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.

Virtual target tracking (VTT) as applied to mobile satellite communication networks

NASA Astrophysics Data System (ADS)

Amoozegar, Farid

1999-08-01

Traditionally, target tracking has been used for aerospace applications, such as, tracking highly maneuvering targets in a cluttered environment for missile-to-target intercept scenarios. Although the speed and maneuvering capability of current aerospace targets demand more efficient algorithms, many complex techniques have already been proposed in the literature, which primarily cover the defense applications of tracking methods. On the other hand, the rapid growth of Global Communication Systems, Global Information Systems (GIS), and Global Positioning Systems (GPS) is creating new and more diverse challenges for multi-target tracking applications. Mobile communication and computing can very well appreciate a huge market for Cellular Communication and Tracking Devices (CCTD), which will be tracking networked devices at the cellular level. The objective of this paper is to introduce a new concept, i.e., Virtual Target Tracking (VTT) for commercial applications of multi-target tracking algorithms and techniques as applied to mobile satellite communication networks. It would be discussed how Virtual Target Tracking would bring more diversity to target tracking research.

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

PubMed

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

2018-05-08

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

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

-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.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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.

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

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

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

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

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.

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 new method for tracking organ motion on diagnostic ultrasound images

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

Kubota, Yoshiki, E-mail: y-kubota@gunma-u.ac.jp; Matsumura, Akihiko, E-mail: matchan.akihiko@gunma-u.ac.jp; Fukahori, Mai, E-mail: fukahori@nirs.go.jp

2014-09-15

Purpose: Respiratory-gated irradiation is effective in reducing the margins of a target in the case of abdominal organs, such as the liver, that change their position as a result of respiratory motion. However, existing technologies are incapable of directly measuring organ motion in real-time during radiation beam delivery. Hence, the authors proposed a novel quantitative organ motion tracking method involving the use of diagnostic ultrasound images; it is noninvasive and does not entail radiation exposure. In the present study, the authors have prospectively evaluated this proposed method. Methods: The method involved real-time processing of clinical ultrasound imaging data rather thanmore » organ monitoring; it comprised a three-dimensional ultrasound device, a respiratory sensing system, and two PCs for data storage and analysis. The study was designed to evaluate the effectiveness of the proposed method by tracking the gallbladder in one subject and a liver vein in another subject. To track a moving target organ, the method involved the control of a region of interest (ROI) that delineated the target. A tracking algorithm was used to control the ROI, and a large number of feature points and an error correction algorithm were used to achieve long-term tracking of the target. Tracking accuracy was assessed in terms of how well the ROI matched the center of the target. Results: The effectiveness of using a large number of feature points and the error correction algorithm in the proposed method was verified by comparing it with two simple tracking methods. The ROI could capture the center of the target for about 5 min in a cross-sectional image with changing position. Indeed, using the proposed method, it was possible to accurately track a target with a center deviation of 1.54 ± 0.9 mm. The computing time for one frame image using our proposed method was 8 ms. It is expected that it would be possible to track any soft-tissue organ or tumor with large

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.

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

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

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

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

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

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

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.

Location detection and tracking of moving targets by a 2D IR-UWB radar system.

PubMed

Nguyen, Van-Han; Pyun, Jae-Young

2015-03-19

In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

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.

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 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

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

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 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.

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.

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

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.

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.

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

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�

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�

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.

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 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.

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.

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.

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.

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

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.

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

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

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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).

Unification of automatic target tracking and automatic target recognition

NASA Astrophysics Data System (ADS)

Schachter, Bruce J.

2014-06-01

The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

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.

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.

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.

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.

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%.

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

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.

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

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

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.

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

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

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.

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

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

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

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.

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.

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.

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.

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.

Real Time Target Tracking Using Dedicated Vision Hardware

NASA Astrophysics Data System (ADS)

Kambies, Keith; Walsh, Peter

1988-03-01

This paper describes a real-time vision target tracking system developed by Adaptive Automation, Inc. and delivered to NASA's Launch Equipment Test Facility, Kennedy Space Center, Florida. The target tracking system is part of the Robotic Application Development Laboratory (RADL) which was designed to provide NASA with a general purpose robotic research and development test bed for the integration of robot and sensor systems. One of the first RADL system applications is the closing of a position control loop around a six-axis articulated arm industrial robot using a camera and dedicated vision processor as the input sensor so that the robot can locate and track a moving target. The vision system is inside of the loop closure of the robot tracking system, therefore, tight throughput and latency constraints are imposed on the vision system that can only be met with specialized hardware and a concurrent approach to the processing algorithms. State of the art VME based vision boards capable of processing the image at frame rates were used with a real-time, multi-tasking operating system to achieve the performance required. This paper describes the high speed vision based tracking task, the system throughput requirements, the use of dedicated vision hardware architecture, and the implementation design details. Important to the overall philosophy of the complete system was the hierarchical and modular approach applied to all aspects of the system, hardware and software alike, so there is special emphasis placed on this topic in the paper.

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

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.

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.

Interactive target tracking for persistent wide-area surveillance

NASA Astrophysics Data System (ADS)

Ersoy, Ilker; Palaniappan, Kannappan; Seetharaman, Guna S.; Rao, Raghuveer M.

2012-06-01

Persistent aerial surveillance is an emerging technology that can provide continuous, wide-area coverage from an aircraft-based multiple-camera system. Tracking targets in these data sets is challenging for vision algorithms due to large data (several terabytes), very low frame rate, changing viewpoint, strong parallax and other imperfections due to registration and projection. Providing an interactive system for automated target tracking also has additional challenges that require online algorithms that are seamlessly integrated with interactive visualization tools to assist the user. We developed an algorithm that overcomes these challenges and demonstrated it on data obtained from a wide-area imaging platform.

GTARG - THE TOPEX/POSEIDON GROUND TRACK MAINTENANCE MANEUVER TARGETING PROGRAM

NASA Technical Reports Server (NTRS)

Shapiro, B. E.

1994-01-01

GTARG, The TOPEX/POSEIDON Ground Track Maintenance Maneuver Targeting Program, was developed to assist in the designing of orbit maintenance maneuvers for the TOPEX/POSEIDON satellite. These maneuvers ensure that the ground track is kept within 1 km of an approximately 9.9 day exact repeat pattern. Targeting strategies used by GTARG will either maximize the time between maneuvers (longitude targeting) or force control band exit to occur at specified intervals (time targeting). A runout mode allows for ground track propagation without targeting. The analytic mean-element propagation algorithm used in GTARG includes all perturbations that are known to cause significant variations in the satellite ground track. These include earth oblateness, luni-solar gravity, and drag, as well as the thrust due to impulsive maneuvers and unspecified along-track satellite fixed forces. Merson's extension of Grove's theory is used for the computation of the geopotential field. Kaula's disturbing function is used to attain the luni-solar gravitational perturbations. GTARG includes a satellite unique drag model which incorporates an approximate mean orbital Jacchia-Roberts atmosphere and a variable mean area model. Error models include uncertainties due to orbit determination, maneuver execution, drag unpredictability, as well as utilization of the knowledge of along-track satellite fixed forces. 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. GTARG is written in VAX-FORTRAN for DEC VAX Series computers running VMS. GTARG output is provided in two forms: an executive report summary which is in tabular form, and a plot file which is formatted as EZPLOT input namelists. Although the EZPLOT program and documentation are included with GTARG, EZPLOT requires PGPLOT, which was written by the California Institute of Technology Astronomy Department. (For non

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.

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

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.

Alternatives to an extended Kalman Filter for target image tracking

NASA Astrophysics Data System (ADS)

Leuthauser, P. R.

1981-12-01

Four alternative filters are compared to an extended Kalman filter (EKF) algorithm for tracking a distributed (elliptical) source target in a closed loop tracking problem, using outputs from a forward looking (FLIR) sensor as measurements. These were (1) an EKF with (second order) bias correction term, (2) a constant gain EKF, (3) a constant gain EKF with bias correction term, and (4) a statistically linearized filter. Estimates are made of both actual target motion and of apparent motion due to atmospheric jitter. These alternative designs are considered specifically to address some of the significant biases exhibited by an EKF due to initial acquisition difficulties, unmodelled maneuvering by the target, low signal-to-noise ratio, and real world conditions varying significantly from those assumed in the filter design (robustness). Filter performance was determined with a Monte Carlo study under both ideal and non ideal conditions for tracking targets on a constant velocity cross range path, and during constant acceleration turns of 5G, 10G, and 20G.

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.

Orbital Evasive Target Tracking and Sensor Management

DTIC Science & Technology

2012-03-30

maximize the total information gain in the observer-to-target assignment. We compare the information based approach to the game theoretic criterion where...tracking with multiple space borne observers. The results indicate that the game theoretic approach is more effective than the information based approach in...sensor management is to maximize the total information gain in the observer-to-target assignment. We compare the information based approach to the game

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

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

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.

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

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.

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.

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.

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.

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.

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

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

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.

Integrated long-range UAV/UGV collaborative target tracking

NASA Astrophysics Data System (ADS)

Moseley, Mark B.; Grocholsky, Benjamin P.; Cheung, Carol; Singh, Sanjiv

2009-05-01

Coordinated operations between unmanned air and ground assets allow leveraging of multi-domain sensing and increase opportunities for improving line of sight communications. While numerous military missions would benefit from coordinated UAV-UGV operations, foundational capabilities that integrate stove-piped tactical systems and share available sensor data are required and not yet available. iRobot, AeroVironment, and Carnegie Mellon University are working together, partially SBIR-funded through ARDEC's small unit network lethality initiative, to develop collaborative capabilities for surveillance, targeting, and improved communications based on PackBot UGV and Raven UAV platforms. We integrate newly available technologies into computational, vision, and communications payloads and develop sensing algorithms to support vision-based target tracking. We first simulated and then applied onto real tactical platforms an implementation of Decentralized Data Fusion, a novel technique for fusing track estimates from PackBot and Raven platforms for a moving target in an open environment. In addition, system integration with AeroVironment's Digital Data Link onto both air and ground platforms has extended our capabilities in communications range to operate the PackBot as well as in increased video and data throughput. The system is brought together through a unified Operator Control Unit (OCU) for the PackBot and Raven that provides simultaneous waypoint navigation and traditional teleoperation. We also present several recent capability accomplishments toward PackBot-Raven coordinated operations, including single OCU display design and operation, early target track results, and Digital Data Link integration efforts, as well as our near-term capability goals.

