Tracking Multiple Video Targets with an Improved GM-PHD Tracker

PubMed Central

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

2015-01-01

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

Exploiting target amplitude information to improve multi-target tracking

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Blair, W. Dale

2006-05-01

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

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.

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

Underwater Acoustic Target Tracking: A Review

PubMed Central

Han, Ying; Fan, Liying

2018-01-01

Advances in acoustic technology and instrumentation now make it possible to explore marine resources. As a significant component of ocean exploration, underwater acoustic target tracking has aroused wide attention both in military and civil fields. Due to the complexity of the marine environment, numerous techniques have been proposed to obtain better tracking performance. In this paper, we survey over 100 papers ranging from innovative papers to the state-of-the-art in this field to present underwater tracking technologies. Not only the related knowledge of acoustic tracking instrument and tracking progress is clarified in detail, but also a novel taxonomy method is proposed. In this paper, algorithms for underwater acoustic target tracking are classified based on the methods used as: (1) instrument-assisted methods; (2) mode-based methods; (3) tracking optimization methods. These algorithms are compared and analyzed in the aspect of dimensions, numbers, and maneuvering of the tracking target, which is different from other survey papers. Meanwhile, challenges, countermeasures, and lessons learned are illustrated in this paper. PMID:29301318

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.

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

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

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

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.

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

Applications of amorphous track models in radiation biology

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Nikjoo, H.; Goodhead, D. T.; Wilson, J. W. (Principal Investigator)

1999-01-01

The average or amorphous track model uses the response of a system to gamma-rays and the radial distribution of dose about an ion's path to describe survival and other cellular endpoints from proton, heavy ion, and neutron irradiation. This model has been used for over 30 years to successfully fit many radiobiology data sets. We review several extensions of this approach that address objections to the original model, and consider applications of interest in radiobiology and space radiation risk assessment. In the light of present views of important cellular targets, the role of target size as manifested through the relative contributions from ion-kill (intra-track) and gamma-kill (inter-track) remains a critical question in understanding the success of the amorphous track model. Several variations of the amorphous model are discussed, including ones that consider the radial distribution of event-sizes rather than average electron dose, damage clusters rather than multiple targets, and a role for repair or damage processing.

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.

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

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

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.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

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

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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�

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.

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.

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.

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.

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%.

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.

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

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.

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.

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

Research on target tracking in coal mine based on optical flow method

NASA Astrophysics Data System (ADS)

Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

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

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.

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

The research on the mean shift algorithm for target tracking

NASA Astrophysics Data System (ADS)

CAO, Honghong

2017-06-01

The traditional mean shift algorithm for target tracking is effective and high real-time, but there still are some shortcomings. The traditional mean shift algorithm is easy to fall into local optimum in the tracking process, the effectiveness of the method is weak when the object is moving fast. And the size of the tracking window never changes, the method will fail when the size of the moving object changes, as a result, we come up with a new method. We use particle swarm optimization algorithm to optimize the mean shift algorithm for target tracking, Meanwhile, SIFT (scale-invariant feature transform) and affine transformation make the size of tracking window adaptive. At last, we evaluate the method by comparing experiments. Experimental result indicates that the proposed method can effectively track the object and the size of the tracking window changes.

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

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

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.

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 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 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.

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

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

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

Infrared dim-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.

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.

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

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

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

NucliTrack: an integrated nuclei tracking application.

PubMed

Cooper, Sam; Barr, Alexis R; Glen, Robert; Bakal, Chris

2017-10-15

Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack's interactive, graphical interface makes it significantly more user friendly. NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab. sam@socooper.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

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.

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

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.

A ground moving target emergency tracking method for catastrophe rescue

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

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.

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.

NucliTrack: an integrated nuclei tracking application

PubMed Central

Cooper, Sam; Barr, Alexis R.; Glen, Robert; Bakal, Chris

2017-01-01

Abstract Summary Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack’s interactive, graphical interface makes it significantly more user friendly. Availability and implementation NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab. Contact sam@socooper.com Supplementary information Supplementary data are available at Bioinformatics online. PMID:28637183

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

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

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.

Application of TrackEye in equine locomotion research.

PubMed

Drevemo, S; Roepstorff, L; Kallings, P; Johnston, C J

1993-01-01

TrackEye is an analysis system, which is applicable for equine biokinematic studies. It covers the whole process from digitizing of images, automatic target tracking and analysis. Key components in the system are an image work station for processing of video images and a high-resolution film-to-video scanner for 16-mm film. A recording module controls the input device and handles the capture of image sequences into a videodisc system, and a tracking module is able to follow reference markers automatically. The system offers a flexible analysis including calculations of markers displacements, distances and joint angles, velocities and accelerations. TrackEye was used to study effects of phenylbutazone on the fetlock and carpal joint angle movements in a horse with a mild lameness caused by osteo-arthritis in the fetlock joint of a forelimb. Significant differences, most evident before treatment, were observed in the minimum fetlock and carpal joint angles when contralateral limbs were compared (p < 0.001). The minimum fetlock angle and the minimum carpal joint angle were significantly greater in the lame limb before treatment compared to those 6, 37 and 49 h after the last treatment (p < 0.001).

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

Joint Transform Correlation for face tracking: elderly fall detection application

NASA Astrophysics Data System (ADS)

Katz, Philippe; Aron, Michael; Alfalou, Ayman

2013-03-01

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

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

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

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.

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

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

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.

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.

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.

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

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.

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.

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

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.

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

Actinium-225 in targeted alpha-particle therapeutic applications

PubMed Central

Scheinberg, David A.; McDevit, Michael R.

2017-01-01

Alpha particle-emitting isotopes are being investigated in radioimmunotherapeutic applications because of their unparalleled cytotoxicity when targeted to cancer and their relative lack of toxicity towards untargeted normal tissue. Actinium-225 has been developed into potent targeting drug constructs and is in clinical use against acute myelogenous leukemia. The key properties of the alpha particles generated by 225Ac are the following: i) limited range in tissue of a few cell diameters; ii) high linear energy transfer leading to dense radiation damage along each alpha track; iii) a 10 day half-life; and iv) four net alpha particles emitted per decay. Targeting 225Ac-drug constructs have potential in the treatment of cancer. PMID:22202153

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.

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.

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.

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.

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.

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.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI

PubMed Central

Stawicki, Piotr; Gembler, Felix; Rezeika, Aya; Volosyak, Ivan

2017-01-01

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques. PMID:28379187

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

Application of Smoothing Techniques for Tracking Maneuvering Targets. Multiple Target Tracking in Clutter: New Approaches

DTIC Science & Technology

1992-07-01

target state estimation is affected not only by the measurement noise but also by the uncertainty in the origins of the measurements. To improve the...to identify targets in the presence of anticipated background noise (including earth, lunar, star backgrounds, complicated spacecraft structures...each other. Futhermore, those frames are often degraded versions of the original scene due to blur and noise . Through the task of image registration

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.

