback control to track and capture floating objects and satellites. We developed a four-circle mark that is useful for this purpose. With this mark, four geometric center positions as feature points can be extracted from the mark by simple image processing. We also developed a position and orientation measurement method that uses the four feature points in our mark. The mark gave good enough image measurement accuracy to let space robots approach and contact objects. A visual feedback control system using this mark enabled a robot arm to track a target object accurately. The control system was able to tolerate a time delay of 2 seconds.

An eye-tracking paradigm for analyzing the processing time of sentences with different linguistic complexities.

PubMed

Wendt, Dorothea; Brand, Thomas; Kollmeier, Birger

2014-01-01

An eye-tracking paradigm was developed for use in audiology in order to enable online analysis of the speech comprehension process. This paradigm should be useful in assessing impediments in speech processing. In this paradigm, two scenes, a target picture and a competitor picture, were presented simultaneously with an aurally presented sentence that corresponded to the target picture. At the same time, eye fixations were recorded using an eye-tracking device. The effect of linguistic complexity on language processing time was assessed from eye fixation information by systematically varying linguistic complexity. This was achieved with a sentence corpus containing seven German sentence structures. A novel data analysis method computed the average tendency to fixate the target picture as a function of time during sentence processing. This allowed identification of the point in time at which the participant understood the sentence, referred to as the decision moment. Systematic differences in processing time were observed as a function of linguistic complexity. These differences in processing time may be used to assess the efficiency of cognitive processes involved in resolving linguistic complexity. Thus, the proposed method enables a temporal analysis of the speech comprehension process and has potential applications in speech audiology and psychoacoustics.

An Eye-Tracking Paradigm for Analyzing the Processing Time of Sentences with Different Linguistic Complexities

PubMed Central

Wendt, Dorothea; Brand, Thomas; Kollmeier, Birger

2014-01-01

An eye-tracking paradigm was developed for use in audiology in order to enable online analysis of the speech comprehension process. This paradigm should be useful in assessing impediments in speech processing. In this paradigm, two scenes, a target picture and a competitor picture, were presented simultaneously with an aurally presented sentence that corresponded to the target picture. At the same time, eye fixations were recorded using an eye-tracking device. The effect of linguistic complexity on language processing time was assessed from eye fixation information by systematically varying linguistic complexity. This was achieved with a sentence corpus containing seven German sentence structures. A novel data analysis method computed the average tendency to fixate the target picture as a function of time during sentence processing. This allowed identification of the point in time at which the participant understood the sentence, referred to as the decision moment. Systematic differences in processing time were observed as a function of linguistic complexity. These differences in processing time may be used to assess the efficiency of cognitive processes involved in resolving linguistic complexity. Thus, the proposed method enables a temporal analysis of the speech comprehension process and has potential applications in speech audiology and psychoacoustics. PMID:24950184

A computer program to determine the possible daily release window for sky target experiments

NASA Technical Reports Server (NTRS)

Michaud, N. H.

1973-01-01

A computer program is presented which is designed to determine the daily release window for sky target experiments. Factors considered in the program include: (1) target illumination by the sun at release time and during the tracking period; (2) look angle elevation above local horizon from each tracking station to the target; (3) solar depression angle from the local horizon of each tracking station during the experimental period after target release; (4) lunar depression angle from the local horizon of each tracking station during the experimental period after target release; and (5) total sky background brightness as seen from each tracking station while viewing the target. Program output is produced in both graphic and data form. Output data can be plotted for a single calendar month or year. The numerical values used to generate the plots are furnished to permit a more detailed review of the computed daily release windows.

Quantitative evaluation for accumulative calibration error and video-CT registration errors in electromagnetic-tracked endoscopy.

PubMed

Liu, Sheena Xin; Gutiérrez, Luis F; Stanton, Doug

2011-05-01

Electromagnetic (EM)-guided endoscopy has demonstrated its value in minimally invasive interventions. Accuracy evaluation of the system is of paramount importance to clinical applications. Previously, a number of researchers have reported the results of calibrating the EM-guided endoscope; however, the accumulated errors of an integrated system, which ultimately reflect intra-operative performance, have not been characterized. To fill this vacancy, we propose a novel system to perform this evaluation and use a 3D metric to reflect the intra-operative procedural accuracy. This paper first presents a portable design and a method for calibration of an electromagnetic (EM)-tracked endoscopy system. An evaluation scheme is then described that uses the calibration results and EM-CT registration to enable real-time data fusion between CT and endoscopic video images. We present quantitative evaluation results for estimating the accuracy of this system using eight internal fiducials as the targets on an anatomical phantom: the error is obtained by comparing the positions of these targets in the CT space, EM space and endoscopy image space. To obtain 3D error estimation, the 3D locations of the targets in the endoscopy image space are reconstructed from stereo views of the EM-tracked monocular endoscope. Thus, the accumulated errors are evaluated in a controlled environment, where the ground truth information is present and systematic performance (including the calibration error) can be assessed. We obtain the mean in-plane error to be on the order of 2 pixels. To evaluate the data integration performance for virtual navigation, target video-CT registration error (TRE) is measured as the 3D Euclidean distance between the 3D-reconstructed targets of endoscopy video images and the targets identified in CT. The 3D error (TRE) encapsulates EM-CT registration error, EM-tracking error, fiducial localization error, and optical-EM calibration error. We present in this paper our calibration method and a virtual navigation evaluation system for quantifying the overall errors of the intra-operative data integration. We believe this phantom not only offers us good insights to understand the systematic errors encountered in all phases of an EM-tracked endoscopy procedure but also can provide quality control of laboratory experiments for endoscopic procedures before the experiments are transferred from the laboratory to human subjects.

Enhancement of tracking performance in electro-optical system based on servo control algorithm

NASA Astrophysics Data System (ADS)

Choi, WooJin; Kim, SungSu; Jung, DaeYoon; Seo, HyoungKyu

2017-10-01

Modern electro-optical surveillance and reconnaissance systems require tracking capability to get exact images of target or to accurately direct the line of sight to target which is moving or still. This leads to the tracking system composed of image based tracking algorithm and servo control algorithm. In this study, we focus on the servo control function to minimize the overshoot in the tracking motion and do not miss the target. The scheme is to limit acceleration and velocity parameters in the tracking controller, depending on the target state information in the image. We implement the proposed techniques by creating a system model of DIRCM and simulate the same environment, validate the performance on the actual equipment.

Small Infrared Target Detection by Region-Adaptive Clutter Rejection for Sea-Based Infrared Search and Track

PubMed Central

Kim, Sungho; Lee, Joohyoung

2014-01-01

This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate. PMID:25054633

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

Targeted and untargeted-metabolite profiling to track the compositional integrity of ginger during processing using digitally-enhanced HPTLC pattern recognition analysis.

PubMed

Ibrahim, Reham S; Fathy, Hoda

2018-03-30

Tracking the impact of commonly applied post-harvesting and industrial processing practices on the compositional integrity of ginger rhizome was implemented in this work. Untargeted metabolite profiling was performed using digitally-enhanced HPTLC method where the chromatographic fingerprints were extracted using ImageJ software then analysed with multivariate Principal Component Analysis (PCA) for pattern recognition. A targeted approach was applied using a new, validated, simple and fast HPTLC image analysis method for simultaneous quantification of the officially recognized markers 6-, 8-, 10-gingerol and 6-shogaol in conjunction with chemometric Hierarchical Clustering Analysis (HCA). The results of both targeted and untargeted metabolite profiling revealed that peeling, drying in addition to storage employed during processing have a great influence on ginger chemo-profile, the different forms of processed ginger shouldn't be used interchangeably. Moreover, it deemed necessary to consider the holistic metabolic profile for comprehensive evaluation of ginger during processing. Copyright © 2018. Published by Elsevier B.V.

A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

PubMed Central

Wang, Xuedong; Sun, Shudong; Corchado, Juan M.

2017-01-01

We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management. PMID:29168772

How facial attractiveness affects sustained attention.

PubMed

Li, Jie; Oksama, Lauri; Hyönä, Jukka

2016-10-01

The present study investigated whether and how facial attractiveness affects sustained attention. We adopted a multiple-identity tracking paradigm, using attractive and unattractive faces as stimuli. Participants were required to track moving target faces amid distractor faces and report the final location of each target. In Experiment 1, the attractive and unattractive faces differed in both the low-level properties (i.e., luminance, contrast, and color saturation) and high-level properties (i.e., physical beauty and age). The results showed that the attractiveness of both the target and distractor faces affected the tracking performance: The attractive target faces were tracked better than the unattractive target faces; when the targets and distractors were both unattractive male faces, the tracking performance was poorer than when they were of different attractiveness. In Experiment 2, the low-level properties of the facial images were equalized. The results showed that the attractive target faces were still tracked better than unattractive targets while the effects related to distractor attractiveness ceased to exist. Taken together, the results indicate that during attentional tracking the high-level properties related to the attractiveness of the target faces can be automatically processed, and then they can facilitate the sustained attention on the attractive targets, either with or without the supplement of low-level properties. On the other hand, only low-level properties of the distractor faces can be processed. When the distractors share similar low-level properties with the targets, they can be grouped together, so that it would be more difficult to sustain attention on the individual targets. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Along-track calibration of SWIR push-broom hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Jemec, Jurij; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran

2016-05-01

Push-broom hyperspectral imaging systems are increasingly used for various medical, agricultural and military purposes. The acquired images contain spectral information in every pixel of the imaged scene collecting additional information about the imaged scene compared to the classical RGB color imaging. Due to the misalignment and imperfections in the optical components comprising the push-broom hyperspectral imaging system, variable spectral and spatial misalignments and blur are present in the acquired images. To capture these distortions, a spatially and spectrally variant response function must be identified at each spatial and spectral position. In this study, we propose a procedure to characterize the variant response function of Short-Wavelength Infrared (SWIR) push-broom hyperspectral imaging systems in the across-track and along-track direction and remove its effect from the acquired images. A custom laser-machined spatial calibration targets are used for the characterization. The spatial and spectral variability of the response function in the across-track and along-track direction is modeled by a parametrized basis function. Finally, the characterization results are used to restore the distorted hyperspectral images in the across-track and along-track direction by a Richardson-Lucy deconvolution-based algorithm. The proposed calibration method in the across-track and along-track direction is thoroughly evaluated on images of targets with well-defined geometric properties. The results suggest that the proposed procedure is well suited for fast and accurate spatial calibration of push-broom hyperspectral imaging systems.

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

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

Xu, Z; Wang, I; Yao, R

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans andmore » then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.« less

Research on regional intrusion prevention and control system based on target tracking

NASA Astrophysics Data System (ADS)

Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

2017-08-01

In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Direction information in multiple object tracking is limited by a graded resource.

PubMed

Horowitz, Todd S; Cohen, Michael A

2010-10-01

Is multiple object tracking (MOT) limited by a fixed set of structures (slots), a limited but divisible resource, or both? Here, we answer this question by measuring the precision of the direction representation for tracked targets. The signature of a limited resource is a decrease in precision as the square root of the tracking load. The signature of fixed slots is a fixed precision. Hybrid models predict a rapid decrease to asymptotic precision. In two experiments, observers tracked moving disks and reported target motion direction by adjusting a probe arrow. We derived the precision of representation of correctly tracked targets using a mixture distribution analysis. Precision declined with target load according to the square-root law up to six targets. This finding is inconsistent with both pure and hybrid slot models. Instead, directional information in MOT appears to be limited by a continuously divisible resource.

Tracking, aiming, and hitting the UAV with ordinary assault rifle

NASA Astrophysics Data System (ADS)

Racek, František; Baláž, Teodor; Krejčí, Jaroslav; Procházka, Stanislav; Macko, Martin

2017-10-01

The usage small-unmanned aerial vehicles (UAVs) is significantly increasing nowadays. They are being used as a carrier of military spy and reconnaissance devices (taking photos, live video streaming and so on), or as a carrier of potentially dangerous cargo (intended for destruction and killing). Both ways of utilizing the UAV cause the necessity to disable it. From the military point of view, to disable the UAV means to bring it down by a weapon of an ordinary soldier that is the assault rifle. This task can be challenging for the soldier because he needs visually detect and identify the target, track the target visually and aim on the target. The final success of the soldier's mission depends not only on the said visual tasks, but also on the properties of the weapon and ammunition. The paper deals with possible methods of prediction of probability of hitting the UAV targets.

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.

Proof-of-concept of a laser mounted endoscope for touch-less navigated procedures

PubMed Central

Kral, Florian; Gueler, Oezguer; Perwoeg, Martina; Bardosi, Zoltan; Puschban, Elisabeth J; Riechelmann, Herbert; Freysinger, Wolfgang

2013-01-01

Background and Objectives During navigated procedures a tracked pointing device is used to define target structures in the patient to visualize its position in a registered radiologic data set. When working with endoscopes in minimal invasive procedures, the target region is often difficult to reach and changing instruments is disturbing in a challenging, crucial moment of the procedure. We developed a device for touch less navigation during navigated endoscopic procedures. Materials and Methods A laser beam is delivered to the tip of a tracked endoscope angled to its axis. Thereby the position of the laser spot in the video-endoscopic images changes according to the distance between the tip of the endoscope and the target structure. A mathematical function is defined by a calibration process and is used to calculate the distance between the tip of the endoscope and the target. The tracked tip of the endoscope and the calculated distance is used to visualize the laser spot in the registered radiologic data set. Results In comparison to the tracked instrument, the touch less target definition with the laser spot yielded in an over and above error of 0.12 mm. The overall application error in this experimental setup with a plastic head was 0.61 ± 0.97 mm (95% CI −1.3 to +2.5 mm). Conclusion Integrating a laser in an endoscope and then calculating the distance to a target structure by image processing of the video endoscopic images is accurate. This technology eliminates the need for tracked probes intraoperatively and therefore allows navigation to be integrated seamlessly in clinical routine. However, it is an additional chain link in the sequence of computer-assisted surgery thus influencing the application error. Lasers Surg. Med. 45:377–382, 2013. © 2013 Wiley Periodicals, Inc. PMID:23737122

Robust visual tracking using a contextual boosting approach

NASA Astrophysics Data System (ADS)

Jiang, Wanyue; Wang, Yin; Wang, Daobo

2018-03-01

In recent years, detection-based image trackers have been gaining ground rapidly, thanks to its capacity of incorporating a variety of image features. Nevertheless, its tracking performance might be compromised if background regions are mislabeled as foreground in the training process. To resolve this problem, we propose an online visual tracking algorithm designated to improving the training label accuracy in the learning phase. In the proposed method, superpixels are used as samples, and their ambiguous labels are reassigned in accordance with both prior estimation and contextual information. The location and scale of the target are usually determined by confidence map, which is doomed to shrink since background regions are always incorporated into the bounding box. To address this dilemma, we propose a cross projection scheme via projecting the confidence map for target detecting. Moreover, the performance of the proposed tracker can be further improved by adding rigid-structured information. The proposed method is evaluated on the basis of the OTB benchmark and the VOT2016 benchmark. Compared with other trackers, the results appear to be competitive.

OpenCV and TYZX : video surveillance for tracking.

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

He, Jim; Spencer, Andrew; Chu, Eric

2008-08-01

As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processingmore » solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition.« less

New platform for evaluating ultrasound-guided interventional technologies

NASA Astrophysics Data System (ADS)

Kim, Younsu; Guo, Xiaoyu; Boctor, Emad M.

2016-04-01

Ultrasound-guided needle tracking systems are frequently used in surgical procedures. Various needle tracking technologies have been developed using ultrasound, electromagnetic sensors, and optical sensors. To evaluate these new needle tracking technologies, 3D volume information is often acquired to compute the actual distance from the needle tip to the target object. The image-guidance conditions for comparison are often inconsistent due to the ultrasound beam-thickness. Since 3D volumes are necessary, there is often some time delay between the surgical procedure and the evaluation. These evaluation methods will generally only measure the final needle location because they interrupt the surgical procedure. The main contribution of this work is a new platform for evaluating needle tracking systems in real-time, resolving the problems stated above. We developed new tools to evaluate the precise distance between the needle tip and the target object. A PZT element transmitting unit is designed as needle introducer shape so that it can be inserted in the needle. We have collected time of flight and amplitude information in real-time. We propose two systems to collect ultrasound signals. We demonstrate this platform on an ultrasound DAQ system and a cost-effective FPGA board. The results of a chicken breast experiment show the feasibility of tracking a time series of needle tip distances. We performed validation experiments with a plastisol phantom and have shown that the preliminary data fits a linear regression model with a RMSE of less than 0.6mm. Our platform can be applied to more general needle tracking methods using other forms of guidance.

A flight test method for pilot/aircraft analysis

NASA Technical Reports Server (NTRS)

Koehler, R.; Buchacker, E.

1986-01-01

In high precision flight maneuvres a pilot is a part of a closed loop pilot/aircraft system. The assessment of the flying qualities is highly dependent on the closed loop characteristics related to precision maneuvres like approach, landing, air-to-air tracking, air-to-ground tracking, close formation flying and air-to air refueling of the receiver. The object of a research program at DFVLR is the final flight phase of an air to ground mission. In this flight phase the pilot has to align the aircraft with the target, correct small deviations from the target direction and keep the target in his sights for a specific time period. To investigate the dynamic behavior of the pilot-aircraft system a special ground attack flight test technique with a prolonged tracking maneuvres was developed. By changing the targets during the attack the pilot is forced to react continously on aiming errors in his sights. Thus the closed loop pilot/aircraft system is excited over a wide frequency range of interest, the pilot gets more information about mission oriented aircraft dynamics and suitable flight test data for a pilot/aircraft analysis can be generated.

Neural mechanisms tracking popularity in real-world social networks.

PubMed

Zerubavel, Noam; Bearman, Peter S; Weber, Jochen; Ochsner, Kevin N

2015-12-08

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.

Space-based infrared scanning sensor LOS determination and calibration using star observation

NASA Astrophysics Data System (ADS)

Chen, Jun; Xu, Zhan; An, Wei; Deng, Xin-Pu; Yang, Jun-Gang

2015-10-01

This paper provides a novel methodology for removing sensor bias from a space based infrared (IR) system (SBIRS) through the use of stars detected in the background field of the sensor. Space based IR system uses the LOS (line of sight) of target for target location. LOS determination and calibration is the key precondition of accurate location and tracking of targets in Space based IR system and the LOS calibration of scanning sensor is one of the difficulties. The subsequent changes of sensor bias are not been taking into account in the conventional LOS determination and calibration process. Based on the analysis of the imaging process of scanning sensor, a theoretical model based on the estimation of bias angles using star observation is proposed. By establishing the process model of the bias angles and the observation model of stars, using an extended Kalman filter (EKF) to estimate the bias angles, and then calibrating the sensor LOS. Time domain simulations results indicate that the proposed method has a high precision and smooth performance for sensor LOS determination and calibration. The timeliness and precision of target tracking process in the space based infrared (IR) tracking system could be met with the proposed algorithm.

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.

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

Potential benefits of dosimetric VMAT tracking verified with 3D film measurements.

PubMed

Crijns, Wouter; Defraene, Gilles; Van Herck, Hans; Depuydt, Tom; Haustermans, Karin; Maes, Frederik; Van den Heuvel, Frank

2016-05-01

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. 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 EBT3 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. 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. 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.

Measuring zebrafish turning rate.

PubMed

Mwaffo, Violet; Butail, Sachit; di Bernardo, Mario; Porfiri, Maurizio

2015-06-01

Zebrafish is becoming a popular animal model in preclinical research, and zebrafish turning rate has been proposed for the analysis of activity in several domains. The turning rate is often estimated from the trajectory of the fish centroid that is output by commercial or custom-made target tracking software run on overhead videos of fish swimming. However, the accuracy of such indirect methods with respect to the turning rate associated with changes in heading during zebrafish locomotion is largely untested. Here, we compare two indirect methods for the turning rate estimation using the centroid velocity or position data, with full shape tracking for three different video sampling rates. We use tracking data from the overhead video recorded at 60, 30, and 15 frames per second of zebrafish swimming in a shallow water tank. Statistical comparisons of absolute turning rate across methods and sampling rates indicate that, while indirect methods are indistinguishable from full shape tracking, the video sampling rate significantly influences the turning rate measurement. The results of this study can aid in the selection of the video capture frame rate, an experimental design parameter in zebrafish behavioral experiments where activity is an important measure.

Trajectory Control of Rendezvous with Maneuver Target Spacecraft

NASA Technical Reports Server (NTRS)

Zhou, Zhinqiang

2012-01-01

In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.

On the internal target model in a tracking task

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Baron, S.

1981-01-01

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Automated 3D trajectory measuring of large numbers of moving particles.

PubMed

Wu, Hai Shan; Zhao, Qi; Zou, Danping; Chen, Yan Qiu

2011-04-11

Complex dynamics of natural particle systems, such as insect swarms, bird flocks, fish schools, has attracted great attention of scientists for years. Measuring 3D trajectory of each individual in a group is vital for quantitative study of their dynamic properties, yet such empirical data is rare mainly due to the challenges of maintaining the identities of large numbers of individuals with similar visual features and frequent occlusions. We here present an automatic and efficient algorithm to track 3D motion trajectories of large numbers of moving particles using two video cameras. Our method solves this problem by formulating it as three linear assignment problems (LAP). For each video sequence, the first LAP obtains 2D tracks of moving targets and is able to maintain target identities in the presence of occlusions; the second one matches the visually similar targets across two views via a novel technique named maximum epipolar co-motion length (MECL), which is not only able to effectively reduce matching ambiguity but also further diminish the influence of frequent occlusions; the last one links 3D track segments into complete trajectories via computing a globally optimal assignment based on temporal and kinematic cues. Experiment results on simulated particle swarms with various particle densities validated the accuracy and robustness of the proposed method. As real-world case, our method successfully acquired 3D flight paths of fruit fly (Drosophila melanogaster) group comprising hundreds of freely flying individuals. © 2011 Optical Society of America

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

The new approach for infrared target tracking based on the particle filter algorithm

NASA Astrophysics Data System (ADS)

Sun, Hang; Han, Hong-xia

2011-08-01

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework .Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation, and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value .Last because of the gray and fusion target motion information, this approach also inhibit interference from the background, ultimately improve the stability and the real-time of the target track.

Attentional enhancement during multiple-object tracking.

PubMed

Drew, Trafton; McCollough, Andrew W; Horowitz, Todd S; Vogel, Edward K

2009-04-01

What is the role of attention in multiple-object tracking? Does attention enhance target representations, suppress distractor representations, or both? It is difficult to ask this question in a purely behavioral paradigm without altering the very attentional allocation one is trying to measure. In the present study, we used event-related potentials to examine the early visual evoked responses to task-irrelevant probes without requiring an additional detection task. Subjects tracked two targets among four moving distractors and four stationary distractors. Brief probes were flashed on targets, moving distractors, stationary distractors, or empty space. We obtained a significant enhancement of the visually evoked P1 and N1 components (approximately 100-150 msec) for probes on targets, relative to distractors. Furthermore, good trackers showed larger differences between target and distractor probes than did poor trackers. These results provide evidence of early attentional enhancement of tracked target items and also provide a novel approach to measuring attentional allocation during tracking.