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

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

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

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.

Comparison of several maneuvering target tracking models

NASA Astrophysics Data System (ADS)

McIntyre, Gregory A.; Hintz, Kenneth J.

1998-07-01

The tracking of maneuvering targets is complicated by the fact that acceleration is not directly observable or measurable. Additionally, acceleration can be induced by a variety of sources including human input, autonomous guidance, or atmospheric disturbances. The approaches to tracking maneuvering targets can be divided into two categories both of which assume that the maneuver input command is unknown. One approach is to model the maneuver as a random process. The other approach assumes that the maneuver is not random and that it is either detected or estimated in real time. The random process models generally assume one of two statistical properties, either white noise or an autocorrelated noise. The multiple-model approach is generally used with the white noise model while a zero-mean, exponentially correlated acceleration approach is used with the autocorrelated noise model. The nonrandom approach uses maneuver detection to correct the state estimate or a variable dimension filter to augment the state estimate with an extra state component during a detected maneuver. Another issue with the tracking of maneuvering target is whether to perform the Kalman filter in Polar or Cartesian coordinates. This paper will examine and compare several exponentially correlated acceleration approaches in both Polar and Cartesian coordinates for accuracy and computational complexity. They include the Singer model in both Polar and Cartesian coordinates, the Singer model in Polar coordinates converted to Cartesian coordinates, Helferty's third order rational approximation of the Singer model and the Bar-Shalom and Fortmann model. This paper shows that these models all provide very accurate position estimates with only minor differences in velocity estimates and compares the computational complexity of the models.

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.

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.

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.

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

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

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.

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.

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.

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.

Polar versus Cartesian velocity models for maneuvering target tracking with IMM

NASA Astrophysics Data System (ADS)

Laneuville, Dann

This paper compares various model sets in different IMM filters for the maneuvering target tracking problem. The aim is to see whether we can improve the tracking performance of what is certainly the most widely used model set in the literature for the maneuvering target tracking problem: a Nearly Constant Velocity model and a Nearly Coordinated Turn model. Our new challenger set consists of a mixed Cartesian position and polar velocity state vector to describe the uniform motion segments and is augmented with the turn rate to obtain the second model for the maneuvering segments. This paper also gives a general procedure to discretize up to second order any non-linear continuous time model with linear diffusion. Comparative simulations on an air defence scenario with a 2D radar, show that this new approach improves significantly the tracking performance in this case.

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.

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.

Game theoretic sensor management for target tracking

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh; Douville, Philip; Yang, Chun; Kadar, Ivan

2010-04-01

This paper develops and evaluates a game-theoretic approach to distributed sensor-network management for target tracking via sensor-based negotiation. We present a distributed sensor-based negotiation game model for sensor management for multi-sensor multi-target tacking situations. In our negotiation framework, each negotiation agent represents a sensor and each sensor maximizes their utility using a game approach. The greediness of each sensor is limited by the fact that the sensor-to-target assignment efficiency will decrease if too many sensor resources are assigned to a same target. It is similar to the market concept in real world, such as agreements between buyers and sellers in an auction market. Sensors are willing to switch targets so that they can obtain their highest utility and the most efficient way of applying their resources. Our sub-game perfect equilibrium-based negotiation strategies dynamically and distributedly assign sensors to targets. Numerical simulations are performed to demonstrate our sensor-based negotiation approach for distributed sensor management.

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.

Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

PubMed Central

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-01-01

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer–Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying. PMID:25393784

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

Accurate State Estimation and Tracking of a Non-Cooperative Target Vehicle

NASA Technical Reports Server (NTRS)

Thienel, Julie K.; Sanner, Robert M.

2006-01-01

Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.

Homography-based multiple-camera person-tracking

NASA Astrophysics Data System (ADS)

Turk, Matthew R.

2009-01-01

Multiple video cameras are cheaply installed overlooking an area of interest. While computerized single-camera tracking is well-developed, multiple-camera tracking is a relatively new problem. The main multi-camera problem is to give the same tracking label to all projections of a real-world target. This is called the consistent labelling problem. Khan and Shah (2003) introduced a method to use field of view lines to perform multiple-camera tracking. The method creates inter-camera meta-target associations when objects enter at the scene edges. They also said that a plane-induced homography could be used for tracking, but this method was not well described. Their homography-based system would not work if targets use only one side of a camera to enter the scene. This paper overcomes this limitation and fully describes a practical homography-based tracker. A new method to find the feet feature is introduced. The method works especially well if the camera is tilted, when using the bottom centre of the target's bounding-box would produce inaccurate results. The new method is more accurate than the bounding-box method even when the camera is not tilted. Next, a method is presented that uses a series of corresponding point pairs "dropped" by oblivious, live human targets to find a plane-induced homography. The point pairs are created by tracking the feet locations of moving targets that were associated using the field of view line method. Finally, a homography-based multiple-camera tracking algorithm is introduced. Rules governing when to create the homography are specified. The algorithm ensures that homography-based tracking only starts after a non-degenerate homography is found. The method works when not all four field of view lines are discoverable; only one line needs to be found to use the algorithm. To initialize the system, the operator must specify pairs of overlapping cameras. Aside from that, the algorithm is fully automatic and uses the natural movement of

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.

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

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Wang, Bingjian; Song, Shangzhen; Zhao, Dong

2017-11-01

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.

Tracking moving radar targets with parallel, velocity-tuned filters

DOEpatents

Bickel, Douglas L.; Harmony, David W.; Bielek, Timothy P.; Hollowell, Jeff A.; Murray, Margaret S.; Martinez, Ana

2013-04-30

Radar data associated with radar illumination of a movable target is processed to monitor motion of the target. A plurality of filter operations are performed in parallel on the radar data so that each filter operation produces target image information. The filter operations are defined to have respectively corresponding velocity ranges that differ from one another. The target image information produced by one of the filter operations represents the target more accurately than the target image information produced by the remainder of the filter operations when a current velocity of the target is within the velocity range associated with the one filter operation. In response to the current velocity of the target being within the velocity range associated with the one filter operation, motion of the target is tracked based on the target image information produced by the one filter operation.

Theatre Ballistic Missile Defense-Multisensor Fusion, Targeting and Tracking Techniques

DTIC Science & Technology

1998-03-01

Washington, D.C., 1994. 8. Brown , R., and Hwang , P., Introduction to Random Signals and Applied Kaiman Filtering, Third Edition, John Wiley and Sons...C. ADDING MEASUREMENT NOISE 15 III. EXTENDED KALMAN FILTER 19 A. DISCRETE TIME KALMAN FILTER 19 B. EXTENDED KALMAN FILTER 21 C. EKF IN TARGET...tracking algorithms. 17 18 in. EXTENDED KALMAN FILTER This chapter provides background information on the development of a tracking algorithm

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

Optimized swimmer tracking system based on a novel multi-related-targets approach

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2017-02-01

Robust tracking is a crucial step in automatic swimmer evaluation from video sequences. We designed a robust swimmer tracking system using a new multi-related-targets approach. The main idea is to consider the swimmer as a bloc of connected subtargets that advance at the same speed. If one of the subtargets is partially or totally occluded, it can be localized by knowing the position of the others. In this paper, we first introduce the two-dimensional direct linear transformation technique that we used to calibrate the videos. Then, we present the classical tracking approach based on dynamic fusion. Next, we highlight the main contribution of our work, which is the multi-related-targets tracking approach. This approach, the classical head-only approach and the ground truth are then compared, through testing on a database of high-level swimmers in training, national and international competitions (French National Championships, Limoges 2015, and World Championships, Kazan 2015). Tracking percentage and the accuracy of the instantaneous speed are evaluated and the findings show that our new appraoach is significantly more accurate than the classical approach.

Real-time WAMI streaming target tracking in fog

NASA Astrophysics Data System (ADS)

Chen, Yu; Blasch, Erik; Chen, Ning; Deng, Anna; Ling, Haibin; Chen, Genshe

2016-05-01

Real-time information fusion based on WAMI (Wide-Area Motion Imagery), FMV (Full Motion Video), and Text data is highly desired for many mission critical emergency or security applications. Cloud Computing has been considered promising to achieve big data integration from multi-modal sources. In many mission critical tasks, however, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform, actually there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion, and decision making are required to be executed on-site (i.e., near the data collection). Fog Computing, a recently proposed extension and complement for Cloud Computing, enables computing on-site without outsourcing jobs to a remote Cloud. In this work, we have investigated the feasibility of processing streaming WAMI in the Fog for real-time, online, uninterrupted target tracking. Using a single target tracking algorithm, we studied the performance of a Fog Computing prototype. The experimental results are very encouraging that validated the effectiveness of our Fog approach to achieve real-time frame rates.

Dazzle camouflage, target tracking, and the confusion effect.

PubMed

Hogan, Benedict G; Cuthill, Innes C; Scott-Samuel, Nicholas E

2016-01-01

The influence of coloration on the ecology and evolution of moving animals in groups is poorly understood. Animals in groups benefit from the "confusion effect," where predator attack success is reduced with increasing group size or density. This is thought to be due to a sensory bottleneck: an increase in the difficulty of tracking one object among many. Motion dazzle camouflage has been hypothesized to disrupt accurate perception of the trajectory or speed of an object or animal. The current study investigates the suggestion that dazzle camouflage may enhance the confusion effect. Utilizing a computer game style experiment with human predators, we found that when moving in groups, targets with stripes parallel to the targets' direction of motion interact with the confusion effect to a greater degree, and are harder to track, than those with more conventional background matching patterns. The findings represent empirical evidence that some high-contrast patterns may benefit animals in groups. The results also highlight the possibility that orientation and turning may be more relevant in the mechanisms of dazzle camouflage than previously recognized.