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.

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.

Impact of a scholarly track on quality of residency program applicants.

PubMed

Celebi, Julie M; Nguyen, Cathina T; Sattler, Amelia L; Stevens, Michael B; Lin, Steven Y

2016-11-01

It is generally believed that residency programs offering scholarly tracks attract higher quality applicants, although there is little evidence of this in the literature. We explored the impact of a clinician-educator track on the quality of applicants to our residency program by comparing the volume and characteristics of applicants before (2008-2011) and after (2012-2015) the track was introduced. The total number of applications received was compared between the pre-track and post-track years. Among interviewees, data on United States Medical Licensing Examination (USMLE) Step 1 scores, Step 2 Clinical Knowledge (CK) scores, Medical Student Performance Evaluation (MSPE) scores, and proportion of candidates with an advanced degree (e.g. MPH, PhD) were compared. An online survey was administered to all interviewees in 2014-2015 to measure interest in the track. The total number of applications to the residency program increased significantly from the pre-track to the post-track years. Compared to the pre-track years, interviewees during the post-track years had statistically higher USMLE Step 1 and Step 2 CK scores, better MSPE scores, and were more likely to have an advanced degree. Two-thirds of survey respondents reported that the track increased their interest in the residency program. A residency clinician-educator track may be associated with increased overall interest from applicants, higher application volume, and better measures of applicant quality based on USMLE scores, MSPE scores, and proportion of candidates with an advanced degree. Residency programs may consider a potential increase in the quality of their applicants as an added benefit of offering a scholarly track.

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.

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

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.

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

PubMed

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

2017-03-20

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

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

PubMed Central

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

2017-01-01

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

A 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

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.

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.

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.

Vigilante: Ultrafast Smart Sensor for Target Recognition and Precision Tracking in a Simulated CMD Scenario

NASA Technical Reports Server (NTRS)

Uldomkesmalee, Suraphol; Suddarth, Steven C.

1997-01-01

VIGILANTE is an ultrafast smart sensor testbed for generic Automatic Target Recognition (ATR) applications with a series of capability demonstration focussed on cruise missile defense (CMD). VIGILANTE's sensor/processor architecture is based on next-generation UV/visible/IR sensors and a tera-operations per second sugar-cube processor, as well as supporting airborne vehicle. Excellent results of efficient ATR methodologies that use an eigenvectors/neural network combination and feature-based precision tracking have been demonstrated in the laboratory environment.

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.

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.

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.

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.

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

CMOS imager for pointing and tracking applications

NASA Technical Reports Server (NTRS)

Sun, Chao (Inventor); Pain, Bedabrata (Inventor); Yang, Guang (Inventor); Heynssens, Julie B. (Inventor)

2006-01-01

Systems and techniques to realize pointing and tracking applications with CMOS imaging devices. In general, in one implementation, the technique includes: sampling multiple rows and multiple columns of an active pixel sensor array into a memory array (e.g., an on-chip memory array), and reading out the multiple rows and multiple columns sampled in the memory array to provide image data with reduced motion artifact. Various operation modes may be provided, including TDS, CDS, CQS, a tracking mode to read out multiple windows, and/or a mode employing a sample-first-read-later readout scheme. The tracking mode can take advantage of a diagonal switch array. The diagonal switch array, the active pixel sensor array and the memory array can be integrated onto a single imager chip with a controller. This imager device can be part of a larger imaging system for both space-based applications and terrestrial applications.

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.

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

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.

Neural network fusion capabilities for efficient implementation of tracking algorithms

NASA Astrophysics Data System (ADS)

Sundareshan, Malur K.; Amoozegar, Farid

1996-05-01

The ability to efficiently fuse information of different forms for facilitating intelligent decision-making is one of the major capabilities of trained multilayer neural networks that is being recognized int eh recent times. While development of innovative adaptive control algorithms for nonlinear dynamical plants which attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. In this paper we describe the capabilities and functionality of neural network algorithms for data fusion and implementation of nonlinear tracking filters. For a discussion of details and for serving as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes form the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. Such an approach results in an overall nonlinear tracking filter which has several advantages over the popular efforts at designing nonlinear estimation algorithms for tracking applications, the principle one being the reduction of mathematical and computational complexities. A system architecture that efficiently integrates the processing capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described in this paper.

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

Emerging applications of eye-tracking technology in dermatology.

PubMed

John, Kevin K; Jensen, Jakob D; King, Andy J; Pokharel, Manusheela; Grossman, Douglas

2018-04-06

Eye-tracking technology has been used within a multitude of disciplines to provide data linking eye movements to visual processing of various stimuli (i.e., x-rays, situational positioning, printed information, and warnings). Despite the benefits provided by eye-tracking in allowing for the identification and quantification of visual attention, the discipline of dermatology has yet to see broad application of the technology. Notwithstanding dermatologists' heavy reliance upon visual patterns and cues to discriminate between benign and atypical nevi, literature that applies eye-tracking to the study of dermatology is sparse; and literature specific to patient-initiated behaviors, such as skin self-examination (SSE), is largely non-existent. The current article provides a review of eye-tracking research in various medical fields, culminating in a discussion of current applications and advantages of eye-tracking for dermatology research. Copyright © 2018 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

DEGAS: sharing and tracking target compound ideas with external collaborators.

PubMed

Lee, Man-Ling; Aliagas, Ignacio; Dotson, Jennafer; Feng, Jianwen A; Gobbi, Alberto; Heffron, Timothy

2012-02-27

To minimize the risk of failure in clinical trials, drug discovery teams must propose active and selective clinical candidates with good physicochemical properties. An additional challenge is that today drug discovery is often conducted by teams at different geographical locations. To improve the collaborative decision making on which compounds to synthesize, we have implemented DEGAS, an application which enables scientists from Genentech and from collaborating external partners to instantly access the same data. DEGAS was implemented to ensure that only the best target compounds are made and that they are made without duplicate effort. Physicochemical properties and DMPK model predictions are computed for each compound to allow the team to make informed decisions when prioritizing. The synthesis progress can be easily tracked. While developing DEGAS, ease of use was a particular goal in order to minimize the difficulty of training and supporting remote users.

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.

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

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Single-photon sensitive fast ebCMOS camera system for multiple-target tracking of single fluorophores: application to nano-biophotonics

NASA Astrophysics Data System (ADS)

Cajgfinger, Thomas; Chabanat, Eric; Dominjon, Agnes; Doan, Quang T.; Guerin, Cyrille; Houles, Julien; Barbier, Remi

2011-03-01

Nano-biophotonics applications will benefit from new fluorescent microscopy methods based essentially on super-resolution techniques (beyond the diffraction limit) on large biological structures (membranes) with fast frame rate (1000 Hz). This trend tends to push the photon detectors to the single-photon counting regime and the camera acquisition system to real time dynamic multiple-target tracing. The LUSIPHER prototype presented in this paper aims to give a different approach than those of Electron Multiplied CCD (EMCCD) technology and try to answer to the stringent demands of the new nano-biophotonics imaging techniques. The electron bombarded CMOS (ebCMOS) device has the potential to respond to this challenge, thanks to the linear gain of the accelerating high voltage of the photo-cathode, to the possible ultra fast frame rate of CMOS sensors and to the single-photon sensitivity. We produced a camera system based on a 640 kPixels ebCMOS with its acquisition system. The proof of concept for single-photon based tracking for multiple single-emitters is the main result of this paper.