Feature aided Monte Carlo probabilistic data association filter for ballistic missile tracking

NASA Astrophysics Data System (ADS)

Ozdemir, Onur; Niu, Ruixin; Varshney, Pramod K.; Drozd, Andrew L.; Loe, Richard

2011-05-01

The problem of ballistic missile tracking in the presence of clutter is investigated. Probabilistic data association filter (PDAF) is utilized as the basic filtering algorithm. We propose to use sequential Monte Carlo methods, i.e., particle filters, aided with amplitude information (AI) in order to improve the tracking performance of a single target in clutter when severe nonlinearities exist in the system. We call this approach "Monte Carlo probabilistic data association filter with amplitude information (MCPDAF-AI)." Furthermore, we formulate a realistic problem in the sense that we use simulated radar cross section (RCS) data for a missile warhead and a cylinder chaff using Lucernhammer1, a state of the art electromagnetic signature prediction software, to model target and clutter amplitude returns as additional amplitude features which help to improve data association and tracking performance. A performance comparison is carried out between the extended Kalman filter (EKF) and the particle filter under various scenarios using single and multiple sensors. The results show that, when only one sensor is used, the MCPDAF performs significantly better than the EKF in terms of tracking accuracy under severe nonlinear conditions for ballistic missile tracking applications. However, when the number of sensors is increased, even under severe nonlinear conditions, the EKF performs as well as the MCPDAF.

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.

Performance Characteristics of qPCR Assays Targeting Human- and Ruminant-Associated Bacteroidetes for Microbial Source Tracking across Sixteen Countries on Six Continents

PubMed Central

2013-01-01

Numerous quantitative PCR assays for microbial fecal source tracking (MST) have been developed and evaluated in recent years. Widespread application has been hindered by a lack of knowledge regarding the geographical stability and hence applicability of such methods beyond the regional level. This study assessed the performance of five previously reported quantitative PCR assays targeting human-, cattle-, or ruminant-associated Bacteroidetes populations on 280 human and animal fecal samples from 16 countries across six continents. The tested cattle-associated markers were shown to be ruminant-associated. The quantitative distributions of marker concentrations in target and nontarget samples proved to be essential for the assessment of assay performance and were used to establish a new metric for quantitative source-specificity. In general, this study demonstrates that stable target populations required for marker-based MST occur around the globe. Ruminant-associated marker concentrations were strongly correlated with total intestinal Bacteroidetes populations and with each other, indicating that the detected ruminant-associated populations seem to be part of the intestinal core microbiome of ruminants worldwide. Consequently tested ruminant-targeted assays appear to be suitable quantitative MST tools beyond the regional level while the targeted human-associated populations seem to be less prevalent and stable, suggesting potential for improvements in human-targeted methods. PMID:23755882

The development of a 4D treatment planning methodology to simulate the tracking of central lung tumors in an MRI-linac.

PubMed

Al-Ward, Shahad M; Kim, Anthony; McCann, Claire; Ruschin, Mark; Cheung, Patrick; Sahgal, Arjun; Keller, Brian M

2018-01-01

Targeting and tracking of central lung tumors may be feasible on the Elekta MRI-linac (MRL) due to the soft-tissue visualization capabilities of MRI. The purpose of this work is to develop a novel treatment planning methodology to simulate tracking of central lung tumors with the MRL and to quantify the benefits in OAR sparing compared with the ITV approach. Full 4D-CT datasets for five central lung cancer patients were selected to simulate the condition of having 4D-pseudo-CTs derived from 4D-MRI data available on the MRL with real-time tracking capabilities. We used the MRL treatment planning system to generate two plans: (a) with a set of MLC-defined apertures around the target at each phase of the breathing ("4D-MRL" method); (b) with a fixed set of fields encompassing the maximum inhale and exhale of the breathing cycle ("ITV" method). For both plans, dose accumulation was performed onto a reference phase. To further study the potential benefits of a 4D-MRL method, the results were stratified by tumor motion amplitude, OAR-to-tumor proximity, and the relative OAR motion (ROM). With the 4D-MRL method, the reduction in mean doses was up to 3.0 Gy and 1.9 Gy for the heart and the lung. Moreover, the lung's V12.5 Gy was spared by a maximum of 300 cc. Maximum doses to serial organs were reduced by up to 6.1 Gy, 1.5 Gy, and 9.0 Gy for the esophagus, spinal cord, and the trachea, respectively. OAR dose reduction with our method depended on the tumor motion amplitude and the ROM. Some OARs with large ROMs and in close proximity to the tumor benefited from tracking despite small tumor amplitudes. We developed a novel 4D tracking methodology for the MRL for central lung tumors and quantified the potential dosimetric benefits compared with our current ITV approach. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Design of tracking and detecting lens system by diffractive optical method

NASA Astrophysics Data System (ADS)

Yang, Jiang; Qi, Bo; Ren, Ge; Zhou, Jianwei

2016-10-01

Many target-tracking applications require an optical system to acquire the target for tracking and identification. This paper describes a new detecting optical system that can provide automatic flying object detecting, tracking and measuring in visible band. The main feature of the detecting lens system is the combination of diffractive optics with traditional lens design by a technique was invented by Schupmann. Diffractive lens has great potential for developing the larger aperture and lightweight lens. First, the optical system scheme was described. Then the Schupmann achromatic principle with diffractive lens and corrective optics is introduced. According to the technical features and requirements of the optical imaging system for detecting and tracking, we designed a lens system with flat surface Fresnel lens and cancels the optical system chromatic aberration by another flat surface Fresnel lens with effective focal length of 1980mm, an F-Number of F/9.9 and a field of view of 2ωω = 14.2', spatial resolution of 46 lp/mm and a working wavelength range of 0.6 0.85um. At last, the system is compact and easy to fabricate and assembly, the diffuse spot size and MTF function and other analysis provide good performance.

Poly (dopamine) coated superparamagnetic iron oxide nanocluster for noninvasive labeling, tracking, and targeted delivery of adipose tissue-derived stem cells.

PubMed

Liao, Naishun; Wu, Ming; Pan, Fan; Lin, Jiumao; Li, Zuanfang; Zhang, Da; Wang, Yingchao; Zheng, Youshi; Peng, Jun; Liu, Xiaolong; Liu, Jingfeng

2016-01-05

Tracking and monitoring of cells in vivo after transplantation can provide crucial information for stem cell therapy. Magnetic resonance imaging (MRI) combined with contrast agents is believed to be an effective and non-invasive technique for cell tracking in living bodies. However, commercial superparamagnetic iron oxide nanoparticles (SPIONs) applied to label cells suffer from shortages such as potential toxicity, low labeling efficiency, and low contrast enhancing. Herein, the adipose tissue-derived stem cells (ADSCs) were efficiently labeled with SPIONs coated with poly (dopamine) (SPIONs cluster@PDA), without affecting their viability, proliferation, apoptosis, surface marker expression, as well as their self-renew ability and multi-differentiation potential. The labeled cells transplanted into the mice through tail intravenous injection exhibited a negative enhancement of the MRI signal in the damaged liver-induced by carbon tetrachloride, and subsequently these homed ADSCs with SPIONs cluster@PDA labeling exhibited excellent repair effects to the damaged liver. Moreover, the enhanced target-homing to tissue of interest and repair effects of SPIONs cluster@PDA-labeled ADSCs could be achieved by use of external magnetic field in the excisional skin wound mice model. Therefore, we provide a facile, safe, noninvasive and sensitive method for external magnetic field targeted delivery and MRI based tracking of transplanted cells in vivo.

Poly (dopamine) coated superparamagnetic iron oxide nanocluster for noninvasive labeling, tracking, and targeted delivery of adipose tissue-derived stem cells

NASA Astrophysics Data System (ADS)

Liao, Naishun; Wu, Ming; Pan, Fan; Lin, Jiumao; Li, Zuanfang; Zhang, Da; Wang, Yingchao; Zheng, Youshi; Peng, Jun; Liu, Xiaolong; Liu, Jingfeng

2016-01-01

Tracking and monitoring of cells in vivo after transplantation can provide crucial information for stem cell therapy. Magnetic resonance imaging (MRI) combined with contrast agents is believed to be an effective and non-invasive technique for cell tracking in living bodies. However, commercial superparamagnetic iron oxide nanoparticles (SPIONs) applied to label cells suffer from shortages such as potential toxicity, low labeling efficiency, and low contrast enhancing. Herein, the adipose tissue-derived stem cells (ADSCs) were efficiently labeled with SPIONs coated with poly (dopamine) (SPIONs cluster@PDA), without affecting their viability, proliferation, apoptosis, surface marker expression, as well as their self-renew ability and multi-differentiation potential. The labeled cells transplanted into the mice through tail intravenous injection exhibited a negative enhancement of the MRI signal in the damaged liver-induced by carbon tetrachloride, and subsequently these homed ADSCs with SPIONs cluster@PDA labeling exhibited excellent repair effects to the damaged liver. Moreover, the enhanced target-homing to tissue of interest and repair effects of SPIONs cluster@PDA-labeled ADSCs could be achieved by use of external magnetic field in the excisional skin wound mice model. Therefore, we provide a facile, safe, noninvasive and sensitive method for external magnetic field targeted delivery and MRI based tracking of transplanted cells in vivo.

Strong Tracking Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-03-31

Conventional spherical simplex-radial cubature Kalman filter (SSRCKF) for maneuvering target tracking may decline in accuracy and even diverge when a target makes abrupt state changes. To overcome this problem, a novel algorithm named strong tracking spherical simplex-radial cubature Kalman filter (STSSRCKF) is proposed in this paper. The proposed algorithm uses the spherical simplex-radial (SSR) rule to obtain a higher accuracy than cubature Kalman filter (CKF) algorithm. Meanwhile, by introducing strong tracking filter (STF) into SSRCKF and modifying the predicted states' error covariance with a time-varying fading factor, the gain matrix is adjusted on line so that the robustness of the filter and the capability of dealing with uncertainty factors is improved. In this way, the proposed algorithm has the advantages of both STF's strong robustness and SSRCKF's high accuracy. Finally, a maneuvering target tracking problem with abrupt state changes is used to test the performance of the proposed filter. Simulation results show that the STSSRCKF algorithm can get better estimation accuracy and greater robustness for maneuvering target tracking.

Strong Tracking Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

Conventional spherical simplex-radial cubature Kalman filter (SSRCKF) for maneuvering target tracking may decline in accuracy and even diverge when a target makes abrupt state changes. To overcome this problem, a novel algorithm named strong tracking spherical simplex-radial cubature Kalman filter (STSSRCKF) is proposed in this paper. The proposed algorithm uses the spherical simplex-radial (SSR) rule to obtain a higher accuracy than cubature Kalman filter (CKF) algorithm. Meanwhile, by introducing strong tracking filter (STF) into SSRCKF and modifying the predicted states’ error covariance with a time-varying fading factor, the gain matrix is adjusted on line so that the robustness of the filter and the capability of dealing with uncertainty factors is improved. In this way, the proposed algorithm has the advantages of both STF’s strong robustness and SSRCKF’s high accuracy. Finally, a maneuvering target tracking problem with abrupt state changes is used to test the performance of the proposed filter. Simulation results show that the STSSRCKF algorithm can get better estimation accuracy and greater robustness for maneuvering target tracking. PMID:28362347

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target.

PubMed

Yin, Fang; Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-03-28

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target

PubMed Central

Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-01-01

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method. PMID:29597323

Tracking Accuracy of a Real-Time Fiducial Tracking System for Patient Positioning and Monitoring in Radiation Therapy

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

Shchory, Tal; Schifter, Dan; Lichtman, Rinat

Purpose: In radiation therapy there is a need to accurately know the location of the target in real time. A novel radioactive tracking technology has been developed to answer this need. The technology consists of a radioactive implanted fiducial marker designed to minimize migration and a linac mounted tracking device. This study measured the static and dynamic accuracy of the new tracking technology in a clinical radiation therapy environment. Methods and Materials: The tracking device was installed on the linac gantry. The radioactive marker was located in a tissue equivalent phantom. Marker location was measured simultaneously by the radioactive trackingmore » system and by a Microscribe G2 coordinate measuring machine (certified spatial accuracy of 0.38 mm). Localization consistency throughout a volume and absolute accuracy in the Fixed coordinate system were measured at multiple gantry angles over volumes of at least 10 cm in diameter centered at isocenter. Dynamic accuracy was measured with the marker located inside a breathing phantom. Results: The mean consistency for the static source was 0.58 mm throughout the tested region at all measured gantry angles. The mean absolute position error in the Fixed coordinate system for all gantry angles was 0.97 mm. The mean real-time tracking error for the dynamic source within the breathing phantom was less than 1 mm. Conclusions: This novel radioactive tracking technology has the potential to be useful in accurate target localization and real-time monitoring for radiation therapy.« less

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

Yewondwossen, M; Robar, J; Parsons, D

Purpose: During radiotherapy treatment, lung tumors can display substantial respiratory motion. This motion usually necessitates enlarged treatment margins to provide full tumour coverage. Unfortunately, these margins limit the dose that can be prescribed for tumour control and cause complications to normal tissue. Options for real-time methods of direct detection of tumour position, and particularly those that obviate the need for inserted fiducial markers, are limited. We propose a method of tumor tracking without implanted fiducial markers using a novel fast switching-target that toggles between a FFF copper/tungsten therapy mode and a FFF low-Z target mode for imaging. In this workmore » we demonstrate proof-of-concept of this new technology. Methods: The prototype includes two targets: i) a FFF copper/tungsten target equivalent to that in the Varian 2100 EX 6 MV, and ii) a low-Z (carbon) target with a thickness of 110% of continuous slowing down approximation range (CSDA) at 7 MeV. The two targets can be exchanged with a custom made linear slide and motor-driven actuator. The usefulness of the switching-target concept is demonstrated through experimental BEV Planar images acquired with continual treatment and imaging at a user-defined period. Results: The prototype switching-target demonstrates that two recent advances in linac technology (FFF target for therapy and low-Z target) can be combined with synergy. The switching-target approach offers the capacity for rapid switching between treatment and high-contrast imaging modes, allowing intrafractional tracking, as demonstrated in this work with dynamic breathing phantom. By using a single beam-line, the design is streamlined and may obviate the need for an auxiliary imaging system (e.g., kV OBI.) Conclusion: This switching-target approach is a feasible combination of two current advances in linac technology (FFF target for therapy and a FFF low-Z target) allowing new options in on-line IGRT.« less

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters

PubMed Central

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-01-01

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers. PMID:27618046

4D Optimization of Scanned Ion Beam Tracking Therapy for Moving Tumors

PubMed Central

Eley, John Gordon; Newhauser, Wayne David; Lüchtenborg, Robert; Graeff, Christian; Bert, Christoph

2014-01-01

Motion mitigation strategies are needed to fully realize the theoretical advantages of scanned ion beam therapy for patients with moving tumors. The purpose of this study was to determine whether a new four-dimensional (4D) optimization approach for scanned-ion-beam tracking could reduce dose to avoidance volumes near a moving target while maintaining target dose coverage, compared to an existing 3D-optimized beam tracking approach. We tested these approaches computationally using a simple 4D geometrical phantom and a complex anatomic phantom, that is, a 4D computed tomogram of the thorax of a lung cancer patient. We also validated our findings using measurements of carbon-ion beams with a motorized film phantom. Relative to 3D-optimized beam tracking, 4D-optimized beam tracking reduced the maximum predicted dose to avoidance volumes by 53% in the simple phantom and by 13% in the thorax phantom. 4D-optimized beam tracking provided similar target dose homogeneity in the simple phantom (standard deviation of target dose was 0.4% versus 0.3%) and dramatically superior homogeneity in the thorax phantom (D5-D95 was 1.9% versus 38.7%). Measurements demonstrated that delivery of 4D-optimized beam tracking was technically feasible and confirmed a 42% decrease in maximum film exposure in the avoidance region compared with 3D-optimized beam tracking. In conclusion, we found that 4D-optimized beam tracking can reduce the maximum dose to avoidance volumes near a moving target while maintaining target dose coverage, compared with 3D-optimized beam tracking. PMID:24889215

4D optimization of scanned ion beam tracking therapy for moving tumors

NASA Astrophysics Data System (ADS)

Eley, John Gordon; Newhauser, Wayne David; Lüchtenborg, Robert; Graeff, Christian; Bert, Christoph

2014-07-01

Motion mitigation strategies are needed to fully realize the theoretical advantages of scanned ion beam therapy for patients with moving tumors. The purpose of this study was to determine whether a new four-dimensional (4D) optimization approach for scanned-ion-beam tracking could reduce dose to avoidance volumes near a moving target while maintaining target dose coverage, compared to an existing 3D-optimized beam tracking approach. We tested these approaches computationally using a simple 4D geometrical phantom and a complex anatomic phantom, that is, a 4D computed tomogram of the thorax of a lung cancer patient. We also validated our findings using measurements of carbon-ion beams with a motorized film phantom. Relative to 3D-optimized beam tracking, 4D-optimized beam tracking reduced the maximum predicted dose to avoidance volumes by 53% in the simple phantom and by 13% in the thorax phantom. 4D-optimized beam tracking provided similar target dose homogeneity in the simple phantom (standard deviation of target dose was 0.4% versus 0.3%) and dramatically superior homogeneity in the thorax phantom (D5-D95 was 1.9% versus 38.7%). Measurements demonstrated that delivery of 4D-optimized beam tracking was technically feasible and confirmed a 42% decrease in maximum film exposure in the avoidance region compared with 3D-optimized beam tracking. In conclusion, we found that 4D-optimized beam tracking can reduce the maximum dose to avoidance volumes near a moving target while maintaining target dose coverage, compared with 3D-optimized beam tracking.

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.

Small target detection based on difference accumulation and Gaussian curvature under complex conditions

NASA Astrophysics Data System (ADS)

Zhang, He; Niu, Yanxiong; Zhang, Hao

2017-12-01

Small target detection is a significant subject in infrared search and track and other photoelectric imaging systems. The small target is imaged under complex conditions, which contains clouds, horizon and bright part. In this paper, a novel small target detection method is proposed based on difference accumulation, clustering and Gaussian curvature. Difference accumulation varies from regions. Therefore, after obtaining difference accumulations, clustering is applied to determine whether the pixel belongs to the heterogeneous region, and eliminate heterogeneous region. Then Gaussian curvature is used to separate target from the homogeneous region. Experiments are conducted for verification, along with comparisons to several other methods. The experimental results demonstrate that our method has an advantage of 1-2 orders of magnitude on SCRG and BSF than others. Given that the false alarm rate is 1, the detection probability can be approximately 0.9 by using proposed method.

Analysis of the track- and dose-averaged LET and LET spectra in proton therapy using the geant4 Monte Carlo code

PubMed Central

Guan, Fada; Peeler, Christopher; Bronk, Lawrence; Geng, Changran; Taleei, Reza; Randeniya, Sharmalee; Ge, Shuaiping; Mirkovic, Dragan; Grosshans, David; Mohan, Radhe; Titt, Uwe

2015-01-01

Purpose: The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons. Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LETt and dose-averaged LET, LETd) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LETt and LETd of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose. Results: Simulation results showed that the step limit effect was small for LETt but significant for LETd. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LETd calculation results in the dose plateau region for small step limits. The erroneous LETd results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LETd values lead to substantial differences in the calculated RBE. Conclusions: When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LETt in the dose plateau region and LETd around the Bragg peak. For a large step limit, i.e., 500 μm, LETd is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LETd and LETt becomes positive. PMID:26520716

An improved multi-domain convolution tracking algorithm

NASA Astrophysics Data System (ADS)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

Along with the wide application of the Deep Learning in the field of Computer vision, Deep learning has become a mainstream direction in the field of object tracking. The tracking algorithm in this paper is based on the improved multidomain convolution neural network, and the VOT video set is pre-trained on the network by multi-domain training strategy. In the process of online tracking, the network evaluates candidate targets sampled from vicinity of the prediction target in the previous with Gaussian distribution, and the candidate target with the highest score is recognized as the prediction target of this frame. The Bounding Box Regression model is introduced to make the prediction target closer to the ground-truths target box of the test set. Grouping-update strategy is involved to extract and select useful update samples in each frame, which can effectively prevent over fitting. And adapt to changes in both target and environment. To improve the speed of the algorithm while maintaining the performance, the number of candidate target succeed in adjusting dynamically with the help of Self-adaption parameter Strategy. Finally, the algorithm is tested by OTB set, compared with other high-performance tracking algorithms, and the plot of success rate and the accuracy are drawn. which illustrates outstanding performance of the tracking algorithm in this paper.

Intelligence-aided multitarget tracking for urban operations - a case study: counter terrorism

NASA Astrophysics Data System (ADS)

Sathyan, T.; Bharadwaj, K.; Sinha, A.; Kirubarajan, T.

2006-05-01

In this paper, we present a framework for tracking multiple mobile targets in an urban environment based on data from multiple sources of information, and for evaluating the threat these targets pose to assets of interest (AOI). The motivating scenario is one where we have to track many targets, each with different (unknown) destinations and/or intents. The tracking algorithm is aided by information about the urban environment (e.g., road maps, buildings, hideouts), and strategic and intelligence data. The tracking algorithm needs to be dynamic in that it has to handle a time-varying number of targets and the ever-changing urban environment depending on the locations of the moving objects and AOI. Our solution uses the variable structure interacting multiple model (VS-IMM) estimator, which has been shown to be effective in tracking targets based on road map information. Intelligence information is represented as target class information and incorporated through a combined likelihood calculation within the VS-IMM estimator. In addition, we develop a model to calculate the probability that a particular target can attack a given AOI. This model for the calculation of the probability of attack is based on the target kinematic and class information. Simulation results are presented to demonstrate the operation of the proposed framework on a representative scenario.

Robust human detection, tracking, and recognition in crowded urban areas

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2014-06-01

In this paper, we present algorithms we recently developed to support an automated security surveillance system for very crowded urban areas. In our approach for human detection, the color features are obtained by taking the difference of R, G, B spectrum and converting R, G, B to HSV (Hue, Saturation, Value) space. Morphological patch filtering and regional minimum and maximum segmentation on the extracted features are applied for target detection. The human tracking process approach includes: 1) Color and intensity feature matching track candidate selection; 2) Separate three parallel trackers for color, bright (above mean intensity), and dim (below mean intensity) detections, respectively; 3) Adaptive track gate size selection for reducing false tracking probability; and 4) Forward position prediction based on previous moving speed and direction for continuing tracking even when detections are missed from frame to frame. The Human target recognition is improved with a Super-Resolution Image Enhancement (SRIE) process. This process can improve target resolution by 3-5 times and can simultaneously process many targets that are tracked. Our approach can project tracks from one camera to another camera with a different perspective viewing angle to obtain additional biometric features from different perspective angles, and to continue tracking the same person from the 2nd camera even though the person moved out of the Field of View (FOV) of the 1st camera with `Tracking Relay'. Finally, the multiple cameras at different view poses have been geo-rectified to nadir view plane and geo-registered with Google- Earth (or other GIS) to obtain accurate positions (latitude, longitude, and altitude) of the tracked human for pin-point targeting and for a large area total human motion activity top-view. Preliminary tests of our algorithms indicate than high probability of detection can be achieved for both moving and stationary humans. Our algorithms can simultaneously track more than 100 human targets with averaged tracking period (time length) longer than the performance of the current state-of-the-art.

Target motion tracking in MRI-guided transrectal robotic prostate biopsy.