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.

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.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2003-12-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs

NASA Astrophysics Data System (ADS)

Adil Mahdi, Omar; Wahab, Ainuddin Wahid Abdul; Idris, Mohd Yamani Idna; Znaid, Ammar Abu; Khan, Suleman; Al-Mayouf, Yusor Rafid Bahar

2016-10-01

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.

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.

Nonlinear dynamics support a linear population code in a retinal target-tracking circuit.

PubMed

Leonardo, Anthony; Meister, Markus

2013-10-23

A basic task faced by the visual system of many organisms is to accurately track the position of moving prey. The retina is the first stage in the processing of such stimuli; the nature of the transformation here, from photons to spike trains, constrains not only the ultimate fidelity of the tracking signal but also the ease with which it can be extracted by other brain regions. Here we demonstrate that a population of fast-OFF ganglion cells in the salamander retina, whose dynamics are governed by a nonlinear circuit, serve to compute the future position of the target over hundreds of milliseconds. The extrapolated position of the target is not found by stimulus reconstruction but is instead computed by a weighted sum of ganglion cell outputs, the population vector average (PVA). The magnitude of PVA extrapolation varies systematically with target size, speed, and acceleration, such that large targets are tracked most accurately at high speeds, and small targets at low speeds, just as is seen in the motion of real prey. Tracking precision reaches the resolution of single photoreceptors, and the PVA algorithm performs more robustly than several alternative algorithms. If the salamander brain uses the fast-OFF cell circuit for target extrapolation as we suggest, the circuit dynamics should leave a microstructure on the behavior that may be measured in future experiments. Our analysis highlights the utility of simple computations that, while not globally optimal, are efficiently implemented and have close to optimal performance over a limited but ethologically relevant range of stimuli.

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.

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.

Impedance modulation and feedback corrections in tracking targets of variable size and frequency.

PubMed

Selen, Luc P J; van Dieën, Jaap H; Beek, Peter J

2006-11-01

Humans are able to adjust the accuracy of their movements to the demands posed by the task at hand. The variability in task execution caused by the inherent noisiness of the neuromuscular system can be tuned to task demands by both feedforward (e.g., impedance modulation) and feedback mechanisms. In this experiment, we studied both mechanisms, using mechanical perturbations to estimate stiffness and damping as indices of impedance modulation and submovement scaling as an index of feedback driven corrections. Eight subjects tracked three differently sized targets (0.0135, 0.0270, and 0.0405 rad) moving at three different frequencies (0.20, 0.25, and 0.33 Hz). Movement variability decreased with both decreasing target size and movement frequency, whereas stiffness and damping increased with decreasing target size, independent of movement frequency. These results are consistent with the theory that mechanical impedance acts as a filter of noisy neuromuscular signals but challenge stochastic theories of motor control that do not account for impedance modulation and only partially for feedback control. Submovements during unperturbed cycles were quantified in terms of their gain, i.e., the slope between their duration and amplitude in the speed profile. Submovement gain decreased with decreasing movement frequency and increasing target size. The results were interpreted to imply that submovement gain is related to observed tracking errors and that those tracking errors are expressed in units of target size. We conclude that impedance and submovement gain modulation contribute additively to tracking accuracy.

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%.

Real-time visual target tracking: two implementations of velocity-based smooth pursuit

NASA Astrophysics Data System (ADS)

Etienne-Cummings, Ralph; Longo, Paul; Van der Spiegel, Jan; Mueller, Paul

1995-06-01

Two systems for velocity-based visual target tracking are presented. The first two computational layers of both implementations are composed of VLSI photoreceptors (logarithmic compression) and edge detection (difference-of-Gaussians) arrays that mimic the outer-plexiform layer of mammalian retinas. The subsequent processing layers for measuring the target velocity and to realize smooth pursuit tracking are implemented in software and at the focal plane in the two versions, respectively. One implentation uses a hybrid of a PC and a silicon retina (39 X 38 pixels) operating at 333 frames/second. The software implementation of a real-time optical flow measurement algorithm is used to determine the target velocity, and a closed-loop control system zeroes the relative velocity of the target and retina. The second implementation is a single VLSI chip, which contains a linear array of photoreceptors, edge detectors and motion detectors at the focal plane. The closed-loop control system is also included on chip. This chip realizes all the computational properties of the hybrid system. The effects of background motion, target occlusion, and disappearance are studied as a function of retinal size and spatial distribution of the measured motion vectors (i.e. foveal/peripheral and diverging/converging measurement schemes). The hybrid system, which tested successfully, tracks targets moving as fast as 3 m/s at 1.3 meters from the camera and it can compensate for external arbitrary movements in its mounting platform. The single chip version, whose circuits tested successfully, can handle targets moving at 10 m/s.

SME filter approach to multiple target tracking with false and missing measurements

NASA Astrophysics Data System (ADS)

Lee, Yong J.; Kamen, Edward W.

1993-10-01

The symmetric measurement equation (SME) filter for track maintenance in multiple target tracking is extended to the general case when there are an arbitrary unknown number of false and missing position measurements in the measurement set at any time point. It is assumed that the number N of targets is known a priori and that the target motions consist of random perturbations of constant-velocity trajectories. The key idea in the paper is to generate a new measurement vector from sums-of-products of the elements of 'feasible' N-element data vectors that pass a thresholding operation in the sums-of-products framework. Via this construction, the data association problem is completely avoided, and in addition, there is no need to identify which target measurements may correspond to false returns or which target measurements may be missing. A computer simulation of SME filter performance is given, including a comparison with the associated filter (a benchmark) and the joint probabilistic data association (JPDA) filter.

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.

Clinical implementation of target tracking by breathing synchronized delivery

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

Tewatia, Dinesh; Zhang Tiezhi; Tome, Wolfgang

2006-11-15

Target-tracking techniques can be categorized based on the mechanism of the feedback loop. In real time tracking, breathing-delivery phase correlation is provided to the treatment delivery hardware. Clinical implementation of target tracking in real time requires major hardware modifications. In breathing synchronized delivery (BSD), the patient is guided to breathe in accordance with target motion derived from four-dimensional computed tomography (4D-CT). Violations of mechanical limitations of hardware are to be avoided at the treatment planning stage. Hardware modifications are not required. In this article, using sliding window IMRT delivery as an example, we have described step-by-step the implementation of targetmore » tracking by the BSD technique: (1) A breathing guide is developed from patient's normal breathing pattern. The patient tries to reproduce this guiding cycle by following the display in the goggles; (2) 4D-CT scans are acquired at all the phases of the breathing cycle; (3) The average tumor trajectory is obtained by deformable image registration of 4D-CT datasets and is smoothed by Fourier filtering; (4) Conventional IMRT planning is performed using the images at reference phase (full exhalation phase) and a leaf sequence based on optimized fluence map is generated; (5) Assuming the patient breathes with a reproducible breathing pattern and the machine maintains a constant dose rate, the treatment process is correlated with the breathing phase; (6) The instantaneous average tumor displacement is overlaid on the dMLC position at corresponding phase; and (7) DMLC leaf speed and acceleration are evaluated to ensure treatment delivery. A custom-built mobile phantom driven by a computer-controlled stepper motor was used in the dosimetry verification. A stepper motor was programmed such that the phantom moved according to the linear component of tumor motion used in BSD treatment planning. A conventional plan was delivered on the phantom with and

Signal Processing for Radar Target Tracking and Identification

DTIC Science & Technology

1996-12-01

Computes the likelihood for various potential jump moves. 12. matrix_mult.m: Parallel implementation of linear algebra ... Elementary Lineary Algebra with Applications, John Wiley k Sons, Inc., New York, 1987. [9] A. K. Bhattacharyya, and D. L. Sengupta, Radar Cross...Miller, ’Target Tracking and Recognition Using Jump-Diffusion Processes," ARO’s 11th Army Conf. on Applied Mathemat- ics and Computing, June 8-11

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

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

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.

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.

Mid-course multi-target tracking using continuous representation

NASA Technical Reports Server (NTRS)

Zak, Michail; Toomarian, Nikzad

1991-01-01

The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.

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.

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

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

Exogenous Social Identity Cues Differentially Affect the Dynamic Tracking of Individual Target Faces

ERIC Educational Resources Information Center

Allen, Roy; Gabbert, Fiona

2013-01-01

We report on an experiment to investigate the top-down effect of exogenous social identity cues on a multiple-identity tracking task, a paradigm well suited to investigate the processes of binding identity to spatial locations. Here we simulated an eyewitness event in which dynamic targets, all to be tracked with equal effort, were identified from…

Precision targeting with a tracking adaptive optics scanning laser ophthalmoscope

NASA Astrophysics Data System (ADS)

Hammer, Daniel X.; Ferguson, R. Daniel; Bigelow, Chad E.; Iftimia, Nicusor V.; Ustun, Teoman E.; Noojin, Gary D.; Stolarski, David J.; Hodnett, Harvey M.; Imholte, Michelle L.; Kumru, Semih S.; McCall, Michelle N.; Toth, Cynthia A.; Rockwell, Benjamin A.

2006-02-01

Precise targeting of retinal structures including retinal pigment epithelial cells, feeder vessels, ganglion cells, photoreceptors, and other cells important for light transduction may enable earlier disease intervention with laser therapies and advanced methods for vision studies. A novel imaging system based upon scanning laser ophthalmoscopy (SLO) with adaptive optics (AO) and active image stabilization was designed, developed, and tested in humans and animals. An additional port allows delivery of aberration-corrected therapeutic/stimulus laser sources. The system design includes simultaneous presentation of non-AO, wide-field (~40 deg) and AO, high-magnification (1-2 deg) retinal scans easily positioned anywhere on the retina in a drag-and-drop manner. The AO optical design achieves an error of <0.45 waves (at 800 nm) over +/-6 deg on the retina. A MEMS-based deformable mirror (Boston Micromachines Inc.) is used for wave-front correction. The third generation retinal tracking system achieves a bandwidth of greater than 1 kHz allowing acquisition of stabilized AO images with an accuracy of ~10 μm. Normal adult human volunteers and animals with previously-placed lesions (cynomolgus monkeys) were tested to optimize the tracking instrumentation and to characterize AO imaging performance. Ultrafast laser pulses were delivered to monkeys to characterize the ability to precisely place lesions and stimulus beams. Other advanced features such as real-time image averaging, automatic highresolution mosaic generation, and automatic blink detection and tracking re-lock were also tested. The system has the potential to become an important tool to clinicians and researchers for early detection and treatment of retinal diseases.