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…

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

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.

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

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

Quantitative nanoparticle tracking: applications to nanomedicine.

PubMed

Huang, Feiran; Dempsey, Christopher; Chona, Daniela; Suh, Junghae

2011-06-01

Particle tracking is an invaluable technique to extract quantitative and qualitative information regarding the transport of nanomaterials through complex biological environments. This technique can be used to probe the dynamic behavior of nanoparticles as they interact with and navigate through intra- and extra-cellular barriers. In this article, we focus on the recent developments in the application of particle-tracking technology to nanomedicine, including the study of synthetic and virus-based materials designed for gene and drug delivery. Specifically, we cover research where mean square displacements of nanomaterial transport were explicitly determined in order to quantitatively assess the transport of nanoparticles through biological environments. Particle-tracking experiments can provide important insights that may help guide the design of more intelligent and effective diagnostic and therapeutic nanoparticles.

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.

Industrial applications of ion track technology

NASA Astrophysics Data System (ADS)

Hanot, H.; Ferain, E.

2009-03-01

It4ip sa is a spin out from the Université Catholique de Louvain (Belgium) dedicated to the development and production of unique templates and membranes based on the combination of ion track technology of polymers. It supplies customers with hi-tech products, state-of-the-art research and product development services with template capability to make high value added membranes. Notably based on results coming from several collaborative R&D projects supported by European and Regional funding, recent improvements of ion track technology open new doors for fast growing applications in niche markets. This paper reviews some of these Hi-Tec applications in different fields such as in healthcare (oncology, drug control release combined to implant and artificial organs etc.), energy (fuel cells and batteries etc.), water de-contamination and electronics (OLED etc.).

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

An improved multi-domain convolution tracking algorithm

NASA Astrophysics Data System (ADS)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

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

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.

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.

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.

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.

Extended applications of track irregularity probabilistic model and vehicle-slab track coupled model on dynamics of railway systems

NASA Astrophysics Data System (ADS)

Xu, Lei; Zhai, Wanming; Gao, Jianmin

2017-11-01

Track irregularities are inevitably in a process of stochastic evolution due to the uncertainty and continuity of wheel-rail interactions. For depicting the dynamic behaviours of vehicle-track coupling system caused by track random irregularities thoroughly, it is a necessity to develop a track irregularity probabilistic model to simulate rail surface irregularities with ergodic properties on amplitudes, wavelengths and probabilities, and to build a three-dimensional vehicle-track coupled model by properly considering the wheel-rail nonlinear contact mechanisms. In the present study, the vehicle-track coupled model is programmed by combining finite element method with wheel-rail coupling model firstly. Then, in light of the capability of power spectral density (PSD) in characterising amplitudes and wavelengths of stationary random signals, a track irregularity probabilistic model is presented to reveal and simulate the whole characteristics of track irregularity PSD. Finally, extended applications from three aspects, that is, extreme analysis, reliability analysis and response relationships between dynamic indices, are conducted to the evaluation and application of the proposed models.

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

PubMed

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

2018-01-01

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

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

PubMed

Lu, Xiaodong; Xie, Yuting; Zhou, Jun

2018-05-27

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

Precise Head Tracking in Hearing Applications

NASA Astrophysics Data System (ADS)

Helle, A. M.; Pilinski, J.; Luhmann, T.

2015-05-01

The paper gives an overview about two research projects, both dealing with optical head tracking in hearing applications. As part of the project "Development of a real-time low-cost tracking system for medical and audiological problems (ELCoT)" a cost-effective single camera 3D tracking system has been developed which enables the detection of arm and head movements of human patients. Amongst others, the measuring system is designed for a new hearing test (based on the "Mainzer Kindertisch"), which analyzes the directional hearing capabilities of children in cooperation with the research project ERKI (Evaluation of acoustic sound source localization for children). As part of the research project framework "Hearing in everyday life (HALLO)" a stereo tracking system is being used for analyzing the head movement of human patients during complex acoustic events. Together with the consideration of biosignals like skin conductance the speech comprehension and listening effort of persons with reduced hearing ability, especially in situations with background noise, is evaluated. For both projects the system design, accuracy aspects and results of practical tests are discussed.

Towards smart mobility in urban spaces: Bus tracking and information application

NASA Astrophysics Data System (ADS)

Yue, Wong Seng; Chye, Koh Keng; Hoy, Cheong Wan

2017-10-01

Smart city can be defined as an urban space with complete and advanced infrastructure, intelligent networks and platforms, with millions of sensors among which people themselves and their mobile devices. Urban mobility is one of the global smart city project which offers traffic management in real-time, management of passenger transport means, tracking applications and logistics, car sharing services, car park management and more smart mobility services. Due to the frustrated waiting time for the arrival of buses and the difficulty of accessing shuttle bus-related information in a one-stop centre, bus tracking and information application (BTA) is one the proposed solutions to solve the traffic problems in urban spaces. This paper is aimed to design and develop a bus tracking and information application in a selected city in Selangor state, Malaysia. Next, this application also provides an alternative to design public transport tracking and information application for the urban places in Malaysia. Furthermore, the application also provides a smart solution for the management of public infrastructures and urban facilities in Malaysia in future.

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.

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

Development of feedforward control in a dynamic manual tracking task.

PubMed

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

2008-01-01

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

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

Adaptive radiation therapy for postprostatectomy patients using real-time electromagnetic target motion tracking during external beam radiation therapy.