PubMed

Tadayyon, Hadi; Lasso, Andras; Kaushal, Aradhana; Guion, Peter; Fichtinger, Gabor

2011-11-01

MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. Two questions are studied and answered in this paper: 1) is rigid registration sufficient in tracking the targets with an error smaller than the clinically significant size of prostate cancer and 2) what is the effect of the number of intraoperative slices on registration accuracy and speed? we propose multislice-to-volume registration algorithms for tracking the biopsy targets within the prostate. Three orthogonal plus additional transverse intraoperative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. Both simulated and clinical MRI-guided robotic prostate biopsy data were used to assess tracking accuracy. average registration errors in clinical patient data were 2.6 mm for the rigid algorithm and 2.1 mm for the deformable algorithm. rigid tracking appears to be promising. Three tracking slices yield significantly high registration speed with an affordable error.

Multiple-target tracking implementation in the ebCMOS camera system: the LUSIPHER prototype

NASA Astrophysics Data System (ADS)

Doan, Quang Tuyen; Barbier, Remi; Dominjon, Agnes; Cajgfinger, Thomas; Guerin, Cyrille

2012-06-01

The domain of the low light imaging systems progresses very fast, thanks to detection and electronic multiplication technology evolution, such as the emCCD (electron multiplying CCD) or the ebCMOS (electron bombarded CMOS). We present an ebCMOS camera system that is able to track every 2 ms more than 2000 targets with a mean number of photons per target lower than two. The point light sources (targets) are spots generated by a microlens array (Shack-Hartmann) used in adaptive optics. The Multiple-Target-Tracking designed and implemented on a rugged workstation is described. The results and the performances of the system on the identification and tracking are presented and discussed.

Video Guidance Sensors Using Remotely Activated Targets

NASA Technical Reports Server (NTRS)

Bryan, Thomas C.; Howard, Richard T.; Book, Michael L.

2004-01-01

Four updated video guidance sensor (VGS) systems have been proposed. As described in a previous NASA Tech Briefs article, a VGS system is an optoelectronic system that provides guidance for automated docking of two vehicles. The VGS provides relative position and attitude (6-DOF) information between the VGS and its target. In the original intended application, the two vehicles would be spacecraft, but the basic principles of design and operation of the system are applicable to aircraft, robots, objects maneuvered by cranes, or other objects that may be required to be aligned and brought together automatically or under remote control. In the first two of the four VGS systems as now proposed, the tracked vehicle would include active targets that would light up on command from the tracking vehicle, and a video camera on the tracking vehicle would be synchronized with, and would acquire images of, the active targets. The video camera would also acquire background images during the periods between target illuminations. The images would be digitized and the background images would be subtracted from the illuminated-target images. Then the position and orientation of the tracked vehicle relative to the tracking vehicle would be computed from the known geometric relationships among the positions of the targets in the image, the positions of the targets relative to each other and to the rest of the tracked vehicle, and the position and orientation of the video camera relative to the rest of the tracking vehicle. The major difference between the first two proposed systems and prior active-target VGS systems lies in the techniques for synchronizing the flashing of the active targets with the digitization and processing of image data. In the prior active-target VGS systems, synchronization was effected, variously, by use of either a wire connection or the Global Positioning System (GPS). In three of the proposed VGS systems, the synchronizing signal would be generated on, and transmitted from, the tracking vehicle. In the first proposed VGS system, the tracking vehicle would transmit a pulse of light. Upon reception of the pulse, circuitry on the tracked vehicle would activate the target lights. During the pulse, the target image acquired by the camera would be digitized. When the pulse was turned off, the target lights would be turned off and the background video image would be digitized. The second proposed system would function similarly to the first proposed system, except that the transmitted synchronizing signal would be a radio pulse instead of a light pulse. In this system, the signal receptor would be a rectifying antenna. If the signal contained sufficient power, the output of the rectifying antenna could be used to activate the target lights, making it unnecessary to include a battery or other power supply for the targets on the tracked vehicle.

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.

DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

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

Villeneuve, Pierre V.

2013-02-28

The goal of this Phase II SBIR is to develop a prototype software package to demonstrate spectrally-aided vehicle tracking performance. The primary application is to demonstrate improved target vehicle tracking performance in complex environments where traditional spatial tracker systems may show reduced performance. Example scenarios in Figure 1 include a) the target vehicle obscured by a large structure for an extended period of time, or b), the target engaging in extreme maneuvers amongst other civilian vehicles. The target information derived from spatial processing is unable to differentiate between the green versus the red vehicle. Spectral signature exploitation enables comparison ofmore » new candidate targets with existing track signatures. The ambiguity in this confusing scenario is resolved by folding spectral analysis results into each target nomination and association processes. Figure 3 shows a number of example spectral signatures from a variety of natural and man-made materials. The work performed over the two-year effort was divided into three general areas: algorithm refinement, software prototype development, and prototype performance demonstration. The tasks performed under this Phase II to accomplish the program goals were as follows: 1. Acquire relevant vehicle target datasets to support prototype. 2. Refine algorithms for target spectral feature exploitation. 3. Implement a prototype multi-hypothesis target tracking software package. 4. Demonstrate and quantify tracking performance using relevant data.« less

Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

NASA Astrophysics Data System (ADS)

Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

2015-09-01

As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

Cooperative Robots to Observe Moving Targets: Review.

PubMed

Khan, Asif; Rinner, Bernhard; Cavallaro, Andrea

2018-01-01

The deployment of multiple robots for achieving a common goal helps to improve the performance, efficiency, and/or robustness in a variety of tasks. In particular, the observation of moving targets is an important multirobot application that still exhibits numerous open challenges, including the effective coordination of the robots. This paper reviews control techniques for cooperative mobile robots monitoring multiple targets. The simultaneous movement of robots and targets makes this problem particularly interesting, and our review systematically addresses this cooperative multirobot problem for the first time. We classify and critically discuss the control techniques: cooperative multirobot observation of multiple moving targets, cooperative search, acquisition, and track, cooperative tracking, and multirobot pursuit evasion. We also identify the five major elements that characterize this problem, namely, the coordination method, the environment, the target, the robot and its sensor(s). These elements are used to systematically analyze the control techniques. The majority of the studied work is based on simulation and laboratory studies, which may not accurately reflect real-world operational conditions. Importantly, while our systematic analysis is focused on multitarget observation, our proposed classification is useful also for related multirobot applications.

Renewal of the Attentive Sensing Project

DTIC Science & Technology

2006-02-07

decisions about target presence or absence, is denoted track before detect . We have investigated joint tracking and detection in the context of the foveal...computationally tractable bounds. 4 Task 2: Sensor Configuration for Tracking and Track Before Detect Task 2 consisted of investigation of attentive...strategy to multiple targets and to track before detect sensors. To apply principles developed in the context of foveal sensors to more immediately

δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells

PubMed Central

Liu, Chao; Lei, Peng; Qi, Yaolong

2018-01-01

The amplitude information (AI) of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target’s state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR) environment. PMID:29642595

Real-time method for motion-compensated MR thermometry and MRgHIFU treatment in abdominal organs.

PubMed

Celicanin, Zarko; Auboiroux, Vincent; Bieri, Oliver; Petrusca, Lorena; Santini, Francesco; Viallon, Magalie; Scheffler, Klaus; Salomir, Rares

2014-10-01

Magnetic resonance-guided high-intensity focused ultrasound is considered to be a promising treatment for localized cancer in abdominal organs such as liver, pancreas, or kidney. Abdominal motion, anatomical arrangement, and required sustained sonication are the main challenges. MR acquisition consisted of thermometry performed with segmented gradient-recalled echo echo-planar imaging, and a segment-based one-dimensional MR navigator parallel to the main axis of motion to track the organ motion. This tracking information was used in real-time for: (i) prospective motion correction of MR thermometry and (ii) HIFU focal point position lock-on target. Ex vivo experiments were performed on a sheep liver and a turkey pectoral muscle using a motion demonstrator, while in vivo experiments were conducted on two sheep liver. Prospective motion correction of MR thermometry yielded good signal-to-noise ratio (range, 25 to 35) and low geometric distortion due to the use of segmented EPI. HIFU focal point lock-on target yielded isotropic in-plane thermal build-up. The feasibility of in vivo intercostal liver treatment was demonstrated in sheep. The presented method demonstrated in moving phantoms and breathing sheep accurate motion-compensated MR thermometry and precise HIFU focal point lock-on target using only real-time pencil-beam navigator tracking information, making it applicable without any pretreatment data acquisition or organ motion modeling. Copyright © 2013 Wiley Periodicals, Inc.

TU-D-202-03: Gating Is the Best ITV Killer

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

Low, D.

Respiratory motion has long been recognized as an important factor affecting the precision of radiotherapy. After the introduction of the 4D CT to visualize the respiratory motion in 3D, the internal target volume (ITV) has been widely adopted as simple method to take the motion into account in treatment planning and delivery. The ITV is generated as the union of the CTVs as the patient goes through the respiratory cycle. Many issues have been identified with the ITV. In this session three alternatives for the ITV will be discussed: 1) An alternative motion-inclusive approach with better imaging and smaller margins,more » called mid-position CT. 2) The tracking approach and 3) The gating approach. The following topics will be addressed by Marcel van Herk (“Is ITV the correct motion encompassing strategy”): Magnitude of respiratory motion, effect of motion on radiotherapy, motion encompassing strategies, and software solutions to assist in motion encompassing strategies. Then Paul Keall (“Make margins simple: Use real-time target tracking”) will discuss tracking with: clinical drivers for tracking, current clinical status of tumor tracking, future tumor tracking technology, and margin margin challenges with and without tracking. Finally Daniel Low will discuss gating (“Gating is the best ITV killer”): why ITV in the first place, requirements for planning, requirements at the machine, benefits and costs. The session will end with a discussion and live demo of motion simulation software to illustrate the issues and explain the relative benefit and appropriate uses for the three methods. Learning Objectives: Explain the 4D imaging and treatment planning process. Summarize the various approaches to deal with respiratory motion during radiotherapy Discuss the tradeoffs involved when choosing one of the three discussed approaches. Explain in which situation each method is the best choice Research is partly funded by Elekta Oncology Systems and the Dutch Cancer Foundation; M. van Herk, Part of the research was funded by Elekta Oncology Systems and the Dutch Cancer Foundation.« less

Target Tracking in Heavy-Tailed Clutter Using Amplitude Information

DTIC Science & Technology

2009-07-01

to integrate the data before the detection decision is made, as done in so- called Track - Before - Detect (TBD) [5,14]. For very low SNR, when the target...Processes. McGraw-Hill, 2002. [14] M. G. Rutten, N. J. Gordon, and S. Maskell, “Recur- sive track - before - detect with target amplitude fluctua- tions,” in IEE

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Three-dimensional tracking and imaging laser scanner for space operations

NASA Astrophysics Data System (ADS)

Laurin, Denis G.; Beraldin, J. A.; Blais, Francois; Rioux, Marc; Cournoyer, Luc

1999-05-01

This paper presents the development of a laser range scanner (LARS) as a three-dimensional sensor for space applications. The scanner is a versatile system capable of doing surface imaging, target ranging and tracking. It is capable of short range (0.5 m to 20 m) and long range (20 m to 10 km) sensing using triangulation and time-of-flight (TOF) methods respectively. At short range (1 m), the resolution is sub-millimeter and drops gradually with distance (2 cm at 10 m). For long range, the TOF provides a constant resolution of plus or minus 3 cm, independent of range. The LARS could complement the existing Canadian Space Vision System (CSVS) for robotic manipulation. As an active vision system, the LARS is immune to sunlight and adverse lighting; this is a major advantage over the CSVS, as outlined in this paper. The LARS could also replace existing radar systems used for rendezvous and docking. There are clear advantages of an optical system over a microwave radar in terms of size, mass, power and precision. Equipped with two high-speed galvanometers, the laser can be steered to address any point in a 30 degree X 30 degree field of view. The scanning can be continuous (raster scan, Lissajous) or direct (random). This gives the scanner the ability to register high-resolution 3D images of range and intensity (up to 4000 X 4000 pixels) and to perform point target tracking as well as object recognition and geometrical tracking. The imaging capability of the scanner using an eye-safe laser is demonstrated. An efficient fiber laser delivers 60 mW of CW or 3 (mu) J pulses at 20 kHz for TOF operation. Implementation of search and track of multiple targets is also demonstrated. For a single target, refresh rates up to 137 Hz is possible. Considerations for space qualification of the scanner are discussed. Typical space operations, such as docking, object attitude tracking, and inspections are described.

Robust visual tracking based on deep convolutional neural networks and kernelized correlation filters

NASA Astrophysics Data System (ADS)

Yang, Hua; Zhong, Donghong; Liu, Chenyi; Song, Kaiyou; Yin, Zhouping

2018-03-01

Object tracking is still a challenging problem in computer vision, as it entails learning an effective model to account for appearance changes caused by occlusion, out of view, plane rotation, scale change, and background clutter. This paper proposes a robust visual tracking algorithm called deep convolutional neural network (DCNNCT) to simultaneously address these challenges. The proposed DCNNCT algorithm utilizes a DCNN to extract the image feature of a tracked target, and the full range of information regarding each convolutional layer is used to express the image feature. Subsequently, the kernelized correlation filters (CF) in each convolutional layer are adaptively learned, the correlation response maps of that are combined to estimate the location of the tracked target. To avoid the case of tracking failure, an online random ferns classifier is employed to redetect the tracked target, and a dual-threshold scheme is used to obtain the final target location by comparing the tracking result with the detection result. Finally, the change in scale of the target is determined by building scale pyramids and training a CF. Extensive experiments demonstrate that the proposed algorithm is effective at tracking, especially when evaluated using an index called the overlap rate. The DCNNCT algorithm is also highly competitive in terms of robustness with respect to state-of-the-art trackers in various challenging scenarios.

The PMHT: solutions for some of its problems

NASA Astrophysics Data System (ADS)

Wieneke, Monika; Koch, Wolfgang

2007-09-01

Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic Multiple Hypothesis Tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on the method of Expectation-Maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. Unfortunately, compared with the Probabilistic Data Association Filter (PDAF), PMHT has not yet shown its superiority in terms of track-lost statistics. Furthermore, the problem of track extraction and deletion is apparently not yet satisfactorily solved within this framework. Four properties of PMHT are responsible for its problems in track maintenance: Non-Adaptivity, Hospitality, Narcissism and Local Maxima. 1, 2 In this work we present a solution for each of them and derive an improved PMHT by integrating the solutions into the PMHT formalism. The new PMHT is evaluated by Monte-Carlo simulations. A sequential Likelihood-Ratio (LR) test for track extraction has been developed and already integrated into the framework of traditional Bayesian Multiple Hypothesis Tracking. 3 As a multi-scan approach, also the PMHT methodology has the potential for track extraction. In this paper an analogous integration of a sequential LR test into the PMHT framework is proposed. We present an LR formula for track extraction and deletion using the PMHT update formulae. As PMHT provides all required ingredients for a sequential LR calculation, the LR is thus a by-product of the PMHT iteration process. Therefore the resulting update formula for the sequential LR test affords the development of Track-Before-Detect algorithms for PMHT. The approach is illustrated by a simple example.

Detection of unknown targets from aerial camera and extraction of simple object fingerprints for the purpose of target reacquisition

NASA Astrophysics Data System (ADS)

Mundhenk, T. Nathan; Ni, Kang-Yu; Chen, Yang; Kim, Kyungnam; Owechko, Yuri

2012-01-01

An aerial multiple camera tracking paradigm needs to not only spot unknown targets and track them, but also needs to know how to handle target reacquisition as well as target handoff to other cameras in the operating theater. Here we discuss such a system which is designed to spot unknown targets, track them, segment the useful features and then create a signature fingerprint for the object so that it can be reacquired or handed off to another camera. The tracking system spots unknown objects by subtracting background motion from observed motion allowing it to find targets in motion, even if the camera platform itself is moving. The area of motion is then matched to segmented regions returned by the EDISON mean shift segmentation tool. Whole segments which have common motion and which are contiguous to each other are grouped into a master object. Once master objects are formed, we have a tight bound on which to extract features for the purpose of forming a fingerprint. This is done using color and simple entropy features. These can be placed into a myriad of different fingerprints. To keep data transmission and storage size low for camera handoff of targets, we try several different simple techniques. These include Histogram, Spatiogram and Single Gaussian Model. These are tested by simulating a very large number of target losses in six videos over an interval of 1000 frames each from the DARPA VIVID video set. Since the fingerprints are very simple, they are not expected to be valid for long periods of time. As such, we test the shelf life of fingerprints. This is how long a fingerprint is good for when stored away between target appearances. Shelf life gives us a second metric of goodness and tells us if a fingerprint method has better accuracy over longer periods. In videos which contain multiple vehicle occlusions and vehicles of highly similar appearance we obtain a reacquisition rate for automobiles of over 80% using the simple single Gaussian model compared with the null hypothesis of <20%. Additionally, the performance for fingerprints stays well above the null hypothesis for as much as 800 frames. Thus, a simple and highly compact single Gaussian model is useful for target reacquisition. Since the model is agnostic to view point and object size, it is expected to perform as well on a test of target handoff. Since some of the performance degradation is due to problems with the initial target acquisition and tracking, the simple Gaussian model may perform even better with an improved initial acquisition technique. Also, since the model makes no assumption about the object to be tracked, it should be possible to use it to fingerprint a multitude of objects, not just cars. Further accuracy may be obtained by creating manifolds of objects from multiple samples.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

PubMed

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

The ship-borne infrared searching and tracking system based on the inertial platform

NASA Astrophysics Data System (ADS)

Li, Yan; Zhang, Haibo

2011-08-01

As a result of the radar system got interferenced or in the state of half silent ,it can cause the guided precision drop badly In the modern electronic warfare, therefore it can lead to the equipment depended on electronic guidance cannot strike the incoming goals exactly. It will need to rely on optoelectronic devices to make up for its shortcomings, but when interference is in the process of radar leading ,especially the electro-optical equipment is influenced by the roll, pitch and yaw rotation ,it can affect the target appear outside of the field of optoelectronic devices for a long time, so the infrared optoelectronic equipment can not exert the superiority, and also it cannot get across weapon-control system "reverse bring" missile against incoming goals. So the conventional ship-borne infrared system unable to track the target of incoming quickly , the ability of optoelectronic rivalry declines heavily.Here we provide a brand new controlling algorithm for the semi-automatic searching and infrared tracking based on inertial navigation platform. Now it is applying well in our XX infrared optoelectronic searching and tracking system. The algorithm is mainly divided into two steps: The artificial mode turns into auto-searching when the deviation of guide exceeds the current scene under the course of leading for radar.When the threshold value of the image picked-up is satisfied by the contrast of the target in the searching scene, the speed computed by using the CA model Least Square Method feeds back to the speed loop. And then combine the infrared information to accomplish the closed-loop control of the infrared optoelectronic system tracking. The algorithm is verified via experiment. Target capturing distance is 22.3 kilometers on the great lead deviation by using the algorithm. But without using the algorithm the capturing distance declines 12 kilometers. The algorithm advances the ability of infrared optoelectronic rivalry and declines the target capturing time by using semi-automatic searching and reliable capturing-tracking, when the lead deviation of the radar is great.

WE-G-BRF-01: Adaptation to Intrafraction Tumor Deformation During Intensity-Modulated Radiotherapy: First Proof-Of-Principle Demonstration

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

Ge, Y; OBrien, R; Shieh, C

2014-06-15

Purpose: Intrafraction tumor deformation limits targeting accuracy in radiotherapy and cannot be adapted to by current motion management techniques. This study simulated intrafractional treatment adaptation to tumor deformations using a dynamic Multi-Leaf Collimator (DMLC) tracking system during Intensity-modulated radiation therapy (IMRT) treatment for the first time. Methods: The DMLC tracking system was developed to adapt to the intrafraction tumor deformation by warping the planned beam aperture guided by the calculated deformation vector field (DVF) obtained from deformable image registration (DIR) at the time of treatment delivery. Seven single phantom deformation images up to 10.4 mm deformation and eight tumor systemmore » phantom deformation images up to 21.5 mm deformation were acquired and used in tracking simulation. The intrafraction adaptation was simulated at the DMLC tracking software platform, which was able to communicate with the image registration software, reshape the instantaneous IMRT field aperture and log the delivered MLC fields.The deformation adaptation accuracy was evaluated by a geometric target coverage metric defined as the sum of the area incorrectly outside and inside the reference aperture. The incremental deformations were arbitrarily determined to take place equally over the delivery interval. The geometric target coverage of delivery with deformation adaptation was compared against the delivery without adaptation. Results: Intrafraction deformation adaptation during dynamic IMRT plan delivery was simulated for single and system deformable phantoms. For the two particular delivery situations, over the treatment course, deformation adaptation improved the target coverage by 89% for single target deformation and 79% for tumor system deformation compared with no-tracking delivery. Conclusion: This work demonstrated the principle of real-time tumor deformation tracking using a DMLC. This is the first step towards the development of an image-guided radiotherapy system to treat deforming tumors in real-time. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship, Cure Cancer Australia Foundation, NHMRC Project Grant APP1042375 and US NIH/NCI R01CA93626.« less

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

Two-Dimensional Stochastic Projections for Tight Integration of Optical and Inertial Sensors for Navigation

DTIC Science & Technology

2007-01-01

Intelligent Robots and Systems, vol- ume 1, pp. 123–128, September 2002. [2] R. G. Brown and P. Y. Hwang . Introduction to Ran- dom Signals and Applied... Kalman Filter-based) method for calculat- ing a trajectory by tracking features at an unknown location on the Earth’s surface, provided the topography...Extended Kalman Filter (EKF) and an automatic target tracking algorithm. In the following section, the integration architecture is presented, which in

A game theory approach to target tracking in sensor networks.

PubMed

Gu, Dongbing

2011-02-01

In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

Target recognitions in multiple-camera closed-circuit television using color constancy

NASA Astrophysics Data System (ADS)

Soori, Umair; Yuen, Peter; Han, Ji Wen; Ibrahim, Izzati; Chen, Wentao; Hong, Kan; Merfort, Christian; James, David; Richardson, Mark

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by the proposed ELRCC algorithm. This amount of improvement represents a reduction of probability of false alarm by about a factor of 5 at the probability of detection of 0.5. Our study concerns mainly the detection of colored targets; and issues for the recognition of white or gray targets will be addressed in a forthcoming study.