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.

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.

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.

EEG and Eye Tracking Signatures of Target Encoding during Structured Visual Search

PubMed Central

Brouwer, Anne-Marie; Hogervorst, Maarten A.; Oudejans, Bob; Ries, Anthony J.; Touryan, Jonathan

2017-01-01

EEG and eye tracking variables are potential sources of information about the underlying processes of target detection and storage during visual search. Fixation duration, pupil size and event related potentials (ERPs) locked to the onset of fixation or saccade (saccade-related potentials, SRPs) have been reported to differ dependent on whether a target or a non-target is currently fixated. Here we focus on the question of whether these variables also differ between targets that are subsequently reported (hits) and targets that are not (misses). Observers were asked to scan 15 locations that were consecutively highlighted for 1 s in pseudo-random order. Highlighted locations displayed either a target or a non-target stimulus with two, three or four targets per trial. After scanning, participants indicated which locations had displayed a target. To induce memory encoding failures, participants concurrently performed an aurally presented math task (high load condition). In a low load condition, participants ignored the math task. As expected, more targets were missed in the high compared with the low load condition. For both conditions, eye tracking features distinguished better between hits and misses than between targets and non-targets (with larger pupil size and shorter fixations for missed compared with correctly encoded targets). In contrast, SRP features distinguished better between targets and non-targets than between hits and misses (with average SRPs showing larger P300 waveforms for targets than for non-targets). Single trial classification results were consistent with these averages. This work suggests complementary contributions of eye and EEG measures in potential applications to support search and detect tasks. SRPs may be useful to monitor what objects are relevant to an observer, and eye variables may indicate whether the observer should be reminded of them later. PMID:28559807

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

Method for targetless tracking subpixel in-plane movements.

PubMed

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

2015-09-01

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

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%.

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.

Tracking and people counting using Particle Filter Method

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

An examination of along-track interferometry for detecting ground moving targets

NASA Technical Reports Server (NTRS)

Chen, Curtis W.; Chapin, Elaine; Muellerschoen, Ron; Hensley, Scott

2005-01-01

Along-track interferometry (ATI) is an interferometric synthetic aperture radar technique primarily used to measure Earth-surface velocities. We present results from an airborne experiment demonstrating phenomenology specific to the context of observing discrete ground targets moving admidst a stationary clutter background.

Prediction of pilot reserve attention capacity during air-to-air target tracking

NASA Technical Reports Server (NTRS)

Onstott, E. D.; Faulkner, W. H.

1977-01-01

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

5. Photocopy of photograph showing target tracking radar from 'Procedures ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. Photocopy of photograph showing target tracking radar from 'Procedures and Drills for the NIKE Hercules Missile Battery,' Department of the Army Field Manual, FM-44-82 from Institute for Military History, Carlisle Barracks, Carlisle, PA, 1959 - NIKE Missile Battery PR-79, East Windsor Road south of State Route 101, Foster, Providence County, RI

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

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.

Improvement in Visual Target Tracking for a Mobile Robot

NASA Technical Reports Server (NTRS)

Kim, Won; Ansar, Adnan; Madison, Richard

2006-01-01

In an improvement of the visual-target-tracking software used aboard a mobile robot (rover) of the type used to explore the Martian surface, an affine-matching algorithm has been replaced by a combination of a normalized- cross-correlation (NCC) algorithm and a template-image-magnification algorithm. Although neither NCC nor template-image magnification is new, the use of both of them to increase the degree of reliability with which features can be matched is new. In operation, a template image of a target is obtained from a previous rover position, then the magnification of the template image is based on the estimated change in the target distance from the previous rover position to the current rover position (see figure). For this purpose, the target distance at the previous rover position is determined by stereoscopy, while the target distance at the current rover position is calculated from an estimate of the current pose of the rover. The template image is then magnified by an amount corresponding to the estimated target distance to obtain a best template image to match with the image acquired at the current rover position.

Retrodiction for Bayesian multiple-hypothesis/multiple-target tracking in densely cluttered environment

NASA Astrophysics Data System (ADS)

Koch, Wolfgang

1996-05-01

Sensor data processing in a dense target/dense clutter environment is inevitably confronted with data association conflicts which correspond with the multiple hypothesis character of many modern approaches (MHT: multiple hypothesis tracking). In this paper we analyze the efficiency of retrodictive techniques that generalize standard fixed interval smoothing to MHT applications. 'Delayed estimation' based on retrodiction provides uniquely interpretable and accurate trajectories from ambiguous MHT output if a certain time delay is tolerated. In a Bayesian framework the theoretical background of retrodiction and its intimate relation to Bayesian MHT is sketched. By a simulated example with two closely-spaced targets, relatively low detection probabilities, and rather high false return densities, we demonstrate the benefits of retrodiction and quantitatively discuss the achievable track accuracies and the time delays involved for typical radar parameters.

Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Rong, Shenghui; Wang, Bingjian; Cheng, Kuanhong

2017-05-01

Infrared small target tracking plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, an effective algorithm based on the Singular Value Decomposition (SVD) and the improved Kernelized Correlation Filter (KCF) is presented for infrared small target tracking. Firstly, the super performance of the SVD-based algorithm is that it takes advantage of the target's global information and obtains a background estimation of an infrared image. A dim target is enhanced by subtracting the corresponding estimated background with update from the original image. Secondly, the KCF algorithm is combined with Gaussian Curvature Filter (GCF) to eliminate the excursion problem. The GCF technology is adopted to preserve the edge and eliminate the noise of the base sample in the KCF algorithm, helping to calculate the classifier parameter for a small target. At last, the target position is estimated with a response map, which is obtained via the kernelized classifier. Experimental results demonstrate that the presented algorithm performs favorably in terms of efficiency and accuracy, compared with several state-of-the-art algorithms.

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

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

Track-Before-Declare Methods in IR Image Sequences

DTIC Science & Technology

1992-09-01

processing methods of this type, known as track- before-declare (TBD), and sometimes by the misleading term track - before - detect , have been employed in systems...Electronic Systems, Vol. AES-il, No. 6. November 1975. 8. A. Corbeil, J. DiDomizio, Track - Before - Detect Development and Demonstration Program, Phase

Supercavitating Projectile Tracking System and Method

DTIC Science & Technology

2009-12-30

Distribution is unlimited 20100104106 Attorney Docket No. 96681 SUPERCAVITATING PROJECTILE TRACKING SYSTEM AND METHOD STATEMENT OF GOVERNMENT...underwater track or path 14 of a supercavitating vehicle under surface 16 of a body of water. In this embodiment, passive acoustic or pressure...transducers 12 are utilized to measure a pressure field produced by a moving supercavitating vehicle. The present invention provides a low-cost, reusable

Speckle tracking as a method to measure hemidiaphragm excursion.

PubMed

Goutman, Stephen A; Hamilton, James D; Swihart, Blake; Foerster, Bradley; Feldman, Eva L; Rubin, Jonathan M

2017-01-01

Diaphragm excursion measured via ultrasound may be an important imaging outcome measure of respiratory function. We developed a new method for measuring diaphragm movement and compared it to the more traditional M-mode method. Ultrasound images of the right and left hemidiaphragms were collected to compare speckle tracking and M-mode measurements of diaphragm excursion. Speckle tracking was performed using EchoInsight (Epsilon Imaging, Ann Arbor, Michigan). Six healthy subjects without a history of pulmonary diseases were included in this proof-of-concept study. Speckle tracking of the diaphragm is technically possible. Unlike M-mode, speckle tracking carries the advantage of reliable visualization and measurement of the left hemidiaphragm. Speckle tracking accounted for diaphragm movement simultaneously in the cephalocaudad and mediolateral directions, unlike M-mode, which is 1-dimensional. Diaphragm speckle tracking may represent a novel, more robust method for measuring diaphragm excursion, especially for the left hemidiaphragm. Muscle Nerve 55: 125-127, 2017. © 2016 Wiley Periodicals, Inc.

Hybrid Orientation Based Human Limbs Motion Tracking Method

PubMed Central

Glonek, Grzegorz; Wojciechowski, Adam

2017-01-01

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

Hyperspectral-Augmented Target Tracking

DTIC Science & Technology

2008-03-01

detectable velocity ( MDV ) of 1.5m/s. After several seconds, the vehicles depart heading in the same di- rection, but this time, the top vehicle speeds up... vehicles begin to speed up ( MDV > 1.5m/s), the tracker once again initiates each track using the class ID of the nearest vehicle , effectively swapping the...Fig. 4.5(b)). After both vehicles speed up to an MDV > 1.5m/s, the tracker initiates each track using the class ID of the nearest vehicle , “re-assigning

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.

Online two-stage association method for robust multiple people tracking

NASA Astrophysics Data System (ADS)

Lv, Jingqin; Fang, Jiangxiong; Yang, Jie

2011-07-01

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

Role of quality of service metrics in visual target acquisition and tracking in resource constrained environments

NASA Astrophysics Data System (ADS)

Anderson, Monica; David, Phillip

2007-04-01

Implementation of an intelligent, automated target acquisition and tracking systems alleviates the need for operators to monitor video continuously. This system could identify situations that fatigued operators could easily miss. If an automated acquisition and tracking system plans motions to maximize a coverage metric, how does the performance of that system change when the user intervenes and manually moves the camera? How can the operator give input to the system about what is important and understand how that relates to the overall task balance between surveillance and coverage? In this paper, we address these issues by introducing a new formulation of the average linear uncovered length (ALUL) metric, specially designed for use in surveilling urban environments. This metric coordinates the often competing goals of acquiring new targets and tracking existing targets. In addition, it provides current system performance feedback to system users in terms of the system's theoretical maximum and minimum performance. We show the successful integration of the algorithm via simulation.