PubMed

Zhu, Mingyao; Bharat, Shyam; Michalski, Jeff M; Gay, Hiram A; Hou, Wei-Hsien; Parikh, Parag J

2013-03-15

Using real-time electromagnetic (EM) transponder tracking data recorded by the Calypso 4D Localization System, we report inter- and intrafractional target motion of the prostate bed, describe a strategy to evaluate treatment adequacy in postprostatectomy patients receiving intensity modulated radiation therapy (IMRT), and propose an adaptive workflow. Tracking data recorded by Calypso EM transponders was analyzed for postprostatectomy patients that underwent step-and-shoot IMRT. Rigid target motion parameters during beam delivery were calculated from recorded transponder positions in 16 patients with rigid transponder geometry. The delivered doses to the clinical target volume (CTV) were estimated from the planned dose matrix and the target motion for the first 3, 5, 10, and all fractions. Treatment adequacy was determined by comparing the delivered minimum dose (Dmin) with the planned Dmin to the CTV. Treatments were considered adequate if the delivered CTV Dmin is at least 95% of the planned CTV Dmin. Translational target motion was minimal for all 16 patients (mean: 0.02 cm; range: -0.12 cm to 0.07 cm). Rotational motion was patient-specific, and maximum pitch, yaw, and roll were 12.2, 4.1, and 10.5°, respectively. We observed inadequate treatments in 5 patients. In these treatments, we observed greater target rotations along with large distances between the CTV centroid and transponder centroid. The treatment adequacy from the initial 10 fractions successfully predicted the overall adequacy in 4 of 5 inadequate treatments and 10 of 11 adequate treatments. Target rotational motion could cause underdosage to partial volume of the postprostatectomy targets. Our adaptive treatment strategy is applicable to post-prostatectomy patients receiving IMRT to evaluate and improve radiation therapy delivery. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

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

PubMed Central

2018-01-01

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

Neural network fusion capabilities for efficient implementation of tracking algorithms

NASA Astrophysics Data System (ADS)

Sundareshan, Malur K.; Amoozegar, Farid

1997-03-01

The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.

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.

DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

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

Villeneuve, Pierre V.

2013-02-28

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

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

H(infinity)/H(2)/Kalman filtering of linear dynamical systems via variational techniques with applications to target tracking

NASA Astrophysics Data System (ADS)

Rawicz, Paul Lawrence

In this thesis, the similarities between the structure of the H infinity, H2, and Kalman filters are examined. The filters used in this examination have been derived through duality to the full information controller. In addition, a direct variation of parameters derivation of the Hinfinity filter is presented for both continuous and discrete time (staler case). Direct and controller dual derivations using differential games exist in the literature and also employ variational techniques. Using a variational, rather than a differential games, viewpoint has resulted in a simple relationship between the Riccati equations that arise from the derivation and the results of the Bounded Real Lemma. This same relation has previously been found in the literature and used to relate the Riccati inequality for linear systems to the Hamilton Jacobi inequality for nonlinear systems when implementing the Hinfinity controller. The Hinfinity, H2, and Kalman filters are applied to the two-state target tracking problem. In continuous time, closed form analytic expressions for the trackers and their performance are determined. To evaluate the trackers using a neutral, realistic, criterion, the probability of target escape is developed. That is, the probability that the target position error will be such that the target is outside the radar beam width resulting in a loss of measurement. In discrete time, a numerical example, using the probability of target escape, is presented to illustrate the differences in tracker performance.

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.

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.

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

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

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.

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.

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).

An RFID-based luggage and passenger tracking system for airport security control applications

NASA Astrophysics Data System (ADS)

Vastianos, George E.; Kyriazanos, Dimitris M.; Kountouriotis, Vassilios I.; Thomopoulos, Stelios C. A.

2014-06-01

Market analysis studies of recent years have shown a steady and significant increase in the usage of RFID technology. Key factors for this growth were the decreased costs of passive RFIDs and their improved performance compared to the other identification technologies. Besides the benefits of RFID technologies into the supply chains, warehousing, traditional inventory and asset management applications, RFID has proven itself worth exploiting on experimental, as well as on commercial level in other sectors, such as healthcare, transport and security. In security sector, airport security is one of the biggest challenges. Airports are extremely busy public places and thus prime targets for terrorism, with aircraft, passengers, crew and airport infrastructure all subject to terrorist attacks. Inside this labyrinth of security challenges, the long range detection capability of the UHF passive RFID technology can be turned into a very important tracking tool that may outperform all the limitations of the barcode tracking inside the current airport security control chain. The Integrated Systems Lab of NCSR Demokritos has developed an RFID based Luggage and Passenger tracking system within the TASS (FP7-SEC-2010-241905) EU research project. This paper describes application scenarios of the system categorized according to the structured nature of the environment, the system architecture and presents evaluation results extracted from measurements with a group of different massive production GEN2 UHF RFID tags that are widely available in the world market.

Video Guidance Sensors Using Remotely Activated Targets

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

LabVIEW application for motion tracking using USB camera

NASA Astrophysics Data System (ADS)

Rob, R.; Tirian, G. O.; Panoiu, M.

2017-05-01

The technical state of the contact line and also the additional equipment in electric rail transport is very important for realizing the repairing and maintenance of the contact line. During its functioning, the pantograph motion must stay in standard limits. Present paper proposes a LabVIEW application which is able to track in real time the motion of a laboratory pantograph and also to acquire the tracking images. An USB webcam connected to a computer acquires the desired images. The laboratory pantograph contains an automatic system which simulates the real motion. The tracking parameters are the horizontally motion (zigzag) and the vertically motion which can be studied in separate diagrams. The LabVIEW application requires appropriate tool-kits for vision development. Therefore the paper describes the subroutines that are especially programmed for real-time image acquisition and also for data processing.

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

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.

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.

The application of measurement techniques to track flutter testing

NASA Technical Reports Server (NTRS)

Roglin, H. R.

1975-01-01

The application is discussed of measurement techniques to captive flight flutter tests at the Supersonic Naval Ordnance Research Track (SNORT), U. S. Naval Ordnance Test Station, China Lake, California. The high-speed track, by its ability to prove the validity of design and to accurately determine the actual margin of safety, offers a unique method of flutter testing for the aircraft design engineer.

A Mobile GPS Application: Mosque Tracking with Prayer Time Synchronization

NASA Astrophysics Data System (ADS)

Hashim, Rathiah; Ikhmatiar, Mohammad Sibghotulloh; Surip, Miswan; Karmin, Masiri; Herawan, Tutut

Global Positioning System (GPS) is a popular technology applied in many areas and embedded in many devices, facilitating end-users to navigate effectively to user's intended destination via the best calculated route. The ability of GPS to track precisely according to coordinates of specific locations can be utilized to assist a Muslim traveler visiting or passing an unfamiliar place to find the nearest mosque in order to perform his prayer. However, not many techniques have been proposed for Mosque tracking. This paper presents the development of GPS technology in tracking the nearest mosque using mobile application software embedded with the prayer time's synchronization system on a mobile application. The prototype GPS system developed has been successfully incorporated with a map and several mosque locations.

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.

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

PubMed Central

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

2017-01-01

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

Leveraging Information Technology. Track VII: Outstanding Applications.

ERIC Educational Resources Information Center

CAUSE, Boulder, CO.