Graph theoretic framework based cooperative control and estimation of multiple UAVs for target tracking

NASA Astrophysics Data System (ADS)

Ahmed, Mousumi

Designing the control technique for nonlinear dynamic systems is a significant challenge. Approaches to designing a nonlinear controller are studied and an extensive study on backstepping based technique is performed in this research with the purpose of tracking a moving target autonomously. Our main motivation is to explore the controller for cooperative and coordinating unmanned vehicles in a target tracking application. To start with, a general theoretical framework for target tracking is studied and a controller in three dimensional environment for a single UAV is designed. This research is primarily focused on finding a generalized method which can be applied to track almost any reference trajectory. The backstepping technique is employed to derive the controller for a simplified UAV kinematic model. This controller can compute three autopilot modes i.e. velocity, ground heading (or course angle), and flight path angle for tracking the unmanned vehicle. Numerical implementation is performed in MATLAB with the assumption of having perfect and full state information of the target to investigate the accuracy of the proposed controller. This controller is then frozen for the multi-vehicle problem. Distributed or decentralized cooperative control is discussed in the context of multi-agent systems. A consensus based cooperative control is studied; such consensus based control problem can be viewed from the algebraic graph theory concepts. The communication structure between the UAVs is represented by the dynamic graph where UAVs are represented by the nodes and the communication links are represented by the edges. The previously designed controller is augmented to account for the group to obtain consensus based on their communication. A theoretical development of the controller for the cooperative group of UAVs is presented and the simulation results for different communication topologies are shown. This research also investigates the cases where the communication topology switches to a different topology over particular time instants. Lyapunov analysis is performed to show stability in all cases. Another important aspect of this dissertation research is to implement the controller for the case, where perfect or full state information is not available. This necessitates the design of an estimator to estimate the system state. A nonlinear estimator, Extended Kalman Filter (EKF) is first developed for target tracking with a single UAV. The uncertainties involved with the measurement model and dynamics model are considered as zero mean Gaussian noises with some known covariances. The measurements of the full state of the target are not available and only the range, elevation, and azimuth angle are available from an onboard seeker sensor. A separate EKF is designed to estimate the UAV's own state where the state measurement is available through on-board sensors. The controller computes the three control commands based on the estimated states of target and its own states. Estimation based control laws is also implemented for colored noise measurement uncertainties, and the controller performance is shown with the simulation results. The estimation based control approach is then extended for the cooperative target tracking case. The target information is available to the network and a separate estimator is used to estimate target states. All of the UAVs in the network apply the same control law and the only difference is that each UAV updates the commands according to their connection. The simulation is performed for both cases of fixed and time varying communication topology. Monte Carlo simulation is also performed with different sample noises to investigate the performance of the estimator. The proposed technique is shown to be simple and robust to noisy environments.

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.

Dissociable Frontal Controls during Visible and Memory-guided Eye-Tracking of Moving Targets

PubMed Central

Ding, Jinhong; Powell, David; Jiang, Yang

2009-01-01

When tracking visible or occluded moving targets, several frontal regions including the frontal eye fields (FEF), dorsal-lateral prefrontal cortex (DLPFC), and Anterior Cingulate Cortex (ACC) are involved in smooth pursuit eye movements (SPEM). To investigate how these areas play different roles in predicting future locations of moving targets, twelve healthy college students participated in a smooth pursuit task of visual and occluded targets. Their eye movements and brain responses measured by event-related functional MRI were simultaneously recorded. Our results show that different visual cues resulted in time discrepancies between physical and estimated pursuit time only when the moving dot was occluded. Visible phase velocity gain was higher than that of occlusion phase. We found bilateral FEF association with eye-movement whether moving targets are visible or occluded. However, the DLPFC and ACC showed increased activity when tracking and predicting locations of occluded moving targets, and were suppressed during smooth pursuit of visible targets. When visual cues were increasingly available, less activation in the DLPFC and the ACC was observed. Additionally, there was a significant hemisphere effect in DLPFC, where right DLPFC showed significantly increased responses over left when pursuing occluded moving targets. Correlation results revealed that DLPFC, the right DLPFC in particular, communicates more with FEF during tracking of occluded moving targets (from memory). The ACC modulates FEF more during tracking of visible targets (likely related to visual attention). Our results suggest that DLPFC and ACC modulate FEF and cortical networks differentially during visible and memory-guided eye tracking of moving targets. PMID:19434603

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Development of an optical three-dimensional laser tracker using dual modulated laser diodes and a signal detector

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

Lee, Hau-Wei; Chen, Chieh-Li; Liu, Chien-Hung

Laser trackers are widely used in industry for tasks such as the assembly of airplanes and automobiles, contour measurement, and robot calibration. However, laser trackers are expensive, and the corresponding solution procedure is very complex. The influence of measurement uncertainties is also significant. This study proposes a three-dimensional space position measurement system which consists of two tracking modules, a zero tracking angle return subsystem, and a target quadrant photodiode (QPD). The target QPD is placed on the object being tracked. The origin locking method is used to keep the rays on the origin of the target QPD. The position ofmore » the target QPD is determined using triangulation since the two laser rays are projected onto one QPD. Modulation and demodulation are utilized to separate the coupled positional values. The experiment results show that measurement errors in the X, Y, and Z directions are less than {+-}0.05% when the measured object was moved by 300, 300, and 200 mm in the X, Y, and Z axes, respectively. The theoretical measurement error estimated from the measurement model is between {+-}0.02% and {+-}0.07% within the defined measurable range. The proposed system can be applied to the measurements of machine tools and robot arms.« less

Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network

NASA Astrophysics Data System (ADS)

Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.

2003-12-01

Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.

Development of an optical three-dimensional laser tracker using dual modulated laser diodes and a signal detector.

PubMed

Lee, Hau-Wei; Chen, Chieh-Li; Liu, Chien-Hung

2011-03-01

Laser trackers are widely used in industry for tasks such as the assembly of airplanes and automobiles, contour measurement, and robot calibration. However, laser trackers are expensive, and the corresponding solution procedure is very complex. The influence of measurement uncertainties is also significant. This study proposes a three-dimensional space position measurement system which consists of two tracking modules, a zero tracking angle return subsystem, and a target quadrant photodiode (QPD). The target QPD is placed on the object being tracked. The origin locking method is used to keep the rays on the origin of the target QPD. The position of the target QPD is determined using triangulation since the two laser rays are projected onto one QPD. Modulation and demodulation are utilized to separate the coupled positional values. The experiment results show that measurement errors in the X, Y, and Z directions are less than ±0.05% when the measured object was moved by 300, 300, and 200 mm in the X, Y, and Z axes, respectively. The theoretical measurement error estimated from the measurement model is between ±0.02% and ±0.07% within the defined measurable range. The proposed system can be applied to the measurements of machine tools and robot arms.

Development of an optical three-dimensional laser tracker using dual modulated laser diodes and a signal detector

NASA Astrophysics Data System (ADS)

Lee, Hau-Wei; Chen, Chieh-Li; Liu, Chien-Hung

2011-03-01

Laser trackers are widely used in industry for tasks such as the assembly of airplanes and automobiles, contour measurement, and robot calibration. However, laser trackers are expensive, and the corresponding solution procedure is very complex. The influence of measurement uncertainties is also significant. This study proposes a three-dimensional space position measurement system which consists of two tracking modules, a zero tracking angle return subsystem, and a target quadrant photodiode (QPD). The target QPD is placed on the object being tracked. The origin locking method is used to keep the rays on the origin of the target QPD. The position of the target QPD is determined using triangulation since the two laser rays are projected onto one QPD. Modulation and demodulation are utilized to separate the coupled positional values. The experiment results show that measurement errors in the X, Y, and Z directions are less than ±0.05% when the measured object was moved by 300, 300, and 200 mm in the X, Y, and Z axes, respectively. The theoretical measurement error estimated from the measurement model is between ±0.02% and ±0.07% within the defined measurable range. The proposed system can be applied to the measurements of machine tools and robot arms.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Eye-Hand Synergy and Intermittent Behaviors during Target-Directed Tracking with Visual and Non-visual Information

PubMed Central

Huang, Chien-Ting; Hwang, Ing-Shiou

2012-01-01

Visual feedback and non-visual information play different roles in tracking of an external target. This study explored the respective roles of the visual and non-visual information in eleven healthy volunteers who coupled the manual cursor to a rhythmically moving target of 0.5 Hz under three sensorimotor conditions: eye-alone tracking (EA), eye-hand tracking with visual feedback of manual outputs (EH tracking), and the same tracking without such feedback (EHM tracking). Tracking error, kinematic variables, and movement intermittency (saccade and speed pulse) were contrasted among tracking conditions. The results showed that EHM tracking exhibited larger pursuit gain, less tracking error, and less movement intermittency for the ocular plant than EA tracking. With the vision of manual cursor, EH tracking achieved superior tracking congruency of the ocular and manual effectors with smaller movement intermittency than EHM tracking, except that the rate precision of manual action was similar for both types of tracking. The present study demonstrated that visibility of manual consequences altered mutual relationships between movement intermittency and tracking error. The speed pulse metrics of manual output were linked to ocular tracking error, and saccade events were time-locked to the positional error of manual tracking during EH tracking. In conclusion, peripheral non-visual information is critical to smooth pursuit characteristics and rate control of rhythmic manual tracking. Visual information adds to eye-hand synchrony, underlying improved amplitude control and elaborate error interpretation during oculo-manual tracking. PMID:23236498

[Research on fuzzy proportional-integral-derivative control of master-slave minimally invasive operation robot driver].

PubMed

Zhao, Ximei; Ren, Chengyi; Liu, Hao; Li, Haogyi

2014-12-01

Robotic catheter minimally invasive operation requires that the driver control system has the advantages of quick response, strong anti-jamming and real-time tracking of target trajectory. Since the catheter parameters of itself and movement environment and other factors continuously change, when the driver is controlled using traditional proportional-integral-derivative (PID), the controller gain becomes fixed once the PID parameters are set. It can not change with the change of the parameters of the object and environmental disturbance so that its change affects the position tracking accuracy, and may bring a large overshoot endangering patients' vessel. Therefore, this paper adopts fuzzy PID control method to adjust PID gain parameters in the tracking process in order to improve the system anti-interference ability, dynamic performance and tracking accuracy. The simulation results showed that the fuzzy PID control method had a fast tracking performance and a strong robustness. Compared with those of traditional PID control, the feasibility and practicability of fuzzy PID control are verified in a robotic catheter minimally invasive operation.

The role of visual attention in multiple object tracking: evidence from ERPs.

PubMed

Doran, Matthew M; Hoffman, James E

2010-01-01

We examined the role of visual attention in the multiple object tracking (MOT) task by measuring the amplitude of the N1 component of the event-related potential (ERP) to probe flashes presented on targets, distractors, or empty background areas. We found evidence that visual attention enhances targets and suppresses distractors (Experiment 1 & 3). However, we also found that when tracking load was light (two targets and two distractors), accurate tracking could be carried out without any apparent contribution from the visual attention system (Experiment 2). Our results suggest that attentional selection during MOT is flexibly determined by task demands as well as tracking load and that visual attention may not always be necessary for accurate tracking.

Ray tracing through a hexahedral mesh in HADES

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

Henderson, G L; Aufderheide, M B

In this paper we describe a new ray tracing method targeted for inclusion in HADES. The algorithm tracks rays through three-dimensional tetrakis hexahedral mesh objects, like those used by the ARES code to model inertial confinement experiments.

Reduced complexity of multi-track joint 2-D Viterbi detectors for bit-patterned media recording channel

NASA Astrophysics Data System (ADS)

Myint, L. M. M.; Warisarn, C.

2017-05-01

Two-dimensional (2-D) interference is one of the prominent challenges in ultra-high density recording system such as bit patterned media recording (BPMR). The multi-track joint 2-D detection technique with the help of the array-head reading can tackle this problem effectively by jointly processing the multiple readback signals from the adjacent tracks. Moreover, it can robustly alleviate the impairments due to track mis-registration (TMR) and media noise. However, the computational complexity of such detectors is normally too high and hard to implement in a reality, even for a few multiple tracks. Therefore, in this paper, we mainly focus on reducing the complexity of multi-track joint 2-D Viterbi detector without paying a large penalty in terms of the performance. We propose a simplified multi-track joint 2-D Viterbi detector with a manageable complexity level for the BPMR's multi-track multi-head (MTMH) system. In the proposed method, the complexity of detector's trellis is reduced with the help of the joint-track equalization method which employs 1-D equalizers and 2-D generalized partial response (GPR) target. Moreover, we also examine the performance of a full-fledged multi-track joint 2-D detector and the conventional 2-D detection. The results show that the simplified detector can perform close to the full-fledge detector, especially when the system faces high media noise, with the significant low complexity.

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

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

Toward the development of intrafraction tumor deformation tracking using a dynamic multi-leaf collimator

PubMed Central

Ge, Yuanyuan; O’Brien, Ricky T.; Shieh, Chun-Chien; Booth, Jeremy T.; Keall, Paul J.

2014-01-01

Purpose: Intrafraction deformation limits targeting accuracy in radiotherapy. Studies show tumor deformation of over 10 mm for both single tumor deformation and system deformation (due to differential motion between primary tumors and involved lymph nodes). Such deformation cannot be adapted to with current radiotherapy methods. The objective of this study was to develop and experimentally investigate the ability of a dynamic multi-leaf collimator (DMLC) tracking system to account for tumor deformation. Methods: To compensate for tumor deformation, the DMLC tracking strategy is to warp the planned beam aperture directly to conform to the new tumor shape based on real time tumor deformation input. Two deformable phantoms that correspond to a single tumor and a tumor system were developed. The planar deformations derived from the phantom images in beam's eye view were used to guide the aperture warping. An in-house deformable image registration software was developed to automatically trigger the registration once new target image was acquired and send the computed deformation to the DMLC tracking software. Because the registration speed is not fast enough to implement the experiment in real-time manner, the phantom deformation only proceeded to the next position until registration of the current deformation position was completed. The deformation tracking accuracy was evaluated by a geometric target coverage metric defined as the sum of the area incorrectly outside and inside the ideal aperture. The individual contributions from the deformable registration algorithm and the finite leaf width to the tracking uncertainty were analyzed. Clinical proof-of-principle experiment of deformation tracking using previously acquired MR images of a lung cancer patient was implemented to represent the MRI-Linac environment. Intensity-modulated radiation therapy (IMRT) treatment delivered with enabled deformation tracking was simulated and demonstrated. Results: The first experimental investigation of adapting to tumor deformation has been performed using simple deformable phantoms. For the single tumor deformation, the Au+Ao was reduced over 56% when deformation was larger than 2 mm. Overall, the total improvement was 82%. For the tumor system deformation, the Au+Ao reductions were all above 75% and the total Au+Ao improvement was 86%. Similar coverage improvement was also found in simulating deformation tracking during IMRT delivery. The deformable image registration algorithm was identified as the dominant contributor to the tracking error rather than the finite leaf width. The discrepancy between the warped beam shape and the ideal beam shape due to the deformable registration was observed to be partially compensated during leaf fitting due to the finite leaf width. The clinical proof-of-principle experiment demonstrated the feasibility of intrafraction deformable tracking for clinical scenarios. Conclusions: For the first time, we developed and demonstrated an experimental system that is capable of adapting the MLC aperture to account for tumor deformation. This work provides a potentially widely available management method to effectively account for intrafractional tumor deformation. This proof-of-principle study is the first experimental step toward the development of an image-guided radiotherapy system to treat deforming tumors in real-time. PMID:24877798

Toward the development of intrafraction tumor deformation tracking using a dynamic multi-leaf collimator

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

Ge, Yuanyuan; O’Brien, Ricky T.; Shieh, Chun-Chien

Purpose: Intrafraction deformation limits targeting accuracy in radiotherapy. Studies show tumor deformation of over 10 mm for both single tumor deformation and system deformation (due to differential motion between primary tumors and involved lymph nodes). Such deformation cannot be adapted to with current radiotherapy methods. The objective of this study was to develop and experimentally investigate the ability of a dynamic multi-leaf collimator (DMLC) tracking system to account for tumor deformation. Methods: To compensate for tumor deformation, the DMLC tracking strategy is to warp the planned beam aperture directly to conform to the new tumor shape based on real timemore » tumor deformation input. Two deformable phantoms that correspond to a single tumor and a tumor system were developed. The planar deformations derived from the phantom images in beam's eye view were used to guide the aperture warping. An in-house deformable image registration software was developed to automatically trigger the registration once new target image was acquired and send the computed deformation to the DMLC tracking software. Because the registration speed is not fast enough to implement the experiment in real-time manner, the phantom deformation only proceeded to the next position until registration of the current deformation position was completed. The deformation tracking accuracy was evaluated by a geometric target coverage metric defined as the sum of the area incorrectly outside and inside the ideal aperture. The individual contributions from the deformable registration algorithm and the finite leaf width to the tracking uncertainty were analyzed. Clinical proof-of-principle experiment of deformation tracking using previously acquired MR images of a lung cancer patient was implemented to represent the MRI-Linac environment. Intensity-modulated radiation therapy (IMRT) treatment delivered with enabled deformation tracking was simulated and demonstrated. Results: The first experimental investigation of adapting to tumor deformation has been performed using simple deformable phantoms. For the single tumor deformation, the A{sub u}+A{sub o} was reduced over 56% when deformation was larger than 2 mm. Overall, the total improvement was 82%. For the tumor system deformation, the A{sub u}+A{sub o} reductions were all above 75% and the total A{sub u}+A{sub o} improvement was 86%. Similar coverage improvement was also found in simulating deformation tracking during IMRT delivery. The deformable image registration algorithm was identified as the dominant contributor to the tracking error rather than the finite leaf width. The discrepancy between the warped beam shape and the ideal beam shape due to the deformable registration was observed to be partially compensated during leaf fitting due to the finite leaf width. The clinical proof-of-principle experiment demonstrated the feasibility of intrafraction deformable tracking for clinical scenarios. Conclusions: For the first time, we developed and demonstrated an experimental system that is capable of adapting the MLC aperture to account for tumor deformation. This work provides a potentially widely available management method to effectively account for intrafractional tumor deformation. This proof-of-principle study is the first experimental step toward the development of an image-guided radiotherapy system to treat deforming tumors in real-time.« less

Adaptive relative pose control of spacecraft with model couplings and uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2018-02-01

The spacecraft pose tracking control problem for an uncertain pursuer approaching to a space target is researched in this paper. After modeling the nonlinearly coupled dynamics for relative translational and rotational motions between two spacecraft, position tracking and attitude synchronization controllers are developed independently by using a robust adaptive control approach. The unknown kinematic couplings, parametric uncertainties, and bounded external disturbances are handled with adaptive updating laws. It is proved via Lyapunov method that the pose tracking errors converge to zero asymptotically. Spacecraft close-range rendezvous and proximity operations are introduced as an example to validate the effectiveness of the proposed control approach.

Modified linear predictive coding approach for moving target tracking by Doppler radar

NASA Astrophysics Data System (ADS)

Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao

2016-07-01

Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.

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

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

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

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

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).

Controlling the Shannon Entropy of Quantum Systems

PubMed Central

Xing, Yifan; Wu, Jun

2013-01-01

This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking. PMID:23818819

Controlling the shannon entropy of quantum systems.

PubMed

Xing, Yifan; Wu, Jun

2013-01-01

This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking.

Automatic methods of the processing of data from track detectors on the basis of the PAVICOM facility

NASA Astrophysics Data System (ADS)

Aleksandrov, A. B.; Goncharova, L. A.; Davydov, D. A.; Publichenko, P. A.; Roganova, T. M.; Polukhina, N. G.; Feinberg, E. L.

2007-02-01

New automatic methods essentially simplify and increase the rate of the processing of data from track detectors. This provides a possibility of processing large data arrays and considerably improves their statistical significance. This fact predetermines the development of new experiments which plan to use large-volume targets, large-area emulsion, and solid-state track detectors [1]. In this regard, the problem of training qualified physicists who are capable of operating modern automatic equipment is very important. Annually, about ten Moscow students master the new methods, working at the Lebedev Physical Institute at the PAVICOM facility [2 4]. Most students specializing in high-energy physics are only given an idea of archaic manual methods of the processing of data from track detectors. In 2005, on the basis of the PAVICOM facility and the physicstraining course of Moscow State University, a new training work was prepared. This work is devoted to the determination of the energy of neutrons passing through a nuclear emulsion. It provides the possibility of acquiring basic practical skills of the processing of data from track detectors using automatic equipment and can be included in the educational process of students of any physical faculty. Those who have mastered the methods of automatic data processing in a simple and pictorial example of track detectors will be able to apply their knowledge in various fields of science and technique. Formulation of training works for pregraduate and graduate students is a new additional aspect of application of the PAVICOM facility described earlier in [4].

Label-free integrative pharmacology on-target of drugs at the β2-adrenergic receptor

NASA Astrophysics Data System (ADS)

Ferrie, Ann M.; Sun, Haiyan; Fang, Ye

2011-07-01

We describe a label-free integrative pharmacology on-target (iPOT) method to assess the pharmacology of drugs at the β2-adrenergic receptor. This method combines dynamic mass redistribution (DMR) assays using an array of probe molecule-hijacked cells with similarity analysis. The whole cell DMR assays track cell system-based, ligand-directed, and kinetics-dependent biased activities of the drugs, and translates their on-target pharmacology into numerical descriptors which are subject to similarity analysis. We demonstrate that the approach establishes an effective link between the label-free pharmacology and in vivo therapeutic indications of drugs.

Low, slow, small target recognition based on spatial vision network

NASA Astrophysics Data System (ADS)

Cheng, Zhao; Guo, Pei; Qi, Xin

2018-03-01

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

Computing Satellite Maneuvers For A Repeating Ground Track

NASA Technical Reports Server (NTRS)

Shapiro, Bruce

1994-01-01

TOPEX/POSEIDON Ground Track Maintenance Maneuver Targeting Program (GTARG) assists in designing maneuvers to maintain orbit of TOPEX/POSEIDON satellite. Targeting strategies used either maximize time between maneuvers or force control band exit to occur at specified intervals. Runout mode allows for ground-track propagation without targeting. GTARG incorporates analytic mean-element propagation algorithm accounting for all perturbations known to cause significant variations in ground track. Perturbations include oblateness of Earth, luni-solar gravitation, drag, thrusts associated with impulsive maneuvers, and unspecified fixed forces acting on satellite in direction along trajectory. Written in VAX-FORTRAN.

Poly (dopamine) coated superparamagnetic iron oxide nanocluster for noninvasive labeling, tracking, and targeted delivery of adipose tissue-derived stem cells

PubMed Central

Liao, Naishun; Wu, Ming; Pan, Fan; Lin, Jiumao; Li, Zuanfang; Zhang, Da; Wang, Yingchao; Zheng, Youshi; Peng, Jun; Liu, Xiaolong; Liu, Jingfeng

2016-01-01

Tracking and monitoring of cells in vivo after transplantation can provide crucial information for stem cell therapy. Magnetic resonance imaging (MRI) combined with contrast agents is believed to be an effective and non-invasive technique for cell tracking in living bodies. However, commercial superparamagnetic iron oxide nanoparticles (SPIONs) applied to label cells suffer from shortages such as potential toxicity, low labeling efficiency, and low contrast enhancing. Herein, the adipose tissue-derived stem cells (ADSCs) were efficiently labeled with SPIONs coated with poly (dopamine) (SPIONs cluster@PDA), without affecting their viability, proliferation, apoptosis, surface marker expression, as well as their self-renew ability and multi-differentiation potential. The labeled cells transplanted into the mice through tail intravenous injection exhibited a negative enhancement of the MRI signal in the damaged liver-induced by carbon tetrachloride, and subsequently these homed ADSCs with SPIONs cluster@PDA labeling exhibited excellent repair effects to the damaged liver. Moreover, the enhanced target-homing to tissue of interest and repair effects of SPIONs cluster@PDA-labeled ADSCs could be achieved by use of external magnetic field in the excisional skin wound mice model. Therefore, we provide a facile, safe, noninvasive and sensitive method for external magnetic field targeted delivery and MRI based tracking of transplanted cells in vivo. PMID:26728448

Multi-target Detection, Tracking, and Data Association on Road Networks Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Barkley, Brett E.