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.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Tracking 20 Years of Compound-to-Target Output from Literature and Patents

PubMed Central

Southan, Christopher; Varkonyi, Peter; Boppana, Kiran; Jagarlapudi, Sarma A.R.P.; Muresan, Sorel

2013-01-01

The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates. PMID

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.

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.

Stimulus selection and tracking during urination: autoshaping directed behavior with toilet targets.

PubMed Central

Siegel, R K

1977-01-01

A simple procedure is described for investigating stimuli selected as targets during urination in the commode. Ten normal males preferred a floating target that could be tracked to a series of stationary targets. This technique was used to bring misdirected urinations in a severely retarded male under rapid stimulus control of a floating target in the commode. The float stimulus was also evaluated with nine institionalized, moderately retarded males and results indicated rapid autoshaping of directed urination without the use of verbal instructions or conventional toilet training. The technique can be applied in training children to control misdirected urinations in institution for the retarded, in psychiatric wards with regressed populations, and in certain male school dormitories. PMID:885828

Stimulus selection and tracking during urination: autoshaping directed behavior with toilet targets.

PubMed

Siegel, R K

1977-01-01

A simple procedure is described for investigating stimuli selected as targets during urination in the commode. Ten normal males preferred a floating target that could be tracked to a series of stationary targets. This technique was used to bring misdirected urinations in a severely retarded male under rapid stimulus control of a floating target in the commode. The float stimulus was also evaluated with nine institionalized, moderately retarded males and results indicated rapid autoshaping of directed urination without the use of verbal instructions or conventional toilet training. The technique can be applied in training children to control misdirected urinations in institution for the retarded, in psychiatric wards with regressed populations, and in certain male school dormitories.

Big brown bats (Eptesicus fuscus) reveal diverse strategies for sonar target tracking in clutter.

PubMed

Mao, Beatrice; Aytekin, Murat; Wilkinson, Gerald S; Moss, Cynthia F

2016-09-01

Bats actively adjust the acoustic features of their sonar calls to control echo information specific to a given task and environment. A previous study investigated how bats adapted their echolocation behavior when tracking a moving target in the presence of a stationary distracter at different distances and angular offsets. The use of only one distracter, however, left open the possibility that a bat could reduce the interference of the distracter by turning its head. Here, bats tracked a moving target in the presence of one or two symmetrically placed distracters to investigate adaptive echolocation behavior in a situation where vocalizing off-axis would result in increased interference from distracter echoes. Both bats reduced bandwidth and duration but increased sweep rate in more challenging distracter conditions, and surprisingly, made more head turns in the two-distracter condition compared to one, but only when distracters were placed at large angular offsets. However, for most variables examined, subjects showed distinct strategies to reduce clutter interference, either by (1) changing spectral or temporal features of their calls, or (2) producing large numbers of sonar sound groups and consistent head-turning behavior. The results suggest that individual bats can use different strategies for target tracking in cluttered environments.

Relative Displacement Method for Track-Structure Interaction

PubMed Central

Ramos, Óscar Ramón; Pantaleón, Marcos J.

2014-01-01

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

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

Inertial fusion energy target injection, tracking, and beam pointing

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

Petzoldt, Ronald Wayne

1995-03-07

Several cryogenic targets must be injected each second into a reaction chamber. Required target speed is about 100 m/s. Required accuracy of the driver beams on target is a few hundred micrometers. Fuel strength is calculated to allow acceleration in excess of 10,000 m/s 2 if the fuel temperature is less than 17 K. A 0.1 μm thick dual membrane will allow nearly 2,000 m/s 2 acceleration. Acceleration is gradually increased and decreased over a few membrane oscillation periods (a few ms), to avoid added stress from vibrations which could otherwise cause a factor of two decrease in allowed acceleration.more » Movable shielding allows multiple targets to be in flight toward the reaction chamber at once while minimizing neutron heating of subsequent targets. The use of multiple injectors is recommended for redundancy which increases availability and allows a higher pulse rate. Gas gun, rail gun, induction accelerator, and electrostatic accelerator target injection devices are studied, and compared. A gas gun is the preferred device for indirect-drive targets due to its simplicity and proven reliability. With the gas gun, the amount of gas required for each target (about 10 to 100 mg) is acceptable. A revolver loading mechanism is recommended with a cam operated poppet valve to control the gas flow. Cutting vents near the muzzle of the gas gun barrel is recommended to improve accuracy and aid gas pumping. If a railgun is used, we recommend an externally applied magnetic field to reduce required current by an order of magnitude. Optical target tracking is recommended. Up/down counters are suggested to predict target arrival time. Target steering is shown to be feasible and would avoid the need to actively point the beams. Calculations show that induced tumble from electrostatically steering the target is not excessive.« less

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

PubMed

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Hough transform method for track finding in center drift chamber

NASA Astrophysics Data System (ADS)

Azmi, K. A. Mohammad Kamal; Wan Abdullah, W. A. T.; Ibrahim, Zainol Abidin

2016-01-01

Hough transform is a global tracking method used which had been expected to be faster approach for tracking the circular pattern of electron moving in Center Drift Chamber (CDC), by transforming the point of hit into a circular curve. This paper present the implementation of hough transform method for the reconstruction of tracks in Center Drift Chamber (CDC) which have been generated by random number in C language programming. Result from implementation of this method shows higher peak of circle parameter value (xc,yc,rc) that indicate the similarity value of the parameter needed for circular track in CDC for charged particles in the region of CDC.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF). PMID:28608843

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

The seam visual tracking method for large structures

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A Method for Finding Metabolic Pathways Using Atomic Group Tracking.

PubMed

Huang, Yiran; Zhong, Cheng; Lin, Hai Xiang; Wang, Jianyi

2017-01-01

A fundamental computational problem in metabolic engineering is to find pathways between compounds. Pathfinding methods using atom tracking have been widely used to find biochemically relevant pathways. However, these methods require the user to define the atoms to be tracked. This may lead to failing to predict the pathways that do not conserve the user-defined atoms. In this work, we propose a pathfinding method called AGPathFinder to find biochemically relevant metabolic pathways between two given compounds. In AGPathFinder, we find alternative pathways by tracking the movement of atomic groups through metabolic networks and use combined information of reaction thermodynamics and compound similarity to guide the search towards more feasible pathways and better performance. The experimental results show that atomic group tracking enables our method to find pathways without the need of defining the atoms to be tracked, avoid hub metabolites, and obtain biochemically meaningful pathways. Our results also demonstrate that atomic group tracking, when incorporated with combined information of reaction thermodynamics and compound similarity, improves the quality of the found pathways. In most cases, the average compound inclusion accuracy and reaction inclusion accuracy for the top resulting pathways of our method are around 0.90 and 0.70, respectively, which are better than those of the existing methods. Additionally, AGPathFinder provides the information of thermodynamic feasibility and compound similarity for the resulting pathways.

A Method for Finding Metabolic Pathways Using Atomic Group Tracking

PubMed Central

Zhong, Cheng; Lin, Hai Xiang; Wang, Jianyi

2017-01-01

A fundamental computational problem in metabolic engineering is to find pathways between compounds. Pathfinding methods using atom tracking have been widely used to find biochemically relevant pathways. However, these methods require the user to define the atoms to be tracked. This may lead to failing to predict the pathways that do not conserve the user-defined atoms. In this work, we propose a pathfinding method called AGPathFinder to find biochemically relevant metabolic pathways between two given compounds. In AGPathFinder, we find alternative pathways by tracking the movement of atomic groups through metabolic networks and use combined information of reaction thermodynamics and compound similarity to guide the search towards more feasible pathways and better performance. The experimental results show that atomic group tracking enables our method to find pathways without the need of defining the atoms to be tracked, avoid hub metabolites, and obtain biochemically meaningful pathways. Our results also demonstrate that atomic group tracking, when incorporated with combined information of reaction thermodynamics and compound similarity, improves the quality of the found pathways. In most cases, the average compound inclusion accuracy and reaction inclusion accuracy for the top resulting pathways of our method are around 0.90 and 0.70, respectively, which are better than those of the existing methods. Additionally, AGPathFinder provides the information of thermodynamic feasibility and compound similarity for the resulting pathways. PMID:28068354

CR-39 track etching and blow-up method

DOEpatents

Hankins, Dale E.

1987-01-01

This invention is a method of etching tracks in CR-39 foil to obtain uniformly sized tracks. The invention comprises a step of electrochemically etching the foil at a low frequency and a "blow-up" step of electrochemically etching the foil at a high frequency.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Hough transform method for track finding in center drift chamber

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

Azmi, K. A. Mohammad Kamal, E-mail: khasmidatul@siswa.um.edu.my; Wan Abdullah, W. A. T., E-mail: wat@um.edu.my; Ibrahim, Zainol Abidin

Hough transform is a global tracking method used which had been expected to be faster approach for tracking the circular pattern of electron moving in Center Drift Chamber (CDC), by transforming the point of hit into a circular curve. This paper present the implementation of hough transform method for the reconstruction of tracks in Center Drift Chamber (CDC) which have been generated by random number in C language programming. Result from implementation of this method shows higher peak of circle parameter value (xc,yc,rc) that indicate the similarity value of the parameter needed for circular track in CDC for charged particlesmore » in the region of CDC.« less

Method for tracking core-contributed publications.

PubMed

Loomis, Cynthia A; Curchoe, Carol Lynn

2012-12-01

Accurately tracking core-contributed publications is an important and often difficult task. Many core laboratories are supported by programmatic grants (such as Cancer Center Support Grant and Clinical Translational Science Awards) or generate data with instruments funded through S10, Major Research Instrumentation, or other granting mechanisms. Core laboratories provide their research communities with state-of-the-art instrumentation and expertise, elevating research. It is crucial to demonstrate the specific projects that have benefited from core services and expertise. We discuss here the method we developed for tracking core contributed publications.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

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

Penalty dynamic programming algorithm for dim targets detection in sensor systems.