Eight papers from the 1987 CAUSE conference's Track VII, Outstanding Applications, are presented. They include: "Image Databases in the University" (Reid Kaplan and Gordon Mathieson); "Using Information Technology for Travel Management at the University of Michigan" (Robert E. Russell and John C. Hufziger); "On-Line Access…

Designing Tracking Software for Image-Guided Surgery Applications: IGSTK Experience

PubMed Central

Enquobahrie, Andinet; Gobbi, David; Turek, Matt; Cheng, Patrick; Yaniv, Ziv; Lindseth, Frank; Cleary, Kevin

2009-01-01

Objective Many image-guided surgery applications require tracking devices as part of their core functionality. The Image-Guided Surgery Toolkit (IGSTK) was designed and developed to interface tracking devices with software applications incorporating medical images. Methods IGSTK was designed as an open source C++ library that provides the basic components needed for fast prototyping and development of image-guided surgery applications. This library follows a component-based architecture with several components designed for specific sets of image-guided surgery functions. At the core of the toolkit is the tracker component that handles communication between a control computer and navigation device to gather pose measurements of surgical instruments present in the surgical scene. The representations of the tracked instruments are superimposed on anatomical images to provide visual feedback to the clinician during surgical procedures. Results The initial version of the IGSTK toolkit has been released in the public domain and several trackers are supported. The toolkit and related information are available at www.igstk.org. Conclusion With the increased popularity of minimally invasive procedures in health care, several tracking devices have been developed for medical applications. Designing and implementing high-quality and safe software to handle these different types of trackers in a common framework is a challenging task. It requires establishing key software design principles that emphasize abstraction, extensibility, reusability, fault-tolerance, and portability. IGSTK is an open source library that satisfies these needs for the image-guided surgery community. PMID:20037671

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

Robust object tracking techniques for vision-based 3D motion analysis applications

NASA Astrophysics Data System (ADS)

Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

2016-04-01

Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

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.

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.

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

An Application of Computerized Axial Tomography (CAT) Technology to Mass Raid Tracking

DTIC Science & Technology

1989-08-01

ESD-TR-89-305 MTR-10542 An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking By John K. Barr August 1989...NO 11. TITLE (Include Security Classification) An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking 12...by block number) Computerized Axial Tomography ( CAT ) Scanner Electronic Support Measures (ESM) Fusion (continued) 19. ABSTRACT (Continue on

Ultra-Wideband Tracking System Design for Relative Navigation

NASA Technical Reports Server (NTRS)

Ni, Jianjun David; Arndt, Dickey; Bgo, Phong; Dekome, Kent; Dusl, John

2011-01-01

This presentation briefly discusses a design effort for a prototype ultra-wideband (UWB) time-difference-of-arrival (TDOA) tracking system that is currently under development at NASA Johnson Space Center (JSC). The system is being designed for use in localization and navigation of a rover in a GPS deprived environment for surface missions. In one application enabled by the UWB tracking, a robotic vehicle carrying equipments can autonomously follow a crewed rover from work site to work site such that resources can be carried from one landing mission to the next thereby saving up-mass. The UWB Systems Group at JSC has developed a UWB TDOA High Resolution Proximity Tracking System which can achieve sub-inch tracking accuracy of a target within the radius of the tracking baseline [1]. By extending the tracking capability beyond the radius of the tracking baseline, a tracking system is being designed to enable relative navigation between two vehicles for surface missions. A prototype UWB TDOA tracking system has been designed, implemented, tested, and proven feasible for relative navigation of robotic vehicles. Future work includes testing the system with the application code to increase the tracking update rate and evaluating the linear tracking baseline to improve the flexibility of antenna mounting on the following vehicle.

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.

Tracking motions from satellite water vapor imagery: Quantitative applications to hurricane track forecasting

NASA Technical Reports Server (NTRS)

Velden, Christopher; Nieman, Steve; Aberson, Sim; Franklin, James

1993-01-01

Water vapor imagery from GOES satellites has been available for over a decade. These data are used extensively, mainly in a qualitative mode, by forecasters in the United States (Weldon and Holmes, 1991). Some attempts have been made at quantifying the data by tracking features in time sequences of the imagery (Stewart et al., 1985; Hayden and Stewart, 1987). For a variety of reasons, applications of this approach have produced marginal results (Velden, 1990). Recently, METEOSAT-3 (M-3) was repositioned at 50W by the European Space Agency, in order to provide complete coverage of the Atlantic Ocean. Data from this satellite are being transmitted to the U.S. for operational use. Compared with the GOES satellite, the M-3 has a superior resolution and signal-to-noise ratio in its water vapor channel, which translates into improved automated tracking capabilities. During a period in 1992 which included the Atlantic hurricane season, water vapor tracking algorithms were applied to the M-3 data in order to evaluate the coverage, accuracy and model impact of the derived vectors. Data sets were produced during several tropical cyclone cases, including Hurricane Andrew. In this paper, the M-3 water vapor wind sets are assessed, and their impact on a hurricane track forecast model is examined.

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

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

Nakamura, M; Matsuo, Y; Mukumoto, N

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

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.

Energy efficient sensor scheduling with a mobile sink node for the target tracking application.

PubMed

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance.

Energy Efficient Sensor Scheduling with a Mobile Sink Node for the Target Tracking Application

PubMed Central

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance PMID:22399934

Detection and tracking of human targets in indoor and urban environments using through-the-wall radar sensors

NASA Astrophysics Data System (ADS)

Radzicki, Vincent R.; Boutte, David; Taylor, Paul; Lee, Hua

2017-05-01

Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.

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.

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.

Integrated Ultra-Wideband Tracking and Carbon Dioxide Sensing System Design for International Space Station Applications

NASA Technical Reports Server (NTRS)

Ni, Jianjun (David); Hafermalz, David; Dusl, John; Barton, Rick; Wagner, Ray; Ngo, Phong

2015-01-01

A three-dimensional (3D) Ultra-Wideband (UWB) Time-of-Arrival (TOA) tracking system has been studied at NASA Johnson Space Center (JSC) to provide the tracking capability inside the International Space Station (ISS) modules for various applications. One of applications is to locate and report the location where crew experienced possible high level of carbon-dioxide (CO2) and felt upset. Recent findings indicate that frequent, short-term crew exposure to elevated CO2 levels combined with other physiological impacts of microgravity may lead to a number of detrimental effects, including loss of vision. To evaluate the risks associated with transient elevated CO2 levels and design effective countermeasures, doctors must have access to frequent CO2 measurements in the immediate vicinity of individual crew members along with simultaneous measurements of their location in the space environment. To achieve this goal, a small, low-power, wearable system that integrates an accurate CO2 sensor with an ultra-wideband (UWB) radio capable of real-time location estimation and data communication is proposed. This system would be worn by crew members or mounted on a free-flyer and would automatically gather and transmit sampled sensor data tagged with real-time, high-resolution location information. Under the current proposed effort, a breadboard prototype of such a system has been developed. Although the initial effort is targeted to CO2 monitoring, the concept is applicable to other types of sensors. For the initial effort, a micro-controller is leveraged to integrate a low-power CO2 sensor with a commercially available UWB radio system with ranging capability. In order to accurately locate those places in a multipath intensive environment like ISS modules, it requires a robust real-time location system (RTLS) which can provide the required accuracy and update rate. A 3D UWB TOA tracking system with two-way ranging has been proposed and studied. The designed system will be tested

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

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

PubMed

Quesada, Luis; León, Alejandro J

2012-10-01

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

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

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

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.