A cooperative detection and tracking algorithm for multiple targets constrained to a road network is presented for fixed-wing Unmanned Air Vehicles (UAVs) with a finite field of view. Road networks of interest are formed into graphs with nodes that indicate the target likelihood ratio (before detection) and position probability (after detection). A Bayesian likelihood ratio tracker recursively assimilates target observations until the cumulative observations at a particular location pass a detection criterion. At this point, a target is considered detected and a position probability is generated for the target on the graph. Data association is subsequently used to route future measurements to update the likelihood ratio tracker (for undetected target) or to update a position probability (a previously detected target). Three strategies for motion planning of UAVs are proposed to balance searching for new targets with tracking known targets for a variety of scenarios. Performance was tested in Monte Carlo simulations for a variety of mission parameters, including tracking on road networks with varying complexity and using UAVs at various altitudes.

A general algorithm for peak-tracking in multi-dimensional NMR experiments.

PubMed

Ravel, P; Kister, G; Malliavin, T E; Delsuc, M A

2007-04-01

We present an algorithmic method allowing automatic tracking of NMR peaks in a series of spectra. It consists in a two phase analysis. The first phase is a local modeling of the peak displacement between two consecutive experiments using distance matrices. Then, from the coefficients of these matrices, a value graph containing the a priori set of possible paths used by these peaks is generated. On this set, the minimization under constraint of the target function by a heuristic approach provides a solution to the peak-tracking problem. This approach has been named GAPT, standing for General Algorithm for NMR Peak Tracking. It has been validated in numerous simulations resembling those encountered in NMR spectroscopy. We show the robustness and limits of the method for situations with many peak-picking errors, and presenting a high local density of peaks. It is then applied to the case of a temperature study of the NMR spectrum of the Lipid Transfer Protein (LTP).

Scene-Aware Adaptive Updating for Visual Tracking via Correlation Filters

PubMed Central

Zhang, Sirou; Qiao, Xiaoya

2017-01-01

In recent years, visual object tracking has been widely used in military guidance, human-computer interaction, road traffic, scene monitoring and many other fields. The tracking algorithms based on correlation filters have shown good performance in terms of accuracy and tracking speed. However, their performance is not satisfactory in scenes with scale variation, deformation, and occlusion. In this paper, we propose a scene-aware adaptive updating mechanism for visual tracking via a kernel correlation filter (KCF). First, a low complexity scale estimation method is presented, in which the corresponding weight in five scales is employed to determine the final target scale. Then, the adaptive updating mechanism is presented based on the scene-classification. We classify the video scenes as four categories by video content analysis. According to the target scene, we exploit the adaptive updating mechanism to update the kernel correlation filter to improve the robustness of the tracker, especially in scenes with scale variation, deformation, and occlusion. We evaluate our tracker on the CVPR2013 benchmark. The experimental results obtained with the proposed algorithm are improved by 33.3%, 15%, 6%, 21.9% and 19.8% compared to those of the KCF tracker on the scene with scale variation, partial or long-time large-area occlusion, deformation, fast motion and out-of-view. PMID:29140311

A simultaneously calibration approach for installation and attitude errors of an INS/GPS/LDS target tracker.

PubMed

Cheng, Jianhua; Chen, Daidai; Sun, Xiangyu; Wang, Tongda

2015-02-04

To obtain the absolute position of a target is one of the basic topics for non-cooperated target tracking problems. In this paper, we present a simultaneously calibration method for an Inertial navigation system (INS)/Global position system (GPS)/Laser distance scanner (LDS) integrated system based target positioning approach. The INS/GPS integrated system provides the attitude and position of observer, and LDS offers the distance between the observer and the target. The two most significant errors are taken into jointly consideration and analyzed: (1) the attitude measure error of INS/GPS; (2) the installation error between INS/GPS and LDS subsystems. Consequently, a INS/GPS/LDS based target positioning approach considering these two errors is proposed. In order to improve the performance of this approach, a novel calibration method is designed to simultaneously estimate and compensate these two main errors. Finally, simulations are conducted to access the performance of the proposed target positioning approach and the designed simultaneously calibration method.

Preliminary Orbit Determination System (PODS) for Tracking and Data Relay Satellite System (TDRSS)-tracked target Spacecraft using the homotopy continuation method

NASA Technical Reports Server (NTRS)

Kirschner, S. M.; Samii, M. V.; Broaddus, S. R.; Doll, C. E.

1988-01-01

The Preliminary Orbit Determination System (PODS) provides early orbit determination capability in the Trajectory Computation and Orbital Products System (TCOPS) for a Tracking and Data Relay Satellite System (TDRSS)-tracked spacecraft. PODS computes a set of orbit states from an a priori estimate and six tracking measurements, consisting of any combination of TDRSS range and Doppler tracking measurements. PODS uses the homotopy continuation method to solve a set of nonlinear equations, and it is particularly effective for the case when the a priori estimate is not well known. Since range and Doppler measurements produce multiple states in PODS, a screening technique selects the desired state. PODS is executed in the TCOPS environment and can directly access all operational data sets. At the completion of the preliminary orbit determination, the PODS-generated state, along with additional tracking measurements, can be directly input to the differential correction (DC) process to generate an improved state. To validate the computational and operational capabilities of PODS, tests were performed using simulated TDRSS tracking measurements for the Cosmic Background Explorer (COBE) satellite and using real TDRSS measurements for the Earth Radiation Budget Satellite (ERBS) and the Solar Mesosphere Explorer (SME) spacecraft. The effects of various measurement combinations, varying arc lengths, and levels of degradation of the a priori state vector on the PODS solutions were considered.

Hue distinctiveness overrides category in determining performance in multiple object tracking.

PubMed

Sun, Mengdan; Zhang, Xuemin; Fan, Lingxia; Hu, Luming

2018-02-01

The visual distinctiveness between targets and distractors can significantly facilitate performance in multiple object tracking (MOT), in which color is a feature that has been commonly used. However, the processing of color can be more than "visual." Color is continuous in chromaticity, while it is commonly grouped into discrete categories (e.g., red, green). Evidence from color perception suggested that color categories may have a unique role in visual tasks independent of its chromatic appearance. Previous MOT studies have not examined the effect of chromatic and categorical distinctiveness on tracking separately. The current study aimed to reveal how chromatic (hue) and categorical distinctiveness of color between the targets and distractors affects tracking performance. With four experiments, we showed that tracking performance was largely facilitated by the increasing hue distance between the target set and the distractor set, suggesting that perceptual grouping was formed based on hue distinctiveness to aid tracking. However, we found no color categorical effect, because tracking performance was not significantly different when the targets and distractors were from the same or different categories. It was concluded that the chromatic distinctiveness of color overrides category in determining tracking performance, suggesting a dominant role of perceptual feature in MOT.

Delineating the Neural Signatures of Tracking Spatial Position and Working Memory during Attentive Tracking

PubMed Central

Drew, Trafton; Horowitz, Todd S.; Wolfe, Jeremy M.; Vogel, Edward K.

2015-01-01

In the attentive tracking task, observers track multiple objects as they move independently and unpredictably among visually identical distractors. Although a number of models of attentive tracking implicate visual working memory as the mechanism responsible for representing target locations, no study has ever directly compared the neural mechanisms of the two tasks. In the current set of experiments, we used electrophysiological recordings to delineate similarities and differences between the neural processing involved in working memory and attentive tracking. We found that the contralateral electrophysiological response to the two tasks was similarly sensitive to the number of items attended in both tasks but that there was also a unique contralateral negativity related to the process of monitoring target position during tracking. This signal was absent for periods of time during tracking tasks when objects briefly stopped moving. These results provide evidence that, during attentive tracking, the process of tracking target locations elicits an electrophysiological response that is distinct and dissociable from neural measures of the number of items being attended. PMID:21228175

How Many Objects are You Worth? Quantification of the Self-Motion Load on Multiple Object Tracking

PubMed Central

Thomas, Laura E.; Seiffert, Adriane E.

2011-01-01

Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1–5) among distractors while either staying in one place or moving along a path that was similar to the objects’ motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2) objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects. PMID:21991259

Technical Note: Validation and implementation of a wireless transponder tracking system for gated stereotactic ablative radiotherapy of the liver

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

James, Joshua, E-mail: joshua.james@louisville.edu; Dunlap, Neal E.; Nguyen, Vi Nhan

Purpose: Tracking soft-tissue targets has recently been cleared as a new application of Calypso, an electromagnetic wireless transponder tracking system, allowing for gated treatment of the liver based on the motion of the target volume itself. The purpose of this study is to describe the details of validating the Calypso system for wireless transponder tracking of the liver and to present the clinical workflow for using it to deliver gated stereotactic ablative radiotherapy (SABR). Methods: A commercial 3D diode array motion system was used to evaluate the dynamic tracking accuracy of Calypso when tracking continuous large amplitude motion. It wasmore » then used to perform end-to-end tests to evaluate the dosimetric accuracy of gated beam delivery for liver SABR. In addition, gating limits were investigated to determine how large the gating window can be while still maintaining dosimetric accuracy. The gating latency of the Calypso system was also measured using a customized motion phantom. Results: The average absolute difference between the measured and expected positional offset was 0.3 mm. The 2%/2 mm gamma pass rates for the gated treatment delivery were greater than 97%. When increasing the gating limits beyond the known extent of planned motion, the gamma pass rates decreased as expected. The 2%/2 mm gamma pass rate for a 1, 2, and 3 mm increase in gating limits was measured to be 97.8%, 82.9%, and 61.4%, respectively. The average gating latency was measured to be 63.8 ms for beam-hold and 195.8 ms for beam-on. Four liver patients with 17 total fractions have been successfully treated at our institution. Conclusions: Wireless transponder tracking was validated as a dosimetrically accurate way to provide gated SABR of the liver. The dynamic tracking accuracy of the Calypso system met manufacturer’s specification, even for continuous large amplitude motion that can be encountered when tracking liver tumors close to the diaphragm. The measured beam-hold gating latency was appropriate for targets that will traverse the gating limit each respiratory cycle causing the beam to be interrupted constantly throughout treatment delivery.« less

Estimation of three-dimensional radar tracking using modified extended kalman filter

NASA Astrophysics Data System (ADS)

Aditya, Prima; Apriliani, Erna; Khusnul Arif, Didik; Baihaqi, Komar

2018-03-01

Kalman filter is an estimation method by combining data and mathematical models then developed be extended Kalman filter to handle nonlinear systems. Three-dimensional radar tracking is one of example of nonlinear system. In this paper developed a modification method of extended Kalman filter from the direct decline of the three-dimensional radar tracking case. The development of this filter algorithm can solve the three-dimensional radar measurements in the case proposed in this case the target measured by radar with distance r, azimuth angle θ, and the elevation angle ϕ. Artificial covariance and mean adjusted directly on the three-dimensional radar system. Simulations result show that the proposed formulation is effective in the calculation of nonlinear measurement compared with extended Kalman filter with the value error at 0.77% until 1.15%.

Visual object tracking by correlation filters and online learning

NASA Astrophysics Data System (ADS)

Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

2018-06-01

Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

Development of feedforward control in a dynamic manual tracking task.

PubMed

van Roon, Dominique; Caeyenberghs, Karen; Swinnen, Stephan P; Smits-Engelsman, Bouwien C M

2008-01-01

To examine the development of feedforward control during manual tracking, 117 participants in 5 age groups (6 to 7, 8 to 9, 10 to 11, 12 to 14, and 15 to 17 years) tracked an accelerating dot presented on a monitor by moving an electronic pen on a digitizer. To remain successful at higher target velocities, they had to create a predictive model of the target's motion. The ability to track the target at higher velocities increased, and the application of a feedback-based step-and-hold strategy decreased with age, as shown by increases in maximum target velocity and decreases in number of stops between ages 6-7 and 8-9 and between ages 8-9 and 10-11. The ability to exploit feedforward control in a dynamic tracking task improves significantly with age.

Study of a stereo electro-optical tracker system for the measurement of model deformations at the national transonic facility

NASA Technical Reports Server (NTRS)

Hertel, R. J.

1979-01-01

An electro-optical method to measure the aeroelastic deformations of wind tunnel models is examined. The multitarget tracking performance of one of the two electronic cameras comprising the stereo pair is modeled and measured. The properties of the targets at the model, the camera optics, target illumination, number of targets, acquisition time, target velocities, and tracker performance are considered. The electronic camera system is shown to be capable of locating, measuring, and following the positions of 5 to 50 targets attached to the model at measuring rates up to 5000 targets per second.

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target recognition and tracking routines. Target tracking is based on simplified versions of Kalman filtration. Accuracy of recognition and tracking of implemented versions of the proposed suite of unsupervised algorithms is somewhat degraded from the ideal. Target recognition and tracking by supervised routines and by unsupervised SVM and CLNN routines in the ground-based WSN is evaluated in simulations using published system values and sensor data from vehicular targets in ground-surveillance scenarios. Results are compared with previously published performance for the system of the ground-based sensor network (GSN) and UAV swarm.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

Multisensor data fusion for integrated maritime surveillance

NASA Astrophysics Data System (ADS)

Premji, A.; Ponsford, A. M.

1995-01-01

A prototype Integrated Coastal Surveillance system has been developed on Canada's East Coast to provide effective surveillance out to and beyond the 200 nautical mile Exclusive Economic Zone. The system has been designed to protect Canada's natural resources, and to monitor and control the coastline for smuggling, drug trafficking, and similar illegal activity. This paper describes the Multiple Sensor - Multiple Target data fusion system that has been developed. The fusion processor has been developed around the celebrated Multiple Hypothesis Tracking algorithm which accommodates multiple targets, new targets, false alarms, and missed detections. This processor performs four major functions: plot-to-track association to form individual radar tracks; fusion of radar tracks with secondary sensor reports; track identification and tagging using secondary reports; and track level fusion to form common tracks. Radar data from coherent and non-coherent radars has been used to evaluate the performance of the processor. This paper presents preliminary results.

Multiple Target Laser Designator (MTLD)

DTIC Science & Technology

2007-03-01

Optimized Liquid Crystal Scanning Element Optimize the Nonimaging Predictive Algorithm for Target Ranging, Tracking, and Position Estimation...commercial potential. 3.0 PROGRESS THIS QUARTER 3.1 Optimization of Nonimaging Holographic Antenna for Target Tracking and Position Estimation (Task 6) In

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.

GTARG - The TOPEX/Poseidon ground track maintenance maneuver targeting program

NASA Technical Reports Server (NTRS)

Shapiro, Bruce E.; Bhat, Ramachandra S.

1993-01-01

GTARG is a computer program used to design orbit maintenance maneuvers for the TOPEX/Poseidon satellite. These maneuvers ensure that the ground track is kept within +/-1 km with of an = 9.9 day exact repeat pattern. Maneuver parameters are determined using either of two targeting strategies: longitude targeting, which maximizes the time between maneuvers, and time targeting, in which maneuvers are targeted to occur at specific intervals. The GTARG algorithm propagates nonsingular mean elements, taking into account anticipated error sigma's in orbit determination, Delta v execution, drag prediction and Delta v quantization. A satellite unique drag model is used which incorporates an approximate mean orbital Jacchia-Roberts atmosphere and a variable mean area model. Maneuver Delta v magnitudes are targeted to precisely maintain either the unbiased ground track itself, or a comfortable (3 sigma) error envelope about the unbiased ground track.

Analysis of the track- and dose-averaged LET and LET spectra in proton therapy using the GEANT4 Monte Carlo code

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

Guan, Fada; Peeler, Christopher; Taleei, Reza

Purpose: The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the GEANT 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from GEANT 4 simulations to correlate with biological effectiveness of therapeutic protons. Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LET{sub t} and dose-averaged LET, LET{sub d}) using GEANT 4 for different tracking stepmore » size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LET{sub t} and LET{sub d} of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose. Results: Simulation results showed that the step limit effect was small for LET{sub t} but significant for LET{sub d}. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in GEANT 4 can result in incorrect LET{sub d} calculation results in the dose plateau region for small step limits. The erroneous LET{sub d} results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in GEANT 4. The incorrect LET{sub d} values lead to substantial differences in the calculated RBE. Conclusions: When the GEANT 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LET{sub t} in the dose plateau region and LET{sub d} around the Bragg peak. For a large step limit, i.e., 500 μm, LET{sub d} is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LET{sub d} and LET{sub t} becomes positive.« less

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.

The semantic category-based grouping in the Multiple Identity Tracking task.

PubMed

Wei, Liuqing; Zhang, Xuemin; Li, Zhen; Liu, Jingyao

2018-01-01

In the Multiple Identity Tracking (MIT) task, categorical distinctions between targets and distractors have been found to facilitate tracking (Wei, Zhang, Lyu, & Li in Frontiers in Psychology, 7, 589, 2016). The purpose of this study was to further investigate the reasons for the facilitation effect, through six experiments. The results of Experiments 1-3 excluded the potential explanations of visual distinctiveness, attentional distribution strategy, and a working memory mechanism, respectively. When objects' visual information was preserved and categorical information was removed, the facilitation effect disappeared, suggesting that the visual distinctiveness between targets and distractors was not the main reason for the facilitation effect. Moreover, the facilitation effect was not the result of strategically shifting the attentional distribution, because the targets received more attention than the distractors in all conditions. Additionally, the facilitation effect did not come about because the identities of targets were encoded and stored in visual working memory to assist in the recovery from tracking errors; when working memory was disturbed by the object identities changing during tracking, the facilitation effect still existed. Experiments 4 and 5 showed that observers grouped targets together and segregated them from distractors on the basis of their categorical information. By doing this, observers could largely avoid distractor interference with tracking and improve tracking performance. Finally, Experiment 6 indicated that category-based grouping is not an automatic, but a goal-directed and effortful, strategy. In summary, the present findings show that a semantic category-based target-grouping mechanism exists in the MIT task, which is likely to be the major reason for the tracking facilitation effect.

Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2016-05-01

Motion video analysis is a challenging task, particularly if real-time analysis is required. It is therefore an important issue how to provide suitable assistance for the human operator. Given that the use of customized video analysis systems is more and more established, one supporting measure is to provide system functions which perform subtasks of the analysis. Recent progress in the development of automated image exploitation algorithms allow, e.g., real-time moving target tracking. Another supporting measure is to provide a user interface which strives to reduce the perceptual, cognitive and motor load of the human operator for example by incorporating the operator's visual focus of attention. A gaze-enhanced user interface is able to help here. This work extends prior work on automated target recognition, segmentation, and tracking algorithms as well as about the benefits of a gaze-enhanced user interface for interaction with moving targets. We also propose a prototypical system design aiming to combine both the qualities of the human observer's perception and the automated algorithms in order to improve the overall performance of a real-time video analysis system. In this contribution, we address two novel issues analyzing gaze-based interaction with target tracking algorithms. The first issue extends the gaze-based triggering of a target tracking process, e.g., investigating how to best relaunch in the case of track loss. The second issue addresses the initialization of tracking algorithms without motion segmentation where the operator has to provide the system with the object's image region in order to start the tracking algorithm.

Multitarget tracking in cluttered environment for a multistatic passive radar system under the DAB/DVB network

NASA Astrophysics Data System (ADS)

Shi, Yi Fang; Park, Seung Hyo; Song, Taek Lyul

2017-12-01

The target tracking using multistatic passive radar in a digital audio/video broadcast (DAB/DVB) network with illuminators of opportunity faces two main challenges: the first challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional association ambiguity between the measurements and targets, which introduces a significantly complex three-dimensional (3-D) data association problem among the target-measurement illuminator, this is because all the illuminators transmit the same carrier frequency signals and signals transmitted by different illuminators but reflected via the same target become indistinguishable; the other challenge is that only the bistatic range and range-rate measurements are available while the angle information is unavailable or of very poor quality. In this paper, the authors propose a new target tracking algorithm directly in three-dimensional (3-D) Cartesian coordinates with the capability of track management using the probability of target existence as a track quality measure. The proposed algorithm is termed sequential processing-joint integrated probabilistic data association (SP-JIPDA), which applies the modified sequential processing technique to resolve the additional association ambiguity between measurements and illuminators. The SP-JIPDA algorithm sequentially operates the JIPDA tracker to update each track for each illuminator with all the measurements in the common measurement set at each time. For reasons of fair comparison, the existing modified joint probabilistic data association (MJPDA) algorithm that addresses the 3-D data association problem via "supertargets" using gate grouping and provides tracks directly in 3-D Cartesian coordinates, is enhanced by incorporating the probability of target existence as an effective track quality measure for track management. Both algorithms deal with nonlinear observations using the extended Kalman filtering. A simulation study is performed to verify the superiority of the proposed SP-JIPDA algorithm over the MJIPDA in this multistatic passive radar system.

Target matching based on multi-view tracking

NASA Astrophysics Data System (ADS)

Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Adaptive Filter Techniques for Optical Beam Jitter Control and Target Tracking

DTIC Science & Technology

2008-12-01

OPTICAL BEAM JITTER CONTROL AND TARGET TRACKING Michael J. Beerer Civilian, United States Air Force B.S., University of California Irvine, 2006...TECHNIQUES FOR OPTICAL BEAM JITTER CONTROL AND TARGET TRACKING by Michael J. Beerer December 2008 Thesis Advisor: Brij N. Agrawal Co...DATE December 2008 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Adaptive Filter Techniques for Optical Beam Jitter

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

PubMed

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

Moving target tracking through distributed clustering in directional sensor networks.

PubMed

Enayet, Asma; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

2014-12-18

The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works.

Moving Target Tracking through Distributed Clustering in Directional Sensor Networks

PubMed Central

Enayet, Asma; Razzaque, Md. Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

2014-01-01

The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works. PMID:25529205

Markerless gating for lung cancer radiotherapy based on machine learning techniques

NASA Astrophysics Data System (ADS)

Lin, Tong; Li, Ruijiang; Tang, Xiaoli; Dy, Jennifer G.; Jiang, Steve B.

2009-03-01

In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks—ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing

PubMed Central

2018-01-01

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets. PMID:29562642

Adaptive bearing estimation and tracking of multiple targets in a realistic passive sonar scenario

NASA Astrophysics Data System (ADS)

Rajagopal, R.; Challa, Subhash; Faruqi, Farhan A.; Rao, P. R.

1997-06-01

In a realistic passive sonar environment, the received signal consists of multipath arrivals from closely separated moving targets. The signals are contaminated by spatially correlated noise. The differential MUSIC has been proposed to estimate the DOAs in such a scenario. This method estimates the 'noise subspace' in order to estimate the DOAs. However, the 'noise subspace' estimate has to be updated as and when new data become available. In order to save the computational costs, a new adaptive noise subspace estimation algorithm is proposed in this paper. The salient features of the proposed algorithm are: (1) Noise subspace estimation is done by QR decomposition of the difference matrix which is formed from the data covariance matrix. Thus, as compared to standard eigen-decomposition based methods which require O(N3) computations, the proposed method requires only O(N2) computations. (2) Noise subspace is updated by updating the QR decomposition. (3) The proposed algorithm works in a realistic sonar environment. In the second part of the paper, the estimated bearing values are used to track multiple targets. In order to achieve this, the nonlinear system/linear measurement extended Kalman filtering proposed is applied. Computer simulation results are also presented to support the theory.