PubMed

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

PubMed Central

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

PubMed Central

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

2013-01-01

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

Surface target-tracking guidance by self-organizing formation flight of fixed-wing UAV

NASA Astrophysics Data System (ADS)

Regina, N.; Zanzi, M.

This paper presents a new concept of ground target surveillance based on a formation flight of two Unmanned Aerial Vehicles (UAVs) of fixed-wing type. Each UAV considered in this work has its own guidance law specifically designed for two different aims. A self organizing non-symmetric collaborative surveying scheme has been developed based on pursuers with different roles: the close-up-pursuer and the distance-pursuer. The close-up-pursuer behaves according to a guidance law which takes it to continually over-fly the target, also optimizing flight endurance. On the other hand, the distancepursuer behaves so as to circle around the target by flying at a certain distance and altitude from it; moreover, its motion ensures the maximum “ seeability” of the ground based target. In addition, the guidance law designed for the distance-pursuer also implements a collision avoidance feature in order to prevent possible risks of collision with the close-up-pursuer during the tracking maneuvers. The surveying scheme is non-symmetric in the sense that the collision avoidance feature is accomplished by a guidance law implemented only on one of the two pursuers; moreover, it is collaborative because the surveying is performed by different tasks of two UAVs and is self-organizing because, due to the collision avoidance feature, target tracking does not require pre-planned collision-risk-free trajectories but trajectories are generated in real time.

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.

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.

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

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.

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.

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

NASA Technical Reports Server (NTRS)

Clune, Thomas; Freeman, Shawn; Cruz, Carlos; Burns, Robert; Kuo, Kwo-Sen; Kouatchou, Jules

2013-01-01

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the

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

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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].

Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Daya, Zahir; Kirubarajan, Thiagalingam

2015-05-01

An airborne EO/IR (electro-optical/infrared) camera system comprises of a suite of sensors, such as a narrow and wide field of view (FOV) EO and mid-wave IR sensors. EO/IR camera systems are regularly employed on military and search and rescue aircrafts. The EO/IR system can be used to detect and identify objects rapidly in daylight and at night, often with superior performance in challenging conditions such as fog. There exist several algorithms for detecting potential targets in the bearing elevation grid. The nonlinear filtering problem is one of estimation of the kinematic parameters from bearing and elevation measurements from a moving platform. In this paper, we developed a complete model for the state of a target as detected by an airborne EO/IR system and simulated a typical scenario with single target with 1 or 2 airborne sensors. We have demonstrated the ability to track the target with `high precision' and noted the improvement from using two sensors on a single platform or on separate platforms. The performance of the Extended Kalman filter (EKF) is investigated on simulated data. Image/video data collected from an IR sensor on an airborne platform are processed using an image tracking by detection algorithm.

Latent uncertainties of the precalculated track Monte Carlo method

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

Renaud, Marc-André; Seuntjens, Jan; Roberge, David

Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited numbermore » of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than

Track and vertex reconstruction: From classical to adaptive methods

NASA Astrophysics Data System (ADS)

Strandlie, Are; Frühwirth, Rudolf

2010-04-01

This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.

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...

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

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

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.

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.

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

Latent uncertainties of the precalculated track Monte Carlo method.

PubMed

Renaud, Marc-André; Roberge, David; Seuntjens, Jan

2015-01-01

While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Particle tracks were pregenerated for electrons and protons using EGSnrc and geant4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (cuda) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a "ground truth" benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of Dmax. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the maximum dose. In proton

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.

Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

NASA Astrophysics Data System (ADS)

Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements

Real-time multisensor data fusion for target detection, classification, tracking, counting, and range estimates

NASA Astrophysics Data System (ADS)

Tsui, Eddy K.; Thomas, Russell L.

2004-09-01

As part of the Commanding General of Army Material Command's Research, Development & Engineering Command (RDECOM), the U.S. Army Research Development and Engineering Center (ARDEC), Picatinny funded a joint development effort with McQ Associates, Inc. to develop an Advanced Minefield Sensor (AMS) as a technology evaluation prototype for the Anti-Personnel Landmine Alternatives (APLA) Track III program. This effort laid the fundamental groundwork of smart sensors for detection and classification of targets, identification of combatant or noncombatant, target location and tracking at and between sensors, fusion of information across targets and sensors, and automatic situation awareness to the 1st responder. The efforts have culminated in developing a performance oriented architecture meeting the requirements of size, weight, and power (SWAP). The integrated digital signal processor (DSP) paradigm is capable of computing signals from sensor modalities to extract needed information within either a 360° or fixed field of view with acceptable false alarm rate. This paper discusses the challenges in the developments of such a sensor, focusing on achieving reasonable operating ranges, achieving low power, small size and low cost, and applications for extensions of this technology.

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.

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.

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.

Experimental investigation of a moving averaging algorithm for motion perpendicular to the leaf travel direction in dynamic MLC target tracking.

PubMed

Yoon, Jai-Woong; Sawant, Amit; Suh, Yelin; Cho, Byung-Chul; Suh, Tae-Suk; Keall, Paul

2011-07-01

In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described. The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a tgamma-test with a 3%/3 mm criterion. The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the gamma-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation. The delivery efficiency of

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

Log-polar mapping-based scale space tracking with adaptive target response

NASA Astrophysics Data System (ADS)

Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Zhang, Ximing

2017-05-01

Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.

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

Force Protection via UGV-UAV Collaboration: Development of Control Law for Vision Based Target Tracking on SUAV

DTIC Science & Technology

2007-12-01

Hardware - In - Loop , Piccolo, UAV, Unmanned Aerial Vehicle 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...Maneuvering Target.......................... 35 C. HARDWARE - IN - LOOP SIMULATION............................................... 37 1. Hardware - In - Loop Setup...law as proposed in equation (23) is capable of tracking a maneuvering target. C. HARDWARE - IN - LOOP SIMULATION The intention of HIL simulation

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

AAVSO Target Tool: A Web-Based Service for Tracking Variable Star Observations (Abstract)

NASA Astrophysics Data System (ADS)

Burger, D.; Stassun, K. G.; Barnes, C.; Kafka, S.; Beck, S.; Li, K.

2018-06-01

(Abstract only) The AAVSO Target Tool is a web-based interface for bringing stars in need of observation to the attention of AAVSOís network of amateur and professional astronomers. The site currently tracks over 700 targets of interest, collecting data from them on a regular basis from AAVSOís servers and sorting them based on priority. While the target tool does not require a login, users can obtain visibility times for each target by signing up and entering a telescope location. Other key features of the site include filtering by AAVSO observing section, sorting by different variable types, formatting the data for printing, and exporting the data to a CSV file. The AAVSO Target Tool builds upon seven years of experience developing web applications for astronomical data analysis, most notably on Filtergraph (Burger, D., et al. 2013, Astronomical Data Analysis Software and Systems XXII, Astronomical Society of the Pacific, San Francisco, 399), and is built using the web2py web framework based on the python programming language. The target tool is available at http://filtergraph.com/aavso.

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

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.

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.

Determination of feature generation methods for PTZ camera object tracking

NASA Astrophysics Data System (ADS)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Tracking of multimodal therapeutic nanocomplexes targeting breast cancer in vivo.

PubMed

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G; Halas, Naomi J; Joshi, Amit

2010-12-08

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions.

Tracking of Multimodal Therapeutic Nanocomplexes Targeting Breast Cancer in Vivo

PubMed Central

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F.; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G.; Halas, Naomi J.; Joshi, Amit

2014-01-01

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions. PMID:21090693

Apparatus and method for tracking a molecule or particle in three dimensions

DOEpatents

Werner, James H [Los Alamos, NM; Goodwin, Peter M [Los Alamos, NM; Lessard, Guillaume [Santa Fe, NM

2009-03-03

An apparatus and method were used to track the movement of fluorescent particles in three dimensions. Control software was used with the apparatus to implement a tracking algorithm for tracking the motion of the individual particles in glycerol/water mixtures. Monte Carlo simulations suggest that the tracking algorithms in combination with the apparatus may be used for tracking the motion of single fluorescent or fluorescently labeled biomolecules in three dimensions.

Uninformative Prior Multiple Target Tracking Using Evidential Particle Filters

NASA Astrophysics Data System (ADS)

Worthy, J. L., III; Holzinger, M. J.

Space situational awareness requires the ability to initialize state estimation from short measurements and the reliable association of observations to support the characterization of the space environment. The electro-optical systems used to observe space objects cannot fully characterize the state of an object given a short, unobservable sequence of measurements. Further, it is difficult to associate these short-arc measurements if many such measurements are generated through the observation of a cluster of satellites, debris from a satellite break-up, or from spurious detections of an object. An optimization based, probabilistic short-arc observation association approach coupled with a Dempster-Shafer based evidential particle filter in a multiple target tracking framework is developed and proposed to address these problems. The optimization based approach is shown in literature to be computationally efficient and can produce probabilities of association, state estimates, and covariances while accounting for systemic errors. Rigorous application of Dempster-Shafer theory is shown to be effective at enabling ignorance to be properly accounted for in estimation by augmenting probability with belief and plausibility. The proposed multiple hypothesis framework will use a non-exclusive hypothesis formulation of Dempster-Shafer theory to assign belief mass to candidate association pairs and generate tracks based on the belief to plausibility ratio. The proposed algorithm is demonstrated using simulated observations of a GEO satellite breakup scenario.

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 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.

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

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

PubMed

Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

2017-07-20

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

Method and apparatus for imaging through 3-dimensional tracking of protons

NASA Technical Reports Server (NTRS)

Ryan, James M. (Inventor); Macri, John R. (Inventor); McConnell, Mark L. (Inventor)

2001-01-01

A method and apparatus for creating density images of an object through the 3-dimensional tracking of protons that have passed through the object are provided. More specifically, the 3-dimensional tracking of the protons is accomplished by gathering and analyzing images of the ionization tracks of the protons in a closely packed stack of scintillating fibers.