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

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.

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

UWB Tracking Software Development

NASA Technical Reports Server (NTRS)

Gross, Julia; Arndt, Dickey; Ngo, Phong; Phan, Chau; Dusl, John; Ni, Jianjun; Rafford, Melinda

2006-01-01

An Ultra-Wideband (UWB) two-cluster Angle of Arrival (AOA) tracking prototype system is currently being developed and tested at NASA Johnson Space Center for space exploration applications. This talk discusses the software development efforts for this UWB two-cluster AOA tracking system. The role the software plays in this system is to take waveform data from two UWB radio receivers as an input, feed this input into an AOA tracking algorithm, and generate the target position as an output. The architecture of the software (Input/Output Interface and Algorithm Core) will be introduced in this talk. The development of this software has three phases. In Phase I, the software is mostly Matlab driven and calls C++ socket functions to provide the communication links to the radios. This is beneficial in the early stage when it is necessary to frequently test changes in the algorithm. Phase II of the development is to have the software mostly C++ driven and call a Matlab function for the AOA tracking algorithm. This is beneficial in order to send the tracking results to other systems and also to improve the tracking update rate of the system. The third phase is part of future work and is to have the software completely C++ driven with a graphics user interface. This software design enables the fine resolution tracking of the UWB two-cluster AOA tracking system.

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

The Extended-Image Tracking Technique Based on the Maximum Likelihood Estimation

NASA Technical Reports Server (NTRS)

Tsou, Haiping; Yan, Tsun-Yee

2000-01-01

This paper describes an extended-image tracking technique based on the maximum likelihood estimation. The target image is assume to have a known profile covering more than one element of a focal plane detector array. It is assumed that the relative position between the imager and the target is changing with time and the received target image has each of its pixels disturbed by an independent additive white Gaussian noise. When a rotation-invariant movement between imager and target is considered, the maximum likelihood based image tracking technique described in this paper is a closed-loop structure capable of providing iterative update of the movement estimate by calculating the loop feedback signals from a weighted correlation between the currently received target image and the previously estimated reference image in the transform domain. The movement estimate is then used to direct the imager to closely follow the moving target. This image tracking technique has many potential applications, including free-space optical communications and astronomy where accurate and stabilized optical pointing is essential.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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.

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

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadrasjavan, F.

2016-06-01

There is an increasingly large number of applications for Unmanned Aerial Vehicles (UAVs) from monitoring, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using an extended Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors, Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. The results of this study compared with code-based ordinary GPS, indicate that RTK observation with proposed method shows more than 10 times improvement of accuracy in target geolocation.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2009-08-01

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

A 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.

Evaluation of pyrolysis and arc tracking on candidate wire insulation designs for space applications

NASA Astrophysics Data System (ADS)

Stueber, Thomas J.; Hammoud, Ahmad; Stavnes, Mark W.; Hrovat, Kenneth

1994-05-01

Polyimide wire insulation has been found to be vulnerable to pyrolization and arc tracking due to momentary short circuit arcing events. This report compares arc tracking susceptibility of candidate insulation configurations for space wiring applications. The insulation types studied in this report were gauge 20 (0.81 mm dia.) hybrid wiring constructions using polyimide, tetrafluoroethylene (TFE), cross-linked ethylene tetrafluoroethylene (XL-ETFE) and/or polytetrafluoroethylene (PTFE) insulations. These constructions were manufactured according to military wiring standards for aerospace applications. Arc track testing was conducted under DC bias and vacuum (10(exp -6) torr). The tests were conducted to compare the various insulation constructions in terms of their resistance to arc tracking restrike. The results of the tests are presented.

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

PubMed Central

Xue, Ming; Yang, Hua; Zheng, Shibao; Zhou, Yi; Yu, Zhenghua

2014-01-01

To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks. PMID:24549252

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

Graphical Environment Tools for Application to Gamma-Ray Energy Tracking Arrays

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

Todd, Richard A.; Radford, David C.

2013-12-30

Highly segmented, position-sensitive germanium detector systems are being developed for nuclear physics research where traditional electronic signal processing with mixed analog and digital function blocks would be enormously complex and costly. Future systems will be constructed using pipelined processing of high-speed digitized signals as is done in the telecommunications industry. Techniques which provide rapid algorithm and system development for future systems are desirable. This project has used digital signal processing concepts and existing graphical system design tools to develop a set of re-usable modular functions and libraries targeted for the nuclear physics community. Researchers working with complex nuclear detector arraysmore » such as the Gamma-Ray Energy Tracking Array (GRETA) have been able to construct advanced data processing algorithms for implementation in field programmable gate arrays (FPGAs) through application of these library functions using intuitive graphical interfaces.« less

A multispectral automatic target recognition application for maritime surveillance, search, and rescue

NASA Astrophysics Data System (ADS)

Schoonmaker, Jon; Reed, Scott; Podobna, Yuliya; Vazquez, Jose; Boucher, Cynthia

2010-04-01

Due to increased security concerns, the commitment to monitor and maintain security in the maritime environment is increasingly a priority. A country's coast is the most vulnerable area for the incursion of illegal immigrants, terrorists and contraband. This work illustrates the ability of a low-cost, light-weight, multi-spectral, multi-channel imaging system to handle the environment and see under difficult marine conditions. The system and its implemented detecting and tracking technologies should be organic to the maritime homeland security community for search and rescue, fisheries, defense, and law enforcement. It is tailored for airborne and ship based platforms to detect, track and monitor suspected objects (such as semi-submerged targets like marine mammals, vessels in distress, and drug smugglers). In this system, automated detection and tracking technology is used to detect, classify and localize potential threats or objects of interest within the imagery provided by the multi-spectral system. These algorithms process the sensor data in real time, thereby providing immediate feedback when features of interest have been detected. A supervised detection system based on Haar features and Cascade Classifiers is presented and results are provided on real data. The system is shown to be extendable and reusable for a variety of different applications.

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

Pose tracking for augmented reality applications in outdoor archaeological sites

NASA Astrophysics Data System (ADS)

Younes, Georges; Asmar, Daniel; Elhajj, Imad; Al-Harithy, Howayda

2017-01-01

In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects of the world's cultural heritage. Of particular importance is the digitization of outdoor archaeological sites. In the spirit of valorization of this digital information, many groups have developed virtual or augmented reality (AR) computer applications themed around a particular archaeological object. The problem of pose tracking in outdoor AR applications is addressed. Different positional systems are analyzed, resulting in the selection of a monocular camera-based user tracker. The limitations that challenge this technique from map generation, scale, anchoring, to lighting conditions are analyzed and systematically addressed. Finally, as a case study, our pose tracking system is implemented within an AR experience in the Byblos Roman theater in Lebanon.