Space moving target detection and tracking method in complex background

NASA Astrophysics Data System (ADS)

Lv, Ping-Yue; Sun, Sheng-Li; Lin, Chang-Qing; Liu, Gao-Rui

2018-06-01

The background of the space-borne detectors in real space-based environment is extremely complex and the signal-to-clutter ratio is very low (SCR ≈ 1), which increases the difficulty for detecting space moving targets. In order to solve this problem, an algorithm combining background suppression processing based on two-dimensional least mean square filter (TDLMS) and target enhancement based on neighborhood gray-scale difference (GSD) is proposed in this paper. The latter can filter out most of the residual background clutter processed by the former such as cloud edge. Through this procedure, both global and local SCR have obtained substantial improvement, indicating that the target has been greatly enhanced. After removing the detector's inherent clutter region through connected domain processing, the image only contains the target point and the isolated noise, in which the isolated noise could be filtered out effectively through multi-frame association. The proposed algorithm in this paper has been compared with some state-of-the-art algorithms for moving target detection and tracking tasks. The experimental results show that the performance of this algorithm is the best in terms of SCR gain, background suppression factor (BSF) and detection results.

Eye Tracking of Occluded Self-Moved Targets: Role of Haptic Feedback and Hand-Target Dynamics.

PubMed

Danion, Frederic; Mathew, James; Flanagan, J Randall

2017-01-01

Previous studies on smooth pursuit eye movements have shown that humans can continue to track the position of their hand, or a target controlled by the hand, after it is occluded, thereby demonstrating that arm motor commands contribute to the prediction of target motion driving pursuit eye movements. Here, we investigated this predictive mechanism by manipulating both the complexity of the hand-target mapping and the provision of haptic feedback. Two hand-target mappings were used, either a rigid (simple) one in which hand and target motion matched perfectly or a nonrigid (complex) one in which the target behaved as a mass attached to the hand by means of a spring. Target animation was obtained by asking participants to oscillate a lightweight robotic device that provided (or not) haptic feedback consistent with the target dynamics. Results showed that as long as 7 s after target occlusion, smooth pursuit continued to be the main contributor to total eye displacement (∼60%). However, the accuracy of eye-tracking varied substantially across experimental conditions. In general, eye-tracking was less accurate under the nonrigid mapping, as reflected by higher positional and velocity errors. Interestingly, haptic feedback helped to reduce the detrimental effects of target occlusion when participants used the nonrigid mapping, but not when they used the rigid one. Overall, we conclude that the ability to maintain smooth pursuit in the absence of visual information can extend to complex hand-target mappings, but the provision of haptic feedback is critical for the maintenance of accurate eye-tracking performance.

Eye Tracking of Occluded Self-Moved Targets: Role of Haptic Feedback and Hand-Target Dynamics

PubMed Central

Mathew, James

2017-01-01

Abstract Previous studies on smooth pursuit eye movements have shown that humans can continue to track the position of their hand, or a target controlled by the hand, after it is occluded, thereby demonstrating that arm motor commands contribute to the prediction of target motion driving pursuit eye movements. Here, we investigated this predictive mechanism by manipulating both the complexity of the hand-target mapping and the provision of haptic feedback. Two hand-target mappings were used, either a rigid (simple) one in which hand and target motion matched perfectly or a nonrigid (complex) one in which the target behaved as a mass attached to the hand by means of a spring. Target animation was obtained by asking participants to oscillate a lightweight robotic device that provided (or not) haptic feedback consistent with the target dynamics. Results showed that as long as 7 s after target occlusion, smooth pursuit continued to be the main contributor to total eye displacement (∼60%). However, the accuracy of eye-tracking varied substantially across experimental conditions. In general, eye-tracking was less accurate under the nonrigid mapping, as reflected by higher positional and velocity errors. Interestingly, haptic feedback helped to reduce the detrimental effects of target occlusion when participants used the nonrigid mapping, but not when they used the rigid one. Overall, we conclude that the ability to maintain smooth pursuit in the absence of visual information can extend to complex hand-target mappings, but the provision of haptic feedback is critical for the maintenance of accurate eye-tracking performance. PMID:28680964

Overview of Microbial Source Tracking Methods Targeting Human Fecal Pollution Sources

EPA Science Inventory

Exposure to human fecal waste can be a public health risk dueto the presence of human pathogens. Human fecal pollutioncan be introduced into water resources from damagedsewer lines, faulty septic systems, combined sewer overflows,illicit dumping activities, and even recreational ...

Evaluation of Two PCR-Based Swine-Specific Fecal Source Tracking Assays (Poster)

EPA Science Inventory

Several PCR-based methods have been proposed to identify swine fecal pollution in environmental waters. However, the specificity and distribution of these targets have not been adequately assessed. Consequently, the utility of these assays in identifying swine fecal contamination...

Optimal Quantization Scheme for Data-Efficient Target Tracking via UWSNs Using Quantized Measurements.

PubMed

Zhang, Senlin; Chen, Huayan; Liu, Meiqin; Zhang, Qunfei

2017-11-07

Target tracking is one of the broad applications of underwater wireless sensor networks (UWSNs). However, as a result of the temporal and spatial variability of acoustic channels, underwater acoustic communications suffer from an extremely limited bandwidth. In order to reduce network congestion, it is important to shorten the length of the data transmitted from local sensors to the fusion center by quantization. Although quantization can reduce bandwidth cost, it also brings about bad tracking performance as a result of information loss after quantization. To solve this problem, this paper proposes an optimal quantization-based target tracking scheme. It improves the tracking performance of low-bit quantized measurements by minimizing the additional covariance caused by quantization. The simulation demonstrates that our scheme performs much better than the conventional uniform quantization-based target tracking scheme and the increment of the data length affects our scheme only a little. Its tracking performance improves by only 4.4% from 2- to 3-bit, which means our scheme weakly depends on the number of data bits. Moreover, our scheme also weakly depends on the number of participate sensors, and it can work well in sparse sensor networks. In a 6 × 6 × 6 sensor network, compared with 4 × 4 × 4 sensor networks, the number of participant sensors increases by 334.92%, while the tracking accuracy using 1-bit quantized measurements improves by only 50.77%. Overall, our optimal quantization-based target tracking scheme can achieve the pursuit of data-efficiency, which fits the requirements of low-bandwidth UWSNs.

Affine Transform to Reform Pixel Coordinates of EOG Signals for Controlling Robot Manipulators Using Gaze Motions

PubMed Central

Rusydi, Muhammad Ilhamdi; Sasaki, Minoru; Ito, Satoshi

2014-01-01

Biosignals will play an important role in building communication between machines and humans. One of the types of biosignals that is widely used in neuroscience are electrooculography (EOG) signals. An EOG has a linear relationship with eye movement displacement. Experiments were performed to construct a gaze motion tracking method indicated by robot manipulator movements. Three operators looked at 24 target points displayed on a monitor that was 40 cm in front of them. Two channels (Ch1 and Ch2) produced EOG signals for every single eye movement. These signals were converted to pixel units by using the linear relationship between EOG signals and gaze motion distances. The conversion outcomes were actual pixel locations. An affine transform method is proposed to determine the shift of actual pixels to target pixels. This method consisted of sequences of five geometry processes, which are translation-1, rotation, translation-2, shear and dilatation. The accuracy was approximately 0.86° ± 0.67° in the horizontal direction and 0.54° ± 0.34° in the vertical. This system successfully tracked the gaze motions not only in direction, but also in distance. Using this system, three operators could operate a robot manipulator to point at some targets. This result shows that the method is reliable in building communication between humans and machines using EOGs. PMID:24919013

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

Passive RFID Rotation Dimension Reduction via Aggregation

NASA Astrophysics Data System (ADS)

Matthews, Eric

Radio Frequency IDentification (RFID) has applications in object identification, position, and orientation tracking. RFID technology can be applied in hospitals for patient and equipment tracking, stores and warehouses for product tracking, robots for self-localisation, tracking hazardous materials, or locating any other desired object. Efficient and accurate algorithms that perform localisation are required to extract meaningful data beyond simple identification. A Received Signal Strength Indicator (RSSI) is the strength of a received radio frequency signal used to localise passive and active RFID tags. Many factors affect RSSI such as reflections, tag rotation in 3D space, and obstacles blocking line-of-sight. LANDMARC is a statistical method for estimating tag location based on a target tag's similarity to surrounding reference tags. LANDMARC does not take into account the rotation of the target tag. By either aggregating multiple reference tag positions at various rotations, or by determining a rotation value for a newly read tag, we can perform an expected value calculation based on a comparison to the k-most similar training samples via an algorithm called K-Nearest Neighbours (KNN) more accurately. By choosing the average as the aggregation function, we improve the relative accuracy of single-rotation LANDMARC localisation by 10%, and any-rotation localisation by 20%.

CR-39 track detector calibration for H, He, and C ions from 0.1-0.5 MeV up to 5 MeV for laser-induced nuclear fusion product identification.

PubMed

Baccou, C; Yahia, V; Depierreux, S; Neuville, C; Goyon, C; Consoli, F; De Angelis, R; Ducret, J E; Boutoux, G; Rafelski, J; Labaune, C

2015-08-01

Laser-accelerated ion beams can be used in many applications and, especially, to initiate nuclear reactions out of thermal equilibrium. We have experimentally studied aneutronic fusion reactions induced by protons accelerated by the Target Normal Sheath Acceleration mechanism, colliding with a boron target. Such experiments require a rigorous method to identify the reaction products (alpha particles) collected in detectors among a few other ion species such as protons or carbon ions, for example. CR-39 track detectors are widely used because they are mostly sensitive to ions and their efficiency is near 100%. We present a complete calibration of CR-39 track detector for protons, alpha particles, and carbon ions. We give measurements of their track diameters for energy ranging from hundreds of keV to a few MeV and for etching times between 1 and 8 h. We used these results to identify alpha particles in our experiments on proton-boron fusion reactions initiated by laser-accelerated protons. We show that their number clearly increases when the boron fuel is preformed in a plasma state.

CR-39 track detector calibration for H, He, and C ions from 0.1-0.5 MeV up to 5 MeV for laser-induced nuclear fusion product identification

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

Baccou, C., E-mail: claire.baccou@polytechnique.edu; Yahia, V.; Labaune, C.

Laser-accelerated ion beams can be used in many applications and, especially, to initiate nuclear reactions out of thermal equilibrium. We have experimentally studied aneutronic fusion reactions induced by protons accelerated by the Target Normal Sheath Acceleration mechanism, colliding with a boron target. Such experiments require a rigorous method to identify the reaction products (alpha particles) collected in detectors among a few other ion species such as protons or carbon ions, for example. CR-39 track detectors are widely used because they are mostly sensitive to ions and their efficiency is near 100%. We present a complete calibration of CR-39 track detectormore » for protons, alpha particles, and carbon ions. We give measurements of their track diameters for energy ranging from hundreds of keV to a few MeV and for etching times between 1 and 8 h. We used these results to identify alpha particles in our experiments on proton-boron fusion reactions initiated by laser-accelerated protons. We show that their number clearly increases when the boron fuel is preformed in a plasma state.« less

Multiple-Object Tracking in Children: The "Catch the Spies" Task

ERIC Educational Resources Information Center

Trick, L.M.; Jaspers-Fayer, F.; Sethi, N.

2005-01-01

Multiple-object tracking involves simultaneously tracking positions of a number of target-items as they move among distractors. The standard version of the task poses special challenges for children, demanding extended concentration and the ability to distinguish targets from identical-looking distractors, and may thus underestimate children's…

Target tracking and surveillance by fusing stereo and RFID information

NASA Astrophysics Data System (ADS)

Raza, Rana H.; Stockman, George C.

2012-06-01

Ensuring security in high risk areas such as an airport is an important but complex problem. Effectively tracking personnel, containers, and machines is a crucial task. Moreover, security and safety require understanding the interaction of persons and objects. Computer vision (CV) has been a classic tool; however, variable lighting, imaging, and random occlusions present difficulties for real-time surveillance, resulting in erroneous object detection and trajectories. Determining object ID via CV at any instance of time in a crowded area is computationally prohibitive, yet the trajectories of personnel and objects should be known in real time. Radio Frequency Identification (RFID) can be used to reliably identify target objects and can even locate targets at coarse spatial resolution, while CV provides fuzzy features for target ID at finer resolution. Our research demonstrates benefits obtained when most objects are "cooperative" by being RFID tagged. Fusion provides a method to simplify the correspondence problem in 3D space. A surveillance system can query for unique object ID as well as tag ID information, such as target height, texture, shape and color, which can greatly enhance scene analysis. We extend geometry-based tracking so that intermittent information on ID and location can be used in determining a set of trajectories of N targets over T time steps. We show that partial-targetinformation obtained through RFID can reduce computation time (by 99.9% in some cases) and also increase the likelihood of producing correct trajectories. We conclude that real-time decision-making should be possible if the surveillance system can integrate information effectively between the sensor level and activity understanding level.

Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

DTIC Science & Technology

2010-01-01

target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

Real-time FDG PET Guidance during Biopsies and Radiofrequency Ablation Using Multimodality Fusion with Electromagnetic Navigation

PubMed Central

Kadoury, Samuel; Abi-Jaoudeh, Nadine; Levy, Elliot B.; Maass-Moreno, Roberto; Krücker, Jochen; Dalal, Sandeep; Xu, Sheng; Glossop, Neil; Wood, Bradford J.

2011-01-01

Purpose: To assess the feasibility of combined electromagnetic device tracking and computed tomography (CT)/ultrasonography (US)/fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) fusion for real-time feedback during percutaneous and intraoperative biopsies and hepatic radiofrequency (RF) ablation. Materials and Methods: In this HIPAA-compliant, institutional review board–approved prospective study with written informed consent, 25 patients (17 men, eight women) underwent 33 percutaneous and three intraoperative biopsies of 36 FDG-avid targets between November 2007 and August 2010. One patient underwent biopsy and RF ablation of an FDG-avid hepatic focus. Targets demonstrated heterogeneous FDG uptake or were not well seen or were totally inapparent at conventional imaging. Preprocedural FDG PET scans were rigidly registered through a semiautomatic method to intraprocedural CT scans. Coaxial biopsy needle introducer tips and RF ablation electrode guider needle tips containing electromagnetic sensor coils were spatially tracked through an electromagnetic field generator. Real-time US scans were registered through a fiducial-based method, allowing US scans to be fused with intraprocedural CT and preacquired FDG PET scans. A visual display of US/CT image fusion with overlaid coregistered FDG PET targets was used for guidance; navigation software enabled real-time biopsy needle and needle electrode navigation and feedback. Results: Successful fusion of real-time US to coregistered CT and FDG PET scans was achieved in all patients. Thirty-one of 36 biopsies were diagnostic (malignancy in 18 cases, benign processes in 13 cases). RF ablation resulted in resolution of targeted FDG avidity, with no local treatment failure during short follow-up (56 days). Conclusion: Combined electromagnetic device tracking and image fusion with real-time feedback may facilitate biopsies and ablations of focal FDG PET abnormalities that would be challenging with conventional image guidance. © RSNA, 2011 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101985/-/DC1 PMID:21734159

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

PubMed

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

Robust 3D Position Estimation in Wide and Unconstrained Indoor Environments

PubMed Central

Mossel, Annette

2015-01-01

In this paper, a system for 3D position estimation in wide, unconstrained indoor environments is presented that employs infrared optical outside-in tracking of rigid-body targets with a stereo camera rig. To overcome limitations of state-of-the-art optical tracking systems, a pipeline for robust target identification and 3D point reconstruction has been investigated that enables camera calibration and tracking in environments with poor illumination, static and moving ambient light sources, occlusions and harsh conditions, such as fog. For evaluation, the system has been successfully applied in three different wide and unconstrained indoor environments, (1) user tracking for virtual and augmented reality applications, (2) handheld target tracking for tunneling and (3) machine guidance for mining. The results of each use case are discussed to embed the presented approach into a larger technological and application context. The experimental results demonstrate the system’s capabilities to track targets up to 100 m. Comparing the proposed approach to prior art in optical tracking in terms of range coverage and accuracy, it significantly extends the available tracking range, while only requiring two cameras and providing a relative 3D point accuracy with sub-centimeter deviation up to 30 m and low-centimeter deviation up to 100 m. PMID:26694388

Motion reconstruction of animal groups: From schooling fish to swarming mosquitoes

NASA Astrophysics Data System (ADS)

Butail, Sachit

The long-term goal of this research is to provide kinematic data for the design and validation of spatial models of collective behavior in animal groups. The specific research objective of this dissertation is to apply methods from nonlinear estimation and computer vision to construct multi-target tracking systems that process multi-view calibrated video to reconstruct the three-dimensional movement of animals in a group. We adapt the tracking systems for the study of two animal species: Danio aequipinnatus, a common species of schooling fish, and Anopheles gambiae, the most important vector of malaria in sub-Saharan Africa. Together these tracking systems span variability in target size on image, density, and movement. For tracking fish, we automatically initialize, predict, and reconstruct shape trajectories of multiple fish through occlusions. For mosquitoes, which appear as faded streaks on in-field footage, we provide methods to extract velocity information from the streaks, adaptively seek missing measurements, and resolve occlusions within a multi-hypothesis framework. In each case the research has yielded an unprecedented volume of trajectory data for subsequent analysis. We present kinematic data of fast-start response in fish schools and first-ever trajectories of wild mosquito swarming and mating events. The broader impact of this work is to advance the understanding of animal groups for the design of bio-inspired robotic systems, where, similar to the animal groups we study, the collective is able to perform tasks far beyond the capabilities of a single inexpensive robot.

Real-time auto-adaptive margin generation for MLC-tracked radiotherapy

NASA Astrophysics Data System (ADS)

Glitzner, M.; Fast, M. F.; de Senneville, B. Denis; Nill, S.; Oelfke, U.; Lagendijk, J. J. W.; Raaymakers, B. W.; Crijns, S. P. M.

2017-01-01

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing {{V}90 %} in the underdosed area about 47 % and 41 % , respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors.

Visual Target Tracking on the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Kim, Won S.; Biesiadecki, Jeffrey J.; Ali, Khaled S.

2008-01-01

Visual Target Tracking (VTT) has been implemented in the new Mars Exploration Rover (MER) Flight Software (FSW) R9.2 release, which is now running on both Spirit and Opportunity rovers. Applying the normalized cross-correlation (NCC) algorithm with template image magnification and roll compensation on MER Navcam images, VTT tracks the target and enables the rover to approach the target within a few cm over a 10 m traverse. Each VTT update takes 1/2 to 1 minute on the rovers, 2-3 times faster than one Visual Odometry (Visodom) update. VTT is a key element to achieve a target approach and instrument placement over a 10-m run in a single sol in contrast to the original baseline of 3 sols. VTT has been integrated into the MER FSW so that it can operate with any combination of blind driving, Autonomous Navigation (Autonav) with hazard avoidance, and Visodom. VTT can either guide the rover towards the target or simply image the target as the rover drives by. Three recent VTT operational checkouts on Opportunity were all successful, tracking the selected target reliably within a few pixels.

Adaptive early detection ML/PDA estimator for LO targets with EO sensors

NASA Astrophysics Data System (ADS)

Chummun, Muhammad R.; Kirubarajan, Thiagalingam; Bar-Shalom, Yaakov

2000-07-01

The batch Maximum Likelihood Estimator, combined with Probabilistic Data (ML-PDA), has been shown to be effective in acquiring low observable (LO) - low SNR - non-maneuvering targets in the presence of heavy clutter. The use of signal strength or amplitude information (AI) in the ML-PDA estimator with AI in a sliding-window fashion, to detect high- speed targets in heavy clutter using electro-optical (EO) sensors. The initial time and the length of the sliding-window are adjusted adaptively according to the information content of the received measurements. A track validation scheme via hypothesis testing is developed to confirm the estimated track, that is, the presence of a target, in each window. The sliding-window ML-PDA approach, together with track validation, enables early detection by rejecting noninformative scans, target reacquisition in case of temporary target disappearance and the handling of targets with speeds evolving over time. The proposed algorithm is shown to detect the target, which is hidden in as many as 600 false alarms per scan, 10 frames earlier than the Multiple Hypothesis Tracking (MHT) algorithm.

Technology survey on video face tracking

NASA Astrophysics Data System (ADS)

Zhang, Tong; Gomes, Herman Martins

2014-03-01

With the pervasiveness of monitoring cameras installed in public areas, schools, hospitals, work places and homes, video analytics technologies for interpreting these video contents are becoming increasingly relevant to people's lives. Among such technologies, human face detection and tracking (and face identification in many cases) are particularly useful in various application scenarios. While plenty of research has been conducted on face tracking and many promising approaches have been proposed, there are still significant challenges in recognizing and tracking people in videos with uncontrolled capturing conditions, largely due to pose and illumination variations, as well as occlusions and cluttered background. It is especially complex to track and identify multiple people simultaneously in real time due to the large amount of computation involved. In this paper, we present a survey on literature and software that are published or developed during recent years on the face tracking topic. The survey covers the following topics: 1) mainstream and state-of-the-art face tracking methods, including features used to model the targets and metrics used for tracking; 2) face identification and face clustering from face sequences; and 3) software packages or demonstrations that are available for algorithm development or trial. A number of publically available databases for face tracking are also introduced.

Eye tracking a self-moved target with complex hand-target dynamics

PubMed Central

Landelle, Caroline; Montagnini, Anna; Madelain, Laurent

2016-01-01

Previous work has shown that the ability to track with the eye a moving target is substantially improved when the target is self-moved by the subject's hand compared with when being externally moved. Here, we explored a situation in which the mapping between hand movement and target motion was perturbed by simulating an elastic relationship between the hand and target. Our objective was to determine whether the predictive mechanisms driving eye-hand coordination could be updated to accommodate this complex hand-target dynamics. To fully appreciate the behavioral effects of this perturbation, we compared eye tracking performance when self-moving a target with a rigid mapping (simple) and a spring mapping as well as when the subject tracked target trajectories that he/she had previously generated when using the rigid or spring mapping. Concerning the rigid mapping, our results confirmed that smooth pursuit was more accurate when the target was self-moved than externally moved. In contrast, with the spring mapping, eye tracking had initially similar low spatial accuracy (though shorter temporal lag) in the self versus externally moved conditions. However, within ∼5 min of practice, smooth pursuit improved in the self-moved spring condition, up to a level similar to the self-moved rigid condition. Subsequently, when the mapping unexpectedly switched from spring to rigid, the eye initially followed the expected target trajectory and not the real one, thereby suggesting that subjects used an internal representation of the new hand-target dynamics. Overall, these results emphasize the stunning adaptability of smooth pursuit when self-maneuvering objects with complex dynamics. PMID:27466129

A novel approach to Hough Transform for implementation in fast triggers

NASA Astrophysics Data System (ADS)

Pozzobon, Nicola; Montecassiano, Fabio; Zotto, Pierluigi

2016-10-01

Telescopes of position sensitive detectors are common layouts in charged particles tracking, and programmable logic devices, such as FPGAs, represent a viable choice for the real-time reconstruction of track segments in such detector arrays. A compact implementation of the Hough Transform for fast triggers in High Energy Physics, exploiting a parameter reduction method, is proposed, targeting the reduction of the needed storage or computing resources in current, or next future, state-of-the-art FPGA devices, while retaining high resolution over a wide range of track parameters. The proposed approach is compared to a Standard Hough Transform with particular emphasis on their application to muon detectors. In both cases, an original readout implementation is modeled.