Two new methods to increase the contrast of track-etch neutron radiographs

NASA Technical Reports Server (NTRS)

Morley, J.

1973-01-01

In one method, fluorescent dye is deposited into tracks of radiograph and viewed under ultraviolet light. In second method, track-etch radiograph is placed between crossed polaroid filters, exposed to diffused light and resulting image is projected onto photographic film.

Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

PubMed Central

Chen, Chao-I; Koseluk, Robert; Buchanan, Chase; Duerner, Andrew; Jeppesen, Brian; Laux, Hunter

2015-01-01

An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. PMID:25970254

A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

PubMed Central

Liu, Zhuowei; Chen, Shuxin; Wu, Hao; He, Renke; Hao, Lin

2018-01-01

In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers. PMID:29617348

Objective comparison of particle tracking methods

PubMed Central

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F.; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R.; Godinez, William J.; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E. G.; Jaldén, Joakim; Blau, Helen M.; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L.; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P.; Dan, Han-Wei; Tsai, Yuh-Show; de Solórzano, Carlos Ortiz; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-01-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Since manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized, for the first time, an open competition, in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to important practical conclusions for users and developers. PMID:24441936

Objective comparison of particle tracking methods.

PubMed

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R; Godinez, William J; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E G; Jaldén, Joakim; Blau, Helen M; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P; Dan, Han-Wei; Tsai, Yuh-Show; Ortiz de Solórzano, Carlos; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-03-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

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

Enhanced Algorithms for EO/IR Electronic Stabilization, Clutter Suppression, and Track-Before-Detect for Multiple Low Observable Targets

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud

Potential dosimetric benefits of adaptive tumor tracking over the internal target volume concept for stereotactic body radiation therapy of pancreatic cancer.

PubMed

Karava, Konstantina; Ehrbar, Stefanie; Riesterer, Oliver; Roesch, Johannes; Glatz, Stefan; Klöck, Stephan; Guckenberger, Matthias; Tanadini-Lang, Stephanie

2017-11-09

Radiotherapy for pancreatic cancer has two major challenges: (I) the tumor is adjacent to several critical organs and, (II) the mobility of both, the tumor and its surrounding organs at risk (OARs). A treatment planning study simulating stereotactic body radiation therapy (SBRT) for pancreatic tumors with both the internal target volume (ITV) concept and the tumor tracking approach was performed. The two respiratory motion-management techniques were compared in terms of doses to the target volume and organs at risk. Two volumetric-modulated arc therapy (VMAT) treatment plans (5 × 5 Gy) were created for each of the 12 previously treated pancreatic cancer patients, one using the ITV concept and one the tumor tracking approach. To better evaluate the overall dose delivered to the moving tumor volume, 4D dose calculations were performed on four-dimensional computed tomography (4DCT) scans. The resulting planning target volume (PTV) size for each technique was analyzed. Target and OAR dose parameters were reported and analyzed for both 3D and 4D dose calculation. Tumor motion ranged from 1.3 to 11.2 mm. Tracking led to a reduction of PTV size (max. 39.2%) accompanied with significant better tumor coverage (p<0.05, paired Wilcoxon signed rank test) both in 3D and 4D dose calculations and improved organ at risk sparing. Especially for duodenum, stomach and liver, the mean dose was significantly reduced (p<0.05) with tracking for 3D and 4D dose calculations. By using an adaptive tumor tracking approach for respiratory-induced pancreatic motion management, a significant reduction in PTV size can be achieved, which subsequently facilitates treatment planning, and improves organ dose sparing. The dosimetric benefit of tumor tracking is organ and patient-specific.

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

PubMed

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-01

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different

A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

PubMed Central

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J.; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa

2016-01-01

On‐board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real‐time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image‐guided radiotherapy (MR‐IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR‐TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR‐TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD‐LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP‐TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high‐contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR‐TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and

A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

PubMed

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-08

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual con-tours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (< 1 ms) with a satisfying accuracy (Dice = 0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of

Implementation of a sensor guided flight algorithm for target tracking by small UAS

NASA Astrophysics Data System (ADS)

Collins, Gaemus E.; Stankevitz, Chris; Liese, Jeffrey

2011-06-01

Small xed-wing UAS (SUAS) such as Raven and Unicorn have limited power, speed, and maneuverability. Their missions can be dramatically hindered by environmental conditions (wind, terrain), obstructions (buildings, trees) blocking clear line of sight to a target, and/or sensor hardware limitations (xed stare, limited gimbal motion, lack of zoom). Toyon's Sensor Guided Flight (SGF) algorithm was designed to account for SUAS hardware shortcomings and enable long-term tracking of maneuvering targets by maintaining persistent eyes-on-target. SGF was successfully tested in simulation with high-delity UAS, sensor, and environment models, but real- world ight testing with 60 Unicorn UAS revealed surprising second order challenges that were not highlighted by the simulations. This paper describes the SGF algorithm, our rst round simulation results, our second order discoveries from ight testing, and subsequent improvements that were made to the algorithm.

A joint tracking method for NSCC based on WLS algorithm

NASA Astrophysics Data System (ADS)

Luo, Ruidan; Xu, Ying; Yuan, Hong

2017-12-01

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

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.

Track reconstruction in the emulsion-lead target of the OPERA experiment using the ESS microscope

NASA Astrophysics Data System (ADS)

Arrabito, L.; Bozza, C.; Buontempo, S.; Consiglio, L.; Cozzi, M.; D'Ambrosio, N.; DeLellis, G.; DeSerio, M.; Di Capua, F.; Di Ferdinando, D.; Di Marco, N.; Ereditato, A.; Esposito, L. S.; Fini, R. A.; Giacomelli, G.; Giorgini, M.; Grella, G.; Ieva, M.; Janicsko Csathy, J.; Juget, F.; Kreslo, I.; Laktineh, I.; Manai, K.; Mandrioli, G.; Marotta, A.; Migliozzi, P.; Monacelli, P.; Moser, U.; Muciaccia, M. T.; Pastore, A.; Patrizii, L.; Petukhov, Y.; Pistillo, C.; Pozzato, M.; Romano, G.; Rosa, G.; Russo, A.; Savvinov, N.; Schembri, A.; Scotto Lavina, L.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Strolin, P.; Tioukov, V.; Waelchli, T.

2007-05-01

The OPERA experiment, designed to conclusively prove the existence of νμ→ντ oscillations in the atmospheric sector, makes use of a massive lead-nuclear emulsion target to observe the appearance of ντ's in the CNGS νμ beam. The location and analysis of the neutrino interactions in quasi real-time required the development of fast computer-controlled microscopes able to reconstruct particle tracks with sub-micron precision and high efficiency at a speed of ~20 cm2/h. This paper describes the performance in particle track reconstruction of the European Scanning System, a novel automatic microscope for the measurement of emulsion films developed for OPERA.

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.

Maximum Power Point Tracking with Dichotomy and Gradient Method for Automobile Exhaust Thermoelectric Generators

NASA Astrophysics Data System (ADS)

Fang, W.; Quan, S. H.; Xie, C. J.; Tang, X. F.; Wang, L. L.; Huang, L.

2016-03-01

In this study, a direct-current/direct-current (DC/DC) converter with maximum power point tracking (MPPT) is developed to down-convert the high voltage DC output from a thermoelectric generator to the lower voltage required to charge batteries. To improve the tracking accuracy and speed of the converter, a novel MPPT control scheme characterized by an aggregated dichotomy and gradient (ADG) method is proposed. In the first stage, the dichotomy algorithm is used as a fast search method to find the approximate region of the maximum power point. The gradient method is then applied for rapid and accurate tracking of the maximum power point. To validate the proposed MPPT method, a test bench composed of an automobile exhaust thermoelectric generator was constructed for harvesting the automotive exhaust heat energy. Steady-state and transient tracking experiments under five different load conditions were carried out using a DC/DC converter with the proposed ADG and with three traditional methods. The experimental results show that the ADG method can track the maximum power within 140 ms with a 1.1% error rate when the engine operates at 3300 rpm@71 NM, which is superior to the performance of the single dichotomy method, the single gradient method and the perturbation and observation method from the viewpoint of improved tracking accuracy and speed.

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.

Radiation-hardened fast acquisition/weak signal tracking system and method

NASA Technical Reports Server (NTRS)

Winternitz, Luke (Inventor); Boegner, Gregory J. (Inventor); Sirotzky, Steve (Inventor)

2009-01-01

A global positioning system (GPS) receiver and method of acquiring and tracking GPS signals comprises an antenna adapted to receive GPS signals; an analog radio frequency device operatively connected to the antenna and adapted to convert the GPS signals from an analog format to a digital format; a plurality of GPS signal tracking correlators operatively connected to the analog RF device; a GPS signal acquisition component operatively connected to the analog RF device and the plurality of GPS signal tracking correlators, wherein the GPS signal acquisition component is adapted to calculate a maximum vector on a databit correlation grid; and a microprocessor operatively connected to the plurality of GPS signal tracking correlators and the GPS signal acquisition component, wherein the microprocessor is adapted to compare the maximum vector with a predetermined correlation threshold to allow the GPS signal to be fully acquired and tracked.

Gamma-ray tracking method for pet systems

DOEpatents

Mihailescu, Lucian; Vetter, Kai M.

2010-06-08

Gamma-ray tracking methods for use with granular, position sensitive detectors identify the sequence of the interactions taking place in the detector and, hence, the position of the first interaction. The improved position resolution in finding the first interaction in the detection system determines a better definition of the direction of the gamma-ray photon, and hence, a superior source image resolution. A PET system using such a method will have increased efficiency and position resolution.