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

Protecting the Privacy of Individuals in Terrorist Tracking Applications

DTIC Science & Technology

2005-04-01

THE PRIVACY OF INDIVIDUALS IN TERRORIST TRACKING APPLICATIONS 6. AUTHOR(S) Teresa Lunt, Paul Aoki, Dirk Balfanz , Glenn Durfee, Philippe Golle...in Data Mining and Knowledge Discovery. 3) Brent Waters, Dirk Balfanz , Glenn Durfee, and Diana Smetters. Building an encrypted and searchable audit

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.

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

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

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

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

Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity

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

Li, Yulan; Huang, Zhenyu; Zhou, Ning

2012-05-01

Ensemble Kalman Filter (EnKF) is proposed to track dynamic states of generators. The algorithm of EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF can effectively track generator dynamic states using disturbance data.

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.

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

DTIC Science & Technology

2010-01-01

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

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.

Managing Information Technology: Facing the Issues. Track VII: Applications and Technology Issues.

ERIC Educational Resources Information Center

CAUSE, Boulder, CO.

Eight papers making up Track VII of the 1989 conference of the Professional Association for the Management of Information Technology in Higher Education (known as CAUSE, an acronym of the association's former name) are presented in this document. The focus of Track VII is on applications and technology issues, and the papers include: "The…

Object acquisition and tracking for space-based surveillance

NASA Astrophysics Data System (ADS)

1991-11-01

This report presents the results of research carried out by Space Computer Corporation under the U.S. government's Small Business Innovation Research (SBIR) Program. The work was sponsored by the Strategic Defense Initiative Organization and managed by the Office of Naval Research under Contracts N00014-87-C-0801 (Phase 1) and N00014-89-C-0015 (Phase 2). The basic purpose of this research was to develop and demonstrate a new approach to the detection of, and initiation of track on, moving targets using data from a passive infrared or visual sensor. This approach differs in very significant ways from the traditional approach of dividing the required processing into time dependent, object dependent, and data dependent processing stages. In that approach individual targets are first detected in individual image frames, and the detections are then assembled into tracks. That requires that the signal to noise ratio in each image frame be sufficient for fairly reliable target detection. In contrast, our approach bases detection of targets on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect, and can lead to a significant reduction in total system cost. For example, it can allow greater detection range for a single sensor, or it can allow the use of smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.

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.

Eye Tracking Dysfunction in Schizophrenia: Characterization and Pathophysiology

PubMed Central

Sereno, Anne B.; Gooding, Diane C.; O’Driscoll, Gilllian A.

2011-01-01

Eye tracking dysfunction (ETD) is one of the most widely replicated behavioral deficits in schizophrenia and is over-represented in clinically unaffected first-degree relatives of schizophrenia patients. Here, we provide an overview of research relevant to the characterization and pathophysiology of this impairment. Deficits are most robust in the maintenance phase of pursuit, particularly during the tracking of predictable target movement. Impairments are also found in pursuit initiation and correlate with performance on tests of motion processing, implicating early sensory processing of motion signals. Taken together, the evidence suggests that ETD involves higher-order structures, including the frontal eye fields, which adjust the gain of the pursuit response to visual and anticipated target movement, as well as early parts of the pursuit pathway, including motion areas (the middle temporal area and the adjacent medial superior temporal area). Broader application of localizing behavioral paradigms in patient and family studies would be advantageous for refining the eye tracking phenotype for genetic studies. PMID:21312405

Technology survey on video face tracking

NASA Astrophysics Data System (ADS)

Zhang, Tong; Gomes, Herman Martins

2014-03-01

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

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.

Secure FAST: Security Enhancement in the NATO Time Sensitive Targeting Tool

DTIC Science & Technology

2010-11-01

designed to aid in the tracking and prosecuting of Time Sensitive Targets. The FAST tool provides user level authentication and authorisation in terms...level authentication and authorisation in terms of security. It uses operating system level security but does not provide application level security for...and collaboration tool, designed to aid in the tracking and prosecuting of Time Sensitive Targets. The FAST tool provides user level authentication and

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.

Discrimination Power Control for Adaptive Target Tracking Applications

DTIC Science & Technology

2008-07-01

represented by the Minister of National Defence, 2008 c© Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense...classification. Résumé Le travail présenté dans ce rapport porte sur le problème de la capacité discriminatoire dans des applications de pistage de cibles...objectifs d’une mission. La stratégie de contrôle est basée sur deux boucles imbriquées. La boucle externe utilise des techniques de regroupement de

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.

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

An Empirical Human Controller Model for Preview Tracking Tasks.

PubMed

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

2016-11-01

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

Envisioning the Future of Aquatic Animal Tracking: Technology, Science, and Application

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

Lennox, Robert J.; Aarestrup, Kim; Cooke, Steven J.

Electronic tags have proven to be extremely useful for broadening our understanding of aquatic animals by answering diverse questions about their behaviours, physiologies, and life histories fundamental to ecology. Simultaneously, many applied conservation and management efforts are informed by animals tagged with electronic tags. In spite of the many advances in tracking software and hardware, an uncertain future in the world’s aquatic ecosystems portends great challenges for science. Aquatic animal tracking with electronic tags represents both the present and future of integrative biology and ecology in aquatic ecosystems. Here we identify what we regard as the future of aquatic animalmore » tracking in a horizon scanning exercise. We submit that the future of aquatic animal tracking will include opportunities for multi-platform tracking systems for simultaneously monitoring position, activity, physiology, and microhabitat of animals, improved data collection and accessibility with new infrastructure (e.g. tags, receivers) and cyberinfrastructure, and integrated tagging information with animal traits derived from biopsy during tagging. We discuss parallel needs and opportunities in areas related to the application of animal tracking in the future such as knowledge mobilization and governance.« less

Mining Software Usage with the Automatic Library Tracking Database (ALTD)

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

Hadri, Bilel; Fahey, Mark R

2013-01-01

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batchmore » job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.« less

Track structure of protons and other light ions in liquid water: applications of the LIonTrack code at the nanometer scale.