A comparison of foveated acquisition and tracking performance relative to uniform resolution approaches

NASA Astrophysics Data System (ADS)

Dubuque, Shaun; Coffman, Thayne; McCarley, Paul; Bovik, A. C.; Thomas, C. William

2009-05-01

Foveated imaging has been explored for compression and tele-presence, but gaps exist in the study of foveated imaging applied to acquisition and tracking systems. Results are presented from two sets of experiments comparing simple foveated and uniform resolution targeting (acquisition and tracking) algorithms. The first experiments measure acquisition performance when locating Gabor wavelet targets in noise, with fovea placement driven by a mutual information measure. The foveated approach is shown to have lower detection delay than a notional uniform resolution approach when using video that consumes equivalent bandwidth. The second experiments compare the accuracy of target position estimates from foveated and uniform resolution tracking algorithms. A technique is developed to select foveation parameters that minimize error in Kalman filter state estimates. Foveated tracking is shown to consistently outperform uniform resolution tracking on an abstract multiple target task when using video that consumes equivalent bandwidth. Performance is also compared to uniform resolution processing without bandwidth limitations. In both experiments, superior performance is achieved at a given bandwidth by foveated processing because limited resources are allocated intelligently to maximize operational performance. These findings indicate the potential for operational performance improvements over uniform resolution systems in both acquisition and tracking tasks.

Magnetic navigation for thoracic aortic stent-graft deployment using ultrasound image guidance.

PubMed

Luo, Zhe; Cai, Junfeng; Wang, Su; Zhao, Qiang; Peters, Terry M; Gu, Lixu

2013-03-01

We propose a system for thoracic aortic stent-graft deployment that employs a magnetic tracking system (MTS) and intraoperative ultrasound (US). A preoperative plan is first performed using a general public utilities-accelerated cardiac modeling method to determine the target position of the stent-graft. During the surgery, an MTS is employed to track sensors embedded in the catheter, cannula, and the US probe, while a fiducial landmark based registration is used to map the patient's coordinate to the image coordinate. The surgical target is tracked in real time via a calibrated intraoperative US image. Under the guidance of the MTS integrated with the real-time US images, the stent-graft can be deployed to the target position without the use of ionizing radiation. This navigation approach was validated using both phantom and animal studies. In the phantom study, we demonstrate a US calibration accuracy of 1.5 ± 0.47 mm, and a deployment error of 1.4 ± 0.16 mm. In the animal study, we performed experiments on five porcine subjects and recorded fiducial, target, and deployment errors of 2.5 ± 0.32, 4.2 ± 0.78, and 2.43 ± 0.69 mm, respectively. These results demonstrate that delivery and deployment of thoracic stent-graft under MTS-guided navigation using US imaging is feasible and appropriate for clinical application.

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

Transbronchial needle aspiration with a new electromagnetically-tracked TBNA needle

NASA Astrophysics Data System (ADS)

Choi, Jae; Popa, Teo; Gruionu, Lucian

2009-02-01

Transbronchial needle aspiration (TBNA) is a common method used to collect tissue for diagnosis of different chest diseases and for staging lung cancer, but the procedure has technical limitations. These limitations are mostly related to the difficulty of accurately placing the biopsy needles into the target mass. Currently, pulmonologists plan TBNA by examining a number of Computed Tomography (CT) scan slices before the operation. Then, they manipulate the bronchoscope down the respiratory track and blindly direct the biopsy. Thus, the biopsy success rate is low. The diagnostic yield of TBNA is approximately 70 percent. To enhance the accuracy of TBNA, we developed a TBNA needle with a tip position that can be electromagnetically tracked. The needle was used to estimate the bronchoscope's tip position and enable the creation of corresponding virtual bronchoscopic images from a preoperative CT scan. The TBNA needle was made with a flexible catheter embedding Wang Transbronchial Histology Needle and a sensor tracked by electromagnetic field generator. We used Aurora system for electromagnetic tracking. We also constructed an image-guided research prototype system incorporating the needle and providing a user-friendly interface to assist the pulmonologist in targeting lesions. To test the feasibility of the accuracy of the newly developed electromagnetically-tracked needle, a phantom study was conducted in the interventional suite at Georgetown University Hospital. Five TBNA simulations with a custom-made phantom with a bronchial tree were performed. The experimental results show that our device has potential to enhance the accuracy of TBNA.

Within-Hemifield Competition in Early Visual Areas Limits the Ability to Track Multiple Objects with Attention

PubMed Central

Alvarez, George A.; Cavanagh, Patrick

2014-01-01

It is much easier to divide attention across the left and right visual hemifields than within the same visual hemifield. Here we investigate whether this benefit of dividing attention across separate visual fields is evident at early cortical processing stages. We measured the steady-state visual evoked potential, an oscillatory response of the visual cortex elicited by flickering stimuli, of moving targets and distractors while human observers performed a tracking task. The amplitude of responses at the target frequencies was larger than that of the distractor frequencies when participants tracked two targets in separate hemifields, indicating that attention can modulate early visual processing when it is divided across hemifields. However, these attentional modulations disappeared when both targets were tracked within the same hemifield. These effects were not due to differences in task performance, because accuracy was matched across the tracking conditions by adjusting target speed (with control conditions ruling out effects due to speed alone). To investigate later processing stages, we examined the P3 component over central-parietal scalp sites that was elicited by the test probe at the end of the trial. The P3 amplitude was larger for probes on targets than on distractors, regardless of whether attention was divided across or within a hemifield, indicating that these higher-level processes were not constrained by visual hemifield. These results suggest that modulating early processing stages enables more efficient target tracking, and that within-hemifield competition limits the ability to modulate multiple target representations within the hemifield maps of the early visual cortex. PMID:25164651

Robustness of external/internal correlation models for real-time tumor tracking to breathing motion variations

NASA Astrophysics Data System (ADS)

Seregni, M.; Cerveri, P.; Riboldi, M.; Pella, A.; Baroni, G.

2012-11-01

In radiotherapy, organ motion mitigation by means of dynamic tumor tracking requires continuous information about the internal tumor position, which can be estimated relying on external/internal correlation models as a function of external surface surrogates. In this work, we propose a validation of a time-independent artificial neural networks-based tumor tracking method in the presence of changes in the breathing pattern, evaluating the performance on two datasets. First, simulated breathing motion traces were specifically generated to include gradually increasing respiratory irregularities. Then, seven publically available human liver motion traces were analyzed for the assessment of tracking accuracy, whose sensitivity with respect to the structural parameters of the model was also investigated. Results on simulated data showed that the proposed method was not affected by hysteretic target trajectories and it was able to cope with different respiratory irregularities, such as baseline drift and internal/external phase shift. The analysis of the liver motion traces reported an average RMS error equal to 1.10 mm, with five out of seven cases below 1 mm. In conclusion, this validation study proved that the proposed method is able to deal with respiratory irregularities both in controlled and real conditions.

Wavelength band selection method for multispectral target detection.

PubMed

Karlholm, Jörgen; Renhorn, Ingmar

2002-11-10

A framework is proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory we derive a cost function that is minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare targets and clutter with known spectral distribution. The method may be used, e.g., in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance, but the required high frame rate prevents the use of hyperspectral sensors.

Target-type probability combining algorithms for multisensor tracking

NASA Astrophysics Data System (ADS)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

A Comparative Assessment of Track Plates to Quantify Fine Scale Variations in the Relative Abundance of Norway Rats in Urban Slums

PubMed Central

Begon, Mike; Diggle, Peter J.; Serrano, Soledad; Reis, Mitermayer G.; Childs, James E.; Ko, Albert I.; Costa, Federico

2016-01-01

Norway rats (Rattus norvegicus) living in urban environments are a critical public health and economic problem, particularly in urban slums where residents are at a higher risk for rat borne diseases, yet convenient methods to quantitatively assess population sizes are lacking. We evaluated track plates as a method to determine rat distribution and relative abundance in a complex urban slum environment by correlating the presence and intensity of rat-specific marks on track plates with findings from rat infestation surveys and trapping of rats to population exhaustion. To integrate the zero-inflated track plate data we developed a two-component mixture model with one binary and one censored continuous component. Track plate mark-intensity was highly correlated with signs of rodent infestation (all coefficients between 0.61 and 0.79 and all p-values < 0.05). Moreover, the mean level of pre-trapping rat-mark intensity on plates was significantly associated with the number of rats captured subsequently (Odds ratio1.38; 95% CI 1.19-1.61) and declined significantly following trapping (Odds ratio 0.86; 95% CI 0.78-0.95). Track plates provided robust proxy measurements of rat abundance and distribution and detected rat presence even when populations appeared ‘trapped out’. Tracking plates are relatively easy and inexpensive methods that can be used to intensively sample settings such as urban slums, where traditional trapping or mark-recapture studies are impossible to implement, and therefore the results can inform and assess the impact of targeted urban rodent control campaigns. PMID:27453682

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

Research on simulation technology of full-path infrared tail flame tracking of photoelectric theodolite in complicated environment

NASA Astrophysics Data System (ADS)

Wu, Hai-ying; Zhang, San-xi; Liu, Biao; Yue, Peng; Weng, Ying-hui

2018-02-01

The photoelectric theodolite is an important scheme to realize the tracking, detection, quantitative measurement and performance evaluation of weapon systems in ordnance test range. With the improvement of stability requirements for target tracking in complex environment, infrared scene simulation with high sense of reality and complex interference has become an indispensable technical way to evaluate the track performance of photoelectric theodolite. And the tail flame is the most important infrared radiation source of the weapon system. The dynamic tail flame with high reality is a key element for the photoelectric theodolite infrared scene simulation and imaging tracking test. In this paper, an infrared simulation method for the full-path tracking of tail flame by photoelectric theodolite is proposed aiming at the faint boundary, irregular, multi-regulated points. In this work, real tail images are employed. Simultaneously, infrared texture conversion technology is used to generate DDS texture for a particle system map. Thus, dynamic real-time tail flame simulation results with high fidelity from the theodolite perspective can be gained in the tracking process.

Visualization of air and metal inhomogeneities in phantoms irradiated by carbon ion beams using prompt secondary ions.

PubMed

Gaa, T; Reinhart, M; Hartmann, B; Jakubek, J; Soukup, P; Jäkel, O; Martišíková, M

2017-06-01

Non-invasive methods for monitoring of the therapeutic ion beam extension in the patient are desired in order to handle deteriorations of the dose distribution related to changes of the patient geometry. In carbon ion radiotherapy, secondary light ions represent one of potential sources of information about the dose distribution in the irradiated target. The capability to detect range-changing inhomogeneities inside of an otherwise homogeneous phantom, based on single track measurements, is addressed in this paper. Air and stainless steel inhomogeneities, with PMMA equivalent thickness of 10mm and 4.8mm respectively, were inserted into a PMMA-phantom at different positions in depth. Irradiations of the phantom with therapeutic carbon ion pencil beams were performed at the Heidelberg Ion Beam Therapy Center. Tracks of single secondary ions escaping the phantom under irradiation were detected with a pixelized semiconductor detector Timepix. The statistical relevance of the found differences between the track distributions with and without inhomogeneities was evaluated. Measured shifts of the distal edge and changes in the fragmentation probability make the presence of inhomogeneities inserted into the traversed medium detectable for both, 10mm air cavities and 1mm thick stainless steel. Moreover, the method was shown to be sensitive also on their position in the observed body, even when localized behind the Bragg-peak. The presented results demonstrate experimentally, that the method using distributions of single secondary ion tracks is sensitive to the changes of homogeneity of the traversed material for the studied geometries of the target. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Multiple-hypothesis multiple-model line tracking

NASA Astrophysics Data System (ADS)

Pace, Donald W.; Owen, Mark W.; Cox, Henry

2000-07-01

Passive sonar signal processing generally includes tracking of narrowband and/or broadband signature components observed on a Lofargram or on a Bearing-Time-Record (BTR) display. Fielded line tracking approaches to date have been recursive and single-hypthesis-oriented Kalman- or alpha-beta filters, with no mechanism for considering tracking alternatives beyond the most recent scan of measurements. While adaptivity is often built into the filter to handle changing track dynamics, these approaches are still extensions of single target tracking solutions to multiple target tracking environment. This paper describes an application of multiple-hypothesis, multiple target tracking technology to the sonar line tracking problem. A Multiple Hypothesis Line Tracker (MHLT) is developed which retains the recursive minimum-mean-square-error tracking behavior of a Kalman Filter in a maximum-a-posteriori delayed-decision multiple hypothesis context. Multiple line track filter states are developed and maintained using the interacting multiple model (IMM) state representation. Further, the data association and assignment problem is enhanced by considering line attribute information (line bandwidth and SNR) in addition to beam/bearing and frequency fit. MHLT results on real sonar data are presented to demonstrate the benefits of the multiple hypothesis approach. The utility of the system in cluttered environments and particularly in crossing line situations is shown.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Multiple-object tracking while driving: the multiple-vehicle tracking task.

PubMed

Lochner, Martin J; Trick, Lana M

2014-11-01

Many contend that driving an automobile involves multiple-object tracking. At this point, no one has tested this idea, and it is unclear how multiple-object tracking would coordinate with the other activities involved in driving. To address some of the initial and most basic questions about multiple-object tracking while driving, we modified the tracking task for use in a driving simulator, creating the multiple-vehicle tracking task. In Experiment 1, we employed a dual-task methodology to determine whether there was interference between tracking and driving. Findings suggest that although it is possible to track multiple vehicles while driving, driving reduces tracking performance, and tracking compromises headway and lane position maintenance while driving. Modified change-detection paradigms were used to assess whether there were change localization advantages for tracked targets in multiple-vehicle tracking. When changes occurred during a blanking interval, drivers were more accurate (Experiment 2a) and ~250 ms faster (Experiment 2b) at locating the vehicle that changed when it was a target rather than a distractor in tracking. In a more realistic driving task where drivers had to brake in response to the sudden onset of brake lights in one of the lead vehicles, drivers were more accurate at localizing the vehicle that braked if it was a tracking target, although there was no advantage in terms of braking response time. Overall, results suggest that multiple-object tracking is possible while driving and perhaps even advantageous in some situations, but further research is required to determine whether multiple-object tracking is actually used in day-to-day driving.

Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

PubMed

Kim, Han-Ul; Kim, Chang-Su

2017-08-01

In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

Sensor Compromise Detection in Multiple-Target Tracking Systems

PubMed Central

Doucette, Emily A.; Curtis, Jess W.

2018-01-01

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

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

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Target Information Processing: A Joint Decision and Estimation Approach

DTIC Science & Technology

2012-03-29

ground targets ( track - before - detect ) using computer cluster and graphics processing unit. Estimation and filtering theory is one of the most important...targets ( track - before - detect ) using computer cluster and graphics processing unit. Estimation and filtering theory is one of the most important

The Extended-Image Tracking Technique Based on the Maximum Likelihood Estimation

NASA Technical Reports Server (NTRS)

Tsou, Haiping; Yan, Tsun-Yee

2000-01-01

This paper describes an extended-image tracking technique based on the maximum likelihood estimation. The target image is assume to have a known profile covering more than one element of a focal plane detector array. It is assumed that the relative position between the imager and the target is changing with time and the received target image has each of its pixels disturbed by an independent additive white Gaussian noise. When a rotation-invariant movement between imager and target is considered, the maximum likelihood based image tracking technique described in this paper is a closed-loop structure capable of providing iterative update of the movement estimate by calculating the loop feedback signals from a weighted correlation between the currently received target image and the previously estimated reference image in the transform domain. The movement estimate is then used to direct the imager to closely follow the moving target. This image tracking technique has many potential applications, including free-space optical communications and astronomy where accurate and stabilized optical pointing is essential.

Decoupled tracking and thermal monitoring of non-stationary targets.

PubMed

Tan, Kok Kiong; Zhang, Yi; Huang, Sunan; Wong, Yoke San; Lee, Tong Heng

2009-10-01

Fault diagnosis and predictive maintenance address pertinent economic issues relating to production systems as an efficient technique can continuously monitor key health parameters and trigger alerts when critical changes in these variables are detected, before they lead to system failures and production shutdowns. In this paper, we present a decoupled tracking and thermal monitoring system which can be used on non-stationary targets of closed systems such as machine tools. There are three main contributions from the paper. First, a vision component is developed to track moving targets under a monitor. Image processing techniques are used to resolve the target location to be tracked. Thus, the system is decoupled and applicable to closed systems without the need for a physical integration. Second, an infrared temperature sensor with a built-in laser for locating the measurement spot is deployed for non-contact temperature measurement of the moving target. Third, a predictive motion control system holds the thermal sensor and follows the moving target efficiently to enable continuous temperature measurement and monitoring.

ACT-Vision: active collaborative tracking for multiple PTZ cameras

NASA Astrophysics Data System (ADS)

Broaddus, Christopher; Germano, Thomas; Vandervalk, Nicholas; Divakaran, Ajay; Wu, Shunguang; Sawhney, Harpreet

2009-04-01

We describe a novel scalable approach for the management of a large number of Pan-Tilt-Zoom (PTZ) cameras deployed outdoors for persistent tracking of humans and vehicles, without resorting to the large fields of view of associated static cameras. Our system, Active Collaborative Tracking - Vision (ACT-Vision), is essentially a real-time operating system that can control hundreds of PTZ cameras to ensure uninterrupted tracking of target objects while maintaining image quality and coverage of all targets using a minimal number of sensors. The system ensures the visibility of targets between PTZ cameras by using criteria such as distance from sensor and occlusion.

Objective Methods to Test Visual Dysfunction in the Presence of Cognitive Impairment

DTIC Science & Technology

2015-12-01

the eye and 3) purposeful eye movements to track targets that are resolved. Major Findings: Three major objective tests of vision were successfully...developed and optimized to detect disease. These were 1) the pupil light reflex (either comparing the two eyes or independently evaluating each eye ...separately for retina or optic nerve damage, 2) eye movement based analysis of target acquisition, fixation, and eccentric viewing as a means of

Extrapolating target tracks

NASA Astrophysics Data System (ADS)

Van Zandt, James R.

2012-05-01

Steady-state performance of a tracking filter is traditionally evaluated immediately after a track update. However, there is commonly a further delay (e.g., processing and communications latency) before the tracks can actually be used. We analyze the accuracy of extrapolated target tracks for four tracking filters: Kalman filter with the Singer maneuver model and worst-case correlation time, with piecewise constant white acceleration, and with continuous white acceleration, and the reduced state filter proposed by Mookerjee and Reifler.1, 2 Performance evaluation of a tracking filter is significantly simplified by appropriate normalization. For the Kalman filter with the Singer maneuver model, the steady-state RMS error immediately after an update depends on only two dimensionless parameters.3 By assuming a worst case value of target acceleration correlation time, we reduce this to a single parameter without significantly changing the filter performance (within a few percent for air tracking).4 With this simplification, we find for all four filters that the RMS errors for the extrapolated state are functions of only two dimensionless parameters. We provide simple analytic approximations in each case.

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

PubMed Central

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R.; Demirer, R. Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios. PMID:22438713

A model for combined targeting and tracking tasks in computer applications.

PubMed

Senanayake, Ransalu; Hoffmann, Errol R; Goonetilleke, Ravindra S

2013-11-01

Current models for targeted-tracking are discussed and shown to be inadequate as a means of understanding the combined task of tracking, as in the Drury's paradigm, and having a final target to be aimed at, as in the Fitts' paradigm. It is shown that the task has to be split into components that are, in general, performed sequentially and have a movement time component dependent on the difficulty of the individual component of the task. In some cases, the task time may be controlled by the Fitts' task difficulty, and in others, it may be dominated by the Drury's task difficulty. Based on an experiment carried out that captured movement time in combinations of visually controlled and ballistic movements, a model for movement time in targeted-tracking was developed.

An optimal model-based trajectory following architecture synthesising the lateral adaptive preview strategy and longitudinal velocity planning for highly automated vehicle

NASA Astrophysics Data System (ADS)

Cao, Haotian; Song, Xiaolin; Zhao, Song; Bao, Shan; Huang, Zhi

2017-08-01

Automated driving has received a broad of attentions from the academia and industry, since it is effective to greatly reduce the severity of potential traffic accidents and achieve the ultimate automobile safety and comfort. This paper presents an optimal model-based trajectory following architecture for highly automated vehicle in its driving tasks such as automated guidance or lane keeping, which includes a velocity-planning module, a steering controller and a velocity-tracking controller. The velocity-planning module considering the optimal time-consuming and passenger comforts simultaneously could generate a smooth velocity profile. The robust sliding mode control (SMC) steering controller with adaptive preview time strategy could not only track the target path well, but also avoid a big lateral acceleration occurred in its path-tracking progress due to a fuzzy-adaptive preview time mechanism introduced. In addition, an SMC controller with input-output linearisation method for velocity tracking is built and validated. Simulation results show this trajectory following architecture are effective and feasible for high automated driving vehicle, comparing with the Driver-in-the-Loop simulations performed by an experienced driver and novice driver, respectively. The simulation results demonstrate that the present trajectory following architecture could plan a satisfying longitudinal speed profile, track the target path well and safely when dealing with different road geometry structure, it ensures a good time efficiency and driving comfort simultaneously.

Visual Target Tracking on the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Kim, Won; Biesiadecki, Jeffrey; Ali, Khaled

2008-01-01

Visual target tracking (VTT) software has been incorporated into Release 9.2 of the Mars Exploration Rover (MER) flight software, now running aboard the rovers Spirit and Opportunity. In the VTT operation (see figure), the rover is driven in short steps between stops and, at each stop, still images are acquired by actively aimed navigation cameras (navcams) on a mast on the rover (see artistic rendition). The VTT software processes the digitized navcam images so as to track a target reliably and to make it possible to approach the target accurately to within a few centimeters over a 10-m traverse.

Stereo Electro-optical Tracking System (SETS)

NASA Astrophysics Data System (ADS)

Koenig, E. W.

1984-09-01

The SETS is a remote, non-contacting, high-accuracy tracking system for the measurement of deflection of models in the National Transonic Facility at Langley Research Center. The system consists of four electronically scanned image dissector trackers which locate the position of Light Emitting Diodes embedded in the wing or body of aircraft models. Target location data is recorded on magnetic tape for later 3-D processing. Up to 63 targets per model may be tracked at typical rates of 1280 targets per second and to precision of 0.02mm at the target under the cold (-193 C) environment of the NTF tunnel.

Real-time tracking of tumor motions and deformations along the leaf travel direction with the aid of a synchronized dynamic MLC leaf sequencer.

PubMed

Tacke, Martin; Nill, Simeon; Oelfke, Uwe

2007-11-21

Advanced radiotherapeutical techniques like intensity-modulated radiation therapy (IMRT) are based on an accurate knowledge of the location of the radiation target. An accurate dose delivery, therefore, requires a method to account for the inter- and intrafractional target motion and the target deformation occurring during the course of treatment. A method to compensate in real time for changes in the position and shape of the target is the use of a dynamic multileaf collimator (MLC) technique which can be devised to automatically arrange the treatment field according to real-time image information. So far, various approaches proposed for leaf sequencers have had to rely on a priori known target motion data and have aimed to optimize the overall treatment time. Since for a real-time dose delivery the target motion is not known a priori, the velocity range of the leading leaves is restricted by a safety margin to c x v(max) while the following leaves can travel with an additional maximum speed to compensate for the respective target movements. Another aspect to be considered is the tongue and groove effect. A uniform radiation field can only be achieved if the leaf movements are synchronized. The method presented in this note is the first to combine a synchronizing sequencer and real-time tracking with a dynamic MLC. The newly developed algorithm is capable of online optimizing the leaf velocities by minimizing the overall treatment time while at the same time it synchronizes the leaf trajectories in order to avoid the tongue and groove effect. The simultaneous synchronization is performed with the help of an online-calculated mid-time leaf trajectory which is common for all leaf pairs and which takes into account the real-time target motion and deformation information.