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

Geometric Factors in Target Positioning and Tracking

DTIC Science & Technology

2009-07-01

Shalom and X.R. Li, Multitarget-Multisensor Tracking: Principles and Techniques, YBS Publishing, Storrs, CT, 1995. [2] S. Blackman and R. Popoli, Design...Multitarget-Multisensor Tracking: Applications and Advances, Vol.2, Y. Bar- Shalom (Ed.), 325-392, Artech House, Norwood, MA, 1999. [10] B. Ristic...R. Yarlagadda, I. Ali , N. Al-Dhahir, and J. Hershey, “GPS GDOP Metric,” IEE Proc. Radar, Sonar Navig, 147(5), Oct. 2000. [14] A. Kelly

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

Dazzle camouflage and the confusion effect: the influence of varying speed on target tracking.

PubMed

Hogan, Benedict G; Cuthill, Innes C; Scott-Samuel, Nicholas E

2017-01-01

The formation of groups is a common strategy to avoid predation in animals, and recent research has indicated that there may be interactions between some forms of defensive coloration, notably high-contrast 'dazzle camouflage', and one of the proposed benefits of grouping: the confusion effect. However, research into the benefits of dazzle camouflage has largely used targets moving with constant speed. This simplification may not generalize well to real animal systems, where a number of factors influence both within- and between-individual variation in speed. Departure from the speed of your neighbours in a group may be predicted to undermine the confusion effect. This is because individual speed may become a parameter through which the observer can individuate otherwise similar targets: an 'oddity effect'. However, dazzle camouflage patterns are thought to interfere with predator perception of speed and trajectory. The current experiment investigated the possibility that such patterns could ameliorate the oddity effect caused by within-group differences in prey speed. We found that variation in speed increased the ease with which participants could track targets in all conditions. However, we found no evidence that motion dazzle camouflage patterns reduced oddity effects based on this variation in speed, a result that may be informative about the mechanisms behind this form of defensive coloration. In addition, results from those conditions most similar to those of published studies replicated previous results, indicating that targets with stripes parallel to the direction of motion are harder to track, and that this pattern interacts with the confusion effect to a greater degree than background matching or orthogonal-to-motion striped patterns.

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…

A neurocomputational model of figure-ground discrimination and target tracking.

PubMed

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

Improvements to Passive Acoustic Tracking Methods for Marine Mammal Monitoring

DTIC Science & Technology

2016-05-02

separate and associate calls from individual animals . Marine mammal; Passive acoustic monitoring; Localization; Tracking; Multiple source; Sparse array...position and hydrophone timing offset in addition to animal position Almost all marine mammal tracking methods treat animal position as the only unknown...Workshop on Detection, Classification and Localization (DCL) of Marine Mammals). The animals were expected to be relatively close to the surface

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.

COMPARATIVE DIVERSITY OF FECAL BACTERIA IN AGRICULTURALLY SIGNIFICANT ANIMALS TO IDENTIFY ALTERNATIVE TARGETS FOR MICROBIAL SOURCE TRACKING

EPA Science Inventory

Animals of agricultural significance contribute a large percentage of fecal pollution to waterways via runoff contamination. The premise of microbial source tracking is to utilize fecal bacteria to identify target populations which are directly correlated to specific animal feces...

A 3D front tracking method on a CPU/GPU system

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

Bo, Wurigen; Grove, John

2011-01-21

We describe the method to port a sequential 3D interface tracking code to a GPU with CUDA. The interface is represented as a triangular mesh. Interface geometry properties and point propagation are performed on a GPU. Interface mesh adaptation is performed on a CPU. The convergence of the method is assessed from the test problems with given velocity fields. Performance results show overall speedups from 11 to 14 for the test problems under mesh refinement. We also briefly describe our ongoing work to couple the interface tracking method with a hydro solver.

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.

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

A practical method of estimating standard error of age in the fission track dating method

USGS Publications Warehouse

Johnson, N.M.; McGee, V.E.; Naeser, C.W.

1979-01-01

A first-order approximation formula for the propagation of error in the fission track age equation is given by PA = C[P2s+P2i+P2??-2rPsPi] 1 2, where PA, Ps, Pi and P?? are the percentage error of age, of spontaneous track density, of induced track density, and of neutron dose, respectively, and C is a constant. The correlation, r, between spontaneous are induced track densities is a crucial element in the error analysis, acting generally to improve the standard error of age. In addition, the correlation parameter r is instrumental is specifying the level of neutron dose, a controlled variable, which will minimize the standard error of age. The results from the approximation equation agree closely with the results from an independent statistical model for the propagation of errors in the fission-track dating method. ?? 1979.

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

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

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.

Autonomous target tracking of UAVs based on low-power neural network hardware

NASA Astrophysics Data System (ADS)

Yang, Wei; Jin, Zhanpeng; Thiem, Clare; Wysocki, Bryant; Shen, Dan; Chen, Genshe

2014-05-01

Detecting and identifying targets in unmanned aerial vehicle (UAV) images and videos have been challenging problems due to various types of image distortion. Moreover, the significantly high processing overhead of existing image/video processing techniques and the limited computing resources available on UAVs force most of the processing tasks to be performed by the ground control station (GCS) in an off-line manner. In order to achieve fast and autonomous target identification on UAVs, it is thus imperative to investigate novel processing paradigms that can fulfill the real-time processing requirements, while fitting the size, weight, and power (SWaP) constrained environment. In this paper, we present a new autonomous target identification approach on UAVs, leveraging the emerging neuromorphic hardware which is capable of massively parallel pattern recognition processing and demands only a limited level of power consumption. A proof-of-concept prototype was developed based on a micro-UAV platform (Parrot AR Drone) and the CogniMemTMneural network chip, for processing the video data acquired from a UAV camera on the y. The aim of this study was to demonstrate the feasibility and potential of incorporating emerging neuromorphic hardware into next-generation UAVs and their superior performance and power advantages towards the real-time, autonomous target tracking.

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.

Colonoscope navigation system using colonoscope tracking method based on line registration

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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.

A novel in vivo method for lung segment movement tracking

NASA Astrophysics Data System (ADS)

Leira, H. O.; Tangen, G. A.; Hofstad, E. F.; Langø, T.; Amundsen, T.

2012-02-01

Knowledge about lung movement in health and disease is sparse. Current evaluation methods, such as CT, MRI and external view have significant limitations. To study respiratory movement for image guided tumour diagnostics and respiratory physiology, we needed a method that overcomes these limitations. We fitted balloon catheters with electromagnetic sensors, and placed them in lung lobes of ventilated pigs. The sensors sensed their position at 40 Hz in an electromagnetic tracking field with a precision of ∼0.5 mm. The method was evaluated by recording sensor movement in different body positions and at different tidal volumes. No ‘gold standard’ exists for lung segment tracking, so our results were compared to ‘common knowledge’. The sensors were easily placed, showed no clinically relevant position drift and yielded sub-millimetre accuracy. Our measurements fit ‘common knowledge’, as increased ventilation volume increased respiratory movement, and the right lung moved significantly less in the right than the left lateral position. The novel method for tracking lung segment movements during respiration was easy to implement and yielded high spatial and temporal resolution, and the equipment parts are reusable. It is easy to implement as a research tool for lung physiology, navigated bronchoscopy and radiation therapy.

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

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

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

PubMed

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

2016-07-02

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

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

PubMed Central

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

2016-01-01

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

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.

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

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.

A simple and rapid method for high-resolution visualization of single-ion tracks

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

Omichi, Masaaki; Center for Collaborative Research, Anan National College of Technology, Anan, Tokushima 774-0017; Choi, Wookjin

2014-11-15

Prompt determination of spatial points of single-ion tracks plays a key role in high-energy particle induced-cancer therapy and gene/plant mutations. In this study, a simple method for the high-resolution visualization of single-ion tracks without etching was developed through the use of polyacrylic acid (PAA)-N, N’-methylene bisacrylamide (MBAAm) blend films. One of the steps of the proposed method includes exposure of the irradiated films to water vapor for several minutes. Water vapor was found to promote the cross-linking reaction of PAA and MBAAm to form a bulky cross-linked structure; the ion-track scars were detectable at a nanometer scale by atomic forcemore » microscopy. This study demonstrated that each scar is easily distinguishable, and the amount of generated radicals of the ion tracks can be estimated by measuring the height of the scars, even in highly dense ion tracks. This method is suitable for the visualization of the penumbra region in a single-ion track with a high spatial resolution of 50 nm, which is sufficiently small to confirm that a single ion hits a cell nucleus with a size ranging between 5 and 20 μm.« less

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

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.

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

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.

A Reliable and Real-Time Tracking Method with Color Distribution

PubMed Central

Zhao, Zishu; Han, Yuqi; Xu, Tingfa; Li, Xiangmin; Song, Haiping; Luo, Jiqiang

2017-01-01

Occlusion is a challenging problem in visual tracking. Therefore, in recent years, many trackers have been explored to solve this problem, but most of them cannot track the target in real time because of the heavy computational cost. A spatio-temporal context (STC) tracker was proposed to accelerate the task by calculating context information in the Fourier domain, alleviating the performance in handling occlusion. In this paper, we take advantage of the high efficiency of the STC tracker and employ salient prior model information based on color distribution to improve the robustness. Furthermore, we exploit a scale pyramid for accurate scale estimation. In particular, a new high-confidence update strategy and a re-searching mechanism are used to avoid the model corruption and handle occlusion. Extensive experimental results demonstrate our algorithm outperforms several state-of-the-art algorithms on the OTB2015 dataset. PMID:28994748

Sub-micron accurate track navigation method ``Navi'' for the analysis of Nuclear Emulsion

NASA Astrophysics Data System (ADS)

Yoshioka, T.; Yoshida, J.; Kodama, K.

2011-03-01

Sub-micron accurate track navigation in Nuclear Emulsion is realized by using low energy signals detected by automated Nuclear Emulsion read-out systems. Using those much dense ``noise'', about 104 times larger than the real tracks, the accuracy of the track position navigation reaches to be sub micron only by using the information of a microscope field of view, 200 micron times 200 micron. This method is applied to OPERA analysis in Japan, i.e. support of human eye checks of the candidate tracks, confirmation of neutrino interaction vertexes and to embed missing track segments to the track data read-out by automated systems.