Prostate Bed Motion During Intensity-Modulated Radiotherapy Treatment

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

Klayton, Tracy; Price, Robert; Buyyounouski, Mark K.

Purpose: Conformal radiation therapy in the postprostatectomy setting requires accurate setup and localization of the prostatic fossa. In this series, we report prostate bed localization and motion characteristics, using data collected from implanted radiofrequency transponders. Methods and Materials: The Calypso four-dimensional localization system uses three implanted radiofrequency transponders for daily target localization and real-time tracking throughout a course of radiation therapy. We reviewed the localization and tracking reports for 20 patients who received ultrasonography-guided placement of Calypso transponders within the prostate bed prior to a course of intensity-modulated radiation therapy at Fox Chase Cancer Center. Results: At localization, prostate bedmore » displacement relative to bony anatomy exceeded 5 mm in 9% of fractions in the anterior-posterior (A-P) direction and 21% of fractions in the superior-inferior (S-I) direction. The three-dimensional vector length from skin marks to Calypso alignment exceeded 1 cm in 24% of all 652 fractions with available setup data. During treatment, the target exceeded the 5-mm tracking limit for at least 30 sec in 11% of all fractions, generally in the A-P or S-I direction. In the A-P direction, target motion was twice as likely to move posteriorly, toward the rectum, than anteriorly. Fifteen percent of all treatments were interrupted for repositioning, and 70% of patients were repositioned at least once during their treatment course. Conclusion: Set-up errors and motion of the prostatic fossa during radiotherapy are nontrivial, leading to potential undertreatment of target and excess normal tissue toxicity if not taken into account during treatment planning. Localization and real-time tracking of the prostate bed via implanted Calypso transponders can be used to improve the accuracy of plan delivery.« less

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.

SLATE: scanning laser automatic threat extraction

NASA Astrophysics Data System (ADS)

Clark, David J.; Prickett, Shaun L.; Napier, Ashley A.; Mellor, Matthew P.

2016-10-01

SLATE is an Autonomous Sensor Module (ASM) designed to work with the SAPIENT system providing accurate location tracking and classifications of targets that pass through its field of view. The concept behind the SLATE ASM is to produce a sensor module that provides a complementary view of the world to the camera-based systems that are usually used for wide area surveillance. Cameras provide a hi-fidelity, human understandable view of the world with which tracking and identification algorithms can be used. Unfortunately, positioning and tracking in a 3D environment is difficult to implement robustly, making location-based threat assessment challenging. SLATE uses a Scanning Laser Rangefinder (SLR) that provides precise (<1cm) positions, sizes, shapes and velocities of targets within its field-of-view (FoV). In this paper we will discuss the development of the SLATE ASM including the techniques used to track and classify detections that move through the field of view of the sensor providing the accurate tracking information to the SAPIENT system. SLATE's ability to locate targets precisely allows subtle boundary-crossing judgements, e.g. on which side of a chain-link fence a target is. SLATE's ability to track targets in 3D throughout its FoV enables behavior classification such as running and walking which can provide an indication of intent and help reduce false alarm rates.

Automatic tracking of cells for video microscopy in patch clamp experiments

PubMed Central

2014-01-01

Background Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Methods Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). Results We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. Conclusion The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices. PMID:24946774

Performance of automatic scanning microscope for nuclear emulsion experiments

NASA Astrophysics Data System (ADS)

Güler, A. Murat; Altınok, Özgür

2015-12-01

The impressive improvements in scanning technology and methods let nuclear emulsion to be used as a target in recent large experiments. We report the performance of an automatic scanning microscope for nuclear emulsion experiments. After successful calibration and alignment of the system, we have reached 99% tracking efficiency for the minimum ionizing tracks that penetrating through the emulsions films. The automatic scanning system is successfully used for the scanning of emulsion films in the OPERA experiment and plan to use for the next generation of nuclear emulsion experiments.

Performance of automatic scanning microscope for nuclear emulsion experiments

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

Güler, A. Murat, E-mail: mguler@newton.physics.metu.edu.tr; Altınok, Özgür; Tufts University, Medford, MA 02155

The impressive improvements in scanning technology and methods let nuclear emulsion to be used as a target in recent large experiments. We report the performance of an automatic scanning microscope for nuclear emulsion experiments. After successful calibration and alignment of the system, we have reached 99% tracking efficiency for the minimum ionizing tracks that penetrating through the emulsions films. The automatic scanning system is successfully used for the scanning of emulsion films in the OPERA experiment and plan to use for the next generation of nuclear emulsion experiments.

A New Method for Preparing Mesenchymal Stem Cells and Labeling with Ferumoxytol for Cell Tracking by MRI.

PubMed

Liu, Li; Tseng, Lanya; Ye, Qing; Wu, Yijen L; Bain, Daniel J; Ho, Chien

2016-05-18

Mesenchymal stem cells (MSCs) are among the major stem cells used for cell therapy and regenerative medicine. In-vivo cell-tracking by magnetic resonance imaging (MRI) is crucial for regenerative medicine, allowing verification that the transplanted cells reach the targeted sites. Cellular MRI combined with superparamagnetic iron-oxide (SPIO) contrast agents is an effective cell-tracking method. Here, we are reporting a new "bio-mimicry" method by making use of the "in-vivo environment" of MSCs to prepare native MSCs, so that (i) the phagocytic activity of cultured MSCs can be recovered and expanded MSCs can be ex-vivo labeled with Ferumoxytol, which is currently the only FDA approved SPIO nanoparticles for human use. Using our new method, 7-day cultured MSCs regain the capability to take up Ferumoxytol and exhibit an intracellular iron concentration of 2.50 ± 0.50 pg/MSC, comparable to that obtained by using Ferumoxytol-heparin-protamine nanocomplex; and (ii) cells can be re-sized to more native size, reducing from 32.0 ± 7.2 μm to 19.5 ± 5.2 μm. Our method can be very useful for expanding MSCs and labeling with Ferumoxytol, without the need for transfection agents and/or electroporation, allowing cell-tracking by MRI in both pre-clinical and clinical studies.

A New Method for Preparing Mesenchymal Stem Cells and Labeling with Ferumoxytol for Cell Tracking by MRI

PubMed Central

Liu, Li; Tseng, Lanya; Ye, Qing; Wu, Yijen L.; Bain, Daniel J.; Ho, Chien

2016-01-01

Mesenchymal stem cells (MSCs) are among the major stem cells used for cell therapy and regenerative medicine. In-vivo cell-tracking by magnetic resonance imaging (MRI) is crucial for regenerative medicine, allowing verification that the transplanted cells reach the targeted sites. Cellular MRI combined with superparamagnetic iron-oxide (SPIO) contrast agents is an effective cell-tracking method. Here, we are reporting a new “bio-mimicry” method by making use of the “in-vivo environment” of MSCs to prepare native MSCs, so that (i) the phagocytic activity of cultured MSCs can be recovered and expanded MSCs can be ex-vivo labeled with Ferumoxytol, which is currently the only FDA approved SPIO nanoparticles for human use. Using our new method, 7-day cultured MSCs regain the capability to take up Ferumoxytol and exhibit an intracellular iron concentration of 2.50 ± 0.50 pg/MSC, comparable to that obtained by using Ferumoxytol-heparin-protamine nanocomplex; and (ii) cells can be re-sized to more native size, reducing from 32.0 ± 7.2 μm to 19.5 ± 5.2 μm. Our method can be very useful for expanding MSCs and labeling with Ferumoxytol, without the need for transfection agents and/or electroporation, allowing cell-tracking by MRI in both pre-clinical and clinical studies. PMID:27188664

The Role of 3T Magnetic Resonance Imaging for Targeting the Human Subthalamic Nucleus in Deep Brain Stimulation for Parkinson Disease.

PubMed

Longhi, Michele; Ricciardi, Giuseppe; Tommasi, Giorgio; Nicolato, Antonio; Foroni, Roberto; Bertolasi, Laura; Beltramello, Alberto; Moretto, Giuseppe; Tinazzi, Michele; Gerosa, Massimo

2015-05-01

Chronic stimulation of the human subthalamic nucleus (STN) is gradually becoming accepted as a long-term therapeutic option for patients with advanced Parkinson disease (PD). 3Tesla (T) magnetic resonance imaging (MRI) improves contrast resolution in basal ganglia nuclei containing high levels of iron, because of magnetic susceptibility effects that increase significantly as the magnetic field gets higher. This phenomenon can be used for better visualization of the STN and may reduce the time necessary for detailed microrecording (MER) mapping, increasing surgery efficacy and lowering morbidity. The objective of this retrospective study is to analyze a population of 20 deep brain stimulation (DBS) electrode implanted patients with PD divided into two groups in which different targeting methods were used. Mean age was 56 years (range 37 to 69 years). Mean disease duration was 11.6 years. Mean follow-up was 12 months (range 6 to 36 months). Patients were divided into two groups: Group A contained 6 patients who underwent STN targeting using 1T stereotactic (T1w + T2w) MRI plus STN indirect atlas derived targeting. Group B consisted of 14 patients who underwent STN targeting using 3T nonstereotactic (T2w) MRI fused with 1T T1w stereotactic MRI and STN direct targeting. For statistical analysis, we compared (five different parameters in both (matched) groups: Unified Parkinson's disease rating scale (UPDRS) score reduction (medication off before surgery against stimulation on/medication off after surgery), postoperative drug reduction, duration of surgery, the "central preoperative track" chosen as final implantation track during surgery, and correspondence between the targeted STN and the intraoperative neurophysiologic data. Mean UPDRS III score reduction (medication off/stimulation on versus preoperative medication off) was 69% in Group A and 74% in Group B (p = 0.015, log-rank test) respectively. Postoperatively, antiparkinsonian treatment was reduced by 66% in Group A and 75% in Group B (p = 0.006, log-rank test). The preoperative "central" track (which corresponds to ideal STN targeting) proved to be the most clinically effective in 2/12 leads for Group A versus 21/28 for Group B (p < 0.001).Neurophysiologic data confirmed these results; the hypothetical target was confirmed by MER data in 76% of tracks in Group A, and in 75% of tracks in Group B (p < 0.001, univariate and multivariate analysis). 3T MRI appears to be a useful tool in STN-DBS preoperative targeting. Neurophysiologic testing remains fundamental to determine lead deepness (and prevent clinical side effects. Georg Thieme Verlag KG Stuttgart · New York.

Radar signature generation for feature-aided tracking research

NASA Astrophysics Data System (ADS)

Piatt, Teri L.; Sherwood, John U.; Musick, Stanton H.

2005-05-01

Accurately associating sensor kinematic reports to known tracks, new tracks, or clutter is one of the greatest obstacles to effective track estimation. Feature-aiding is one technology that is emerging to address this problem, and it is expected that adding target features will aid report association by enhancing track accuracy and lengthening track life. The Sensor's Directorate of the Air Force Research Laboratory is sponsoring a challenge problem called Feature-Aided Tracking of Stop-move Objects (FATSO). The long-range goal of this research is to provide a full suite of public data and software to encourage researchers from government, industry, and academia to participate in radar-based feature-aided tracking research. The FATSO program is currently releasing a vehicle database coupled to a radar signature generator. The completed FATSO system will incorporate this database/generator into a Monte Carlo simulation environment for evaluating multiplatform/multitarget tracking scenarios. The currently released data and software contains the following: eight target models, including a tank, ammo hauler, and self-propelled artillery vehicles; and a radar signature generator capable of producing SAR and HRR signatures of all eight modeled targets in almost any configuration or articulation. In addition, the signature generator creates Z-buffer data, label map data, and radar cross-section prediction and allows the user to add noise to an image while varying sensor-target geometry (roll, pitch, yaw, squint). Future capabilities of this signature generator, such as scene models and EO signatures as well as details of the complete FATSO testbed, are outlined.

Design of a Holonic Control Architecture for Distributed Sensor Management

DTIC Science & Technology

2009-09-01

Tracking tasks require only intermit - tent access to the sensors to maintain a given track quality. The higher the specified quality, the more often...resolution of the sensor (i.e., sensor mode), which can be adjusted to compensate for fast moving targets tracked over long ranges, or slower moving...but provides higher data update rates that are beneficial when tracking fast agile targets (i.e., a fighter). Table A.2 illustrates the dependence of

Reallocating attention during multiple object tracking.

PubMed

Ericson, Justin M; Christensen, James C

2012-07-01

Wolfe, Place, and Horowitz (Psychonomic Bulletin & Review 14:344-349, 2007) found that participants were relatively unaffected by selecting and deselecting targets while performing a multiple object tracking task, such that maintaining tracking was possible for longer durations than the few seconds typically studied. Though this result was generally consistent with other findings on tracking duration (Franconeri, Jonathon, & Scimeca Psychological Science 21:920-925, 2010), it was inconsistent with research involving cuing paradigms, specifically precues (Pylyshyn & Annan Spatial Vision 19:485-504, 2006). In the present research, we broke down the addition and removal of targets into separate conditions and incorporated a simple performance model to evaluate the costs associated with the selection and deselection of moving targets. Across three experiments, we demonstrated evidence against a cost being associated with any shift in attention, but rather that varying the type of cue used for target deselection produces no additional cost to performance and that hysteresis effects are not induced by a reduction in tracking load.

Glucose administration prior to a divided attention task improves tracking performance but not word recognition: evidence against differential memory enhancement?

PubMed

Scholey, Andrew B; Sünram-Lea, Sandra I; Greer, Joanna; Elliott, Jade; Kennedy, David O

2009-01-01

The cognition-enhancing effects of glucose administration to humans have been well-documented; however, it remains unclear whether this effect preferentially targets episodic memory or other cognitive domains. The effect of glucose on the allocation of attentional resources during memory encoding was assessed using a sensitive dual-attention paradigm. One hundred and twenty volunteers (mean age 21.60, SD 4.89, 77 females) took part in this randomised, double-blind, placebo-controlled, parallel groups study where each consumed a 25-g glucose drink or a placebo. Half of the participants in each drink condition attempted to track a moving on-screen target during auditory word presentation. The distance between the cursor and the tracking target was used as an index of attentional cost during encoding. Effects of drink and tracking on recognition memory and drink on tracking performance were assessed. Self-rated appetite and mood were co-monitored. Co-performing the tracking task significantly impaired memory performance irrespective of drink condition. In the placebo-tracking condition, there was a cost to tracking manifest as greater deviation from target during and immediately following word presentation. Compared with placebo, the glucose drink significantly improved tracking performance during encoding. There were significant time-related changes in thirst and alertness ratings but these were not differentially affected by drink or tracking conditions. Tracking but not memory was enhanced by glucose. This finding suggests that, under certain task conditions, glucose administrations does not preferentially enhance memory performance. One mechanism through which glucose acts as a cognition enhancer is through allowing greater allocation of attentional resources.

A new markerless patient-to-image registration method using a portable 3D scanner.

PubMed

Fan, Yifeng; Jiang, Dongsheng; Wang, Manning; Song, Zhijian

2014-10-01

Patient-to-image registration is critical to providing surgeons with reliable guidance information in the application of image-guided neurosurgery systems. The conventional point-matching registration method, which is based on skin markers, requires expensive and time-consuming logistic support. Surface-matching registration with facial surface scans is an alternative method, but the registration accuracy is unstable and the error in the more posterior parts of the head is usually large because the scan range is limited. This study proposes a new surface-matching method using a portable 3D scanner to acquire a point cloud of the entire head to perform the patient-to-image registration. A new method for transforming the scan points from the device space into the patient space without calibration and tracking was developed. Five positioning targets were attached on a reference star, and their coordinates in the patient space were measured prior. During registration, the authors moved the scanner around the head to scan its entire surface as well as the positioning targets, and the scanner generated a unique point cloud in the device space. The coordinates of the positioning targets in the device space were automatically detected by the scanner, and a spatial transformation from the device space to the patient space could be calculated by registering them to their coordinates in the patient space that had been measured prior. A three-step registration algorithm was then used to register the patient space to the image space. The authors evaluated their method on a rigid head phantom and an elastic head phantom to verify its practicality and to calculate the target registration error (TRE) in different regions of the head phantoms. The authors also conducted an experiment with a real patient's data to test the feasibility of their method in the clinical environment. In the phantom experiments, the mean fiducial registration error between the device space and the patient space, the mean surface registration error, and the mean TRE of 15 targets on the surface of each phantom were 0.34 ± 0.01 mm and 0.33 ± 0.02 mm, 1.17 ± 0.02 mm and 1.34 ± 0.10 mm, and 1.06 ± 0.11 mm and 1.48 ± 0.21 mm, respectively. When grouping the targets according to their positions on the head, high accuracy was achieved in all parts of the head, and the TREs were similar across different regions. The authors compared their method with the current surface registration methods that use only a part of the facial surface on the elastic phantom, and the mean TRE of 15 targets was 1.48 ± 0.21 mm and 1.98 ± 0.53 mm, respectively. In a clinical experiment, the mean TRE of seven targets on the patient's head surface was 1.92 ± 0.18 mm, which was sufficient to meet clinical requirements. The proposed surface-matching registration method provides sufficient registration accuracy even in the posterior area of the head. The 3D point cloud of the entire head, including the facial surface and the back of the head, can be easily acquired using a portable 3D scanner. The scanner does not need to be calibrated prior or tracked by the optical tracking system during scanning.

Within-hemifield competition in early visual areas limits the ability to track multiple objects with attention.

PubMed

Störmer, Viola S; Alvarez, George A; Cavanagh, Patrick

2014-08-27

It is much easier to divide attention across the left and right visual hemifields than within the same visual hemifield. Here we investigate whether this benefit of dividing attention across separate visual fields is evident at early cortical processing stages. We measured the steady-state visual evoked potential, an oscillatory response of the visual cortex elicited by flickering stimuli, of moving targets and distractors while human observers performed a tracking task. The amplitude of responses at the target frequencies was larger than that of the distractor frequencies when participants tracked two targets in separate hemifields, indicating that attention can modulate early visual processing when it is divided across hemifields. However, these attentional modulations disappeared when both targets were tracked within the same hemifield. These effects were not due to differences in task performance, because accuracy was matched across the tracking conditions by adjusting target speed (with control conditions ruling out effects due to speed alone). To investigate later processing stages, we examined the P3 component over central-parietal scalp sites that was elicited by the test probe at the end of the trial. The P3 amplitude was larger for probes on targets than on distractors, regardless of whether attention was divided across or within a hemifield, indicating that these higher-level processes were not constrained by visual hemifield. These results suggest that modulating early processing stages enables more efficient target tracking, and that within-hemifield competition limits the ability to modulate multiple target representations within the hemifield maps of the early visual cortex. Copyright © 2014 the authors 0270-6474/14/3311526-08$15.00/0.

Neural mechanisms tracking popularity in real-world social networks

PubMed Central

Zerubavel, Noam; Bearman, Peter S.; Weber, Jochen; Ochsner, Kevin N.

2015-01-01

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others’ popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets’ sociometric popularity, even when controlling for potential confounds. The target popularity–social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity–valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members’ popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior. PMID:26598684

Tracking target objects orbiting earth using satellite-based telescopes

DOEpatents

De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

2014-10-14

A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

Fuzzy System-Based Target Selection for a NIR Camera-Based Gaze Tracker

PubMed Central

Naqvi, Rizwan Ali; Arsalan, Muhammad; Park, Kang Ryoung

2017-01-01

Gaze-based interaction (GBI) techniques have been a popular subject of research in the last few decades. Among other applications, GBI can be used by persons with disabilities to perform everyday tasks, as a game interface, and can play a pivotal role in the human computer interface (HCI) field. While gaze tracking systems have shown high accuracy in GBI, detecting a user’s gaze for target selection is a challenging problem that needs to be considered while using a gaze detection system. Past research has used the blinking of the eyes for this purpose as well as dwell time-based methods, but these techniques are either inconvenient for the user or requires a long time for target selection. Therefore, in this paper, we propose a method for fuzzy system-based target selection for near-infrared (NIR) camera-based gaze trackers. The results of experiments performed in addition to tests of the usability and on-screen keyboard use of the proposed method show that it is better than previous methods. PMID:28420114

A Novel Azimuth Super-Resolution Method by Synthesizing Azimuth Bandwidth of Multiple Tracks of Airborne Stripmap SAR Data

PubMed Central

Wang, Yan; Li, Jingwen; Sun, Bing; Yang, Jian

2016-01-01

Azimuth resolution of airborne stripmap synthetic aperture radar (SAR) is restricted by the azimuth antenna size. Conventionally, a higher azimuth resolution should be achieved by employing alternate modes that steer the beam in azimuth to enlarge the synthetic antenna aperture. However, if a data set of a certain region, consisting of multiple tracks of airborne stripmap SAR data, is available, the azimuth resolution of specific small region of interest (ROI) can be conveniently improved by a novel azimuth super-resolution method as introduced by this paper. The proposed azimuth super-resolution method synthesize the azimuth bandwidth of the data selected from multiple discontinuous tracks and contributes to a magnifier-like function with which the ROI can be further zoomed in with a higher azimuth resolution than that of the original stripmap images. Detailed derivation of the azimuth super-resolution method, including the steps of two-dimensional dechirping, residual video phase (RVP) removal, data stitching and data correction, is provided. The restrictions of the proposed method are also discussed. Lastly, the presented approach is evaluated via both the single- and multi-target computer simulations. PMID:27304959

Poster - Thurs Eve-12: A needle-positioning robot co-registered with volumetric x-ray micro-computed tomography images for minimally-invasive small-animal interventions.

PubMed

Waspe, A C; Holdsworth, D W; Lacefield, J C; Fenster, A

2008-07-01

Preclinical research protocols often require the delivery of biological substances to specific targets in small animal disease models. To target biologically relevant locations in mice accurately, the needle positioning error needs to be < 200 μm. If targeting is inaccurate, experimental results can be inconclusive or misleading. We have developed a robotic manipulator that is capable of positioning a needle with a mean error < 100 μm. An apparatus and method were developed for integrating the needle-positioning robot with volumetric micro-computed tomography image guidance for interventions in small animals. Accurate image-to-robot registration is critical for integration as it enables targets identified in the image to be mapped to physical coordinates inside the animal. Registration is accomplished by injecting barium sulphate into needle tracks as the robot withdraws the needle from target points in a tissue-mimicking phantom. Registration accuracy is therefore affected by the positioning error of the robot and is assessed by measuring the point-to-line fiducial and target registration errors (FRE, TRE). Centroid points along cross-sectional slices of the track are determined using region growing segmentation followed by application of a center-of-mass algorithm. The centerline points are registered to needle trajectories in robot coordinates by applying an iterative closest point algorithm between points and lines. Implementing this procedure with four fiducial needle tracks produced a point-to-line FRE and TRE of 246 ± 58 μm and 194 ± 18 μm, respectively. The proposed registration technique produced a TRE < 200 μm, in the presence of robot positioning error, meeting design specification. © 2008 American Association of Physicists in Medicine.