PubMed

Bäckström, G; Galassi, M E; Tilly, N; Ahnesjö, A; Fernández-Varea, J M

2013-06-01

The LIonTrack (Light Ion Track) Monte Carlo (MC) code for the simulation of H(+), He(2+), and other light ions in liquid water is presented together with the results of a novel investigation of energy-deposition site properties from single ion tracks. The continuum distorted-wave formalism with the eikonal initial state approximation (CDW-EIS) is employed to generate the initial energy and angle of the electrons emitted in ionizing collisions of the ions with H2O molecules. The model of Dingfelder et al. ["Electron inelastic-scattering cross sections in liquid water," Radiat. Phys. Chem. 53, 1-18 (1998); "Comparisons of calculations with PARTRAC and NOREC: Transport of electrons in liquid water," Radiat. Res. 169, 584-594 (2008)] is linked to the general-purpose MC code PENELOPE/penEasy to simulate the inelastic interactions of the secondary electrons in liquid water. In this way, the extended PENELOPE/penEasy code may provide an improved description of the 3D distribution of energy deposits (EDs), making it suitable for applications at the micrometer and nanometer scales. Single-ionization cross sections calculated with the ab initio CDW-EIS formalism are compared to available experimental values, some of them reported very recently, and the theoretical electronic stopping powers are benchmarked against those recommended by the ICRU. The authors also analyze distinct aspects of the spatial patterns of EDs, such as the frequency of nearest-neighbor distances for various radiation qualities, and the variation of the mean specific energy imparted in nanoscopic targets located around the track. For 1 MeV/u particles, the C(6+) ions generate about 15 times more clusters of six EDs within an ED distance of 3 nm than H(+). On average clusters of two to three EDs for 1 MeV/u H(+) and clusters of four to five EDs for 1 MeV/u C(6+) could be expected for a modeling double strand break distance of 3.4 nm.

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...

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

Model tracking system for low-level radioactive waste disposal facilities: License application interrogatories and responses

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

Benbennick, M.E.; Broton, M.S.; Fuoto, J.S.

This report describes a model tracking system for a low-level radioactive waste (LLW) disposal facility license application. In particular, the model tracks interrogatories (questions, requests for information, comments) and responses. A set of requirements and desired features for the model tracking system was developed, including required structure and computer screens. Nine tracking systems were then reviewed against the model system requirements and only two were found to meet all requirements. Using Kepner-Tregoe decision analysis, a model tracking system was selected.

Cooperative Robots to Observe Moving Targets: Review.

PubMed

Khan, Asif; Rinner, Bernhard; Cavallaro, Andrea

2018-01-01

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

Use of an inertial navigation system for accurate track recovery and coastal oceanographic measurements

NASA Technical Reports Server (NTRS)

Oliver, B. M.; Gower, J. F. R.

1977-01-01

A data acquisition system using a Litton LTN-51 inertial navigation unit (INU) was tested and used for aircraft track recovery and for location and tracking from the air of targets at sea. The characteristic position drift of the INU is compensated for by sighting landmarks of accurately known position at discrete time intervals using a visual sighting system in the transparent nose of the Beechcraft 18 aircraft used. For an aircraft altitude of about 300 m, theoretical and experimental tests indicate that calculated aircraft and/or target positions obtained from the interpolated INU drift curve will be accurate to within 10 m for landmarks spaced approximately every 15 minutes in time. For applications in coastal oceanography, such as surface current mapping by tracking artificial targets, the system allows a broad area to be covered without use of high altitude photography and its attendant needs for large targets and clear weather.

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.

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.

UWB Tracking System Design for Lunar/Mars Exploration

NASA Technical Reports Server (NTRS)

Ni, Jianjun; Arndt, Dickey; Ngo, Phong; Phan, Chau; Gross, Julia

2006-01-01

This paper describes a design effort for a prototype ultra-wideband (UWB) tracking system that is currently under development at NASA Johnson Space Center (JSC). The system is being studied for use in tracking of lunar/Mars rovers during early exploration missions when satellite navigation systems are not available. The UWB technology is exploited to implement the tracking system due to its properties such as high data rate, fine time resolution, low power spectral density, and multipath immunity. A two-cluster prototype design using commercially available UWB products is proposed to implement the Angle Of Arrival (AOA) tracking methodology in this research effort. An AOA technique using the Time Difference Of Arrival (TDOA) information is utilized for location estimation in the prototype system, not only to exploit the precise time resolution possible with UWB signals, but also to eliminate the need for synchronization between the transmitter and the receiver. After the UWB radio at each cluster is used to obtain the TDOA estimates from the UWB signal sent from the target, the TDOA data is converted to AOA data to find the angle of arrival, assuming this is a far field application. Since the distance between two clusters is known, the target position is computed by a simple triangulation. Simulations show that the average tracking error at a range of 610 meters is 2.7595 meters, less than 0.5% of the tracking range. Outdoor tests to track the SCOUT vehicle (The Science Crew Operations and Utility Testbed) near the Meteor Crater, Flagstaff, Arizona were performed on September 12-13, 2005. The tracking performance was obtained with less than 1% tracking error at ranges up to 2000 feet. No RF interference with on-board GPS, video, voice and telemetry systems was detected. Outdoor tests demonstrated the UWB tracking capability.

Information Technology: Making It All Fit. Track VI: Outstanding Applications.

ERIC Educational Resources Information Center

CAUSE, Boulder, CO.

Seven papers from the 1988 CAUSE conference's Track VI, Outstanding Applications, are presented. They include: "Designing DB2 Data Bases Using Entity-Relationship Modeling: A Case Study--The LSU System Worker's Compensation Project" (Cynthia M. Hadden and Sara G. Zimmerman); "Integrating Information Technology: Prerequisites for…

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.

Medical Imaging for the Tracking of Micromotors.

PubMed

Vilela, Diana; Cossío, Unai; Parmar, Jemish; Martínez-Villacorta, Angel M; Gómez-Vallejo, Vanessa; Llop, Jordi; Sánchez, Samuel

2018-02-27

Micro/nanomotors are useful tools for several biomedical applications, including targeted drug delivery and minimally invasive microsurgeries. However, major challenges such as in vivo imaging need to be addressed before they can be safely applied on a living body. Here, we show that positron emission tomography (PET), a molecular imaging technique widely used in medical imaging, can also be used to track a large population of tubular Au/PEDOT/Pt micromotors. Chemisorption of an iodine isotope onto the micromotor's Au surface rendered them detectable by PET, and we could track their movements in a tubular phantom over time frames of up to 15 min. In a second set of experiments, micromotors and the bubbles released during self-propulsion were optically tracked by video imaging and bright-field microscopy. The results from direct optical tracking agreed with those from PET tracking, demonstrating that PET is a suitable technique for the imaging of large populations of active micromotors in opaque environments, thus opening opportunities for the use of this mature imaging technology for the in vivo localization of artificial swimmers.

Multi-Target Camera Tracking, Hand-off and Display LDRD 158819 Final Report

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

Anderson, Robert J.

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn’t lead to more alarms, moremore » monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identify individual moving targets from the background imagery, and then display the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.« less

Multi-target camera tracking, hand-off and display LDRD 158819 final report

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

Anderson, Robert J.

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn't lead to more alarms, moremore » monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identifies individual moving targets from the background imagery, and then displays the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.« less

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

PubMed

Zelinsky, Gregory J; Todor, Andrei

2010-12-29

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

Tracking strategies for laser ranging to multiple satellite targets

NASA Technical Reports Server (NTRS)

Robbins, J. W.; Smith, D. E.; Kolenkiewicz, R.

1994-01-01

By the middle of the decade, several new Laser Geodynamic Satellites will be launched to join the current constellation comprised of the laser geodynamic satellite (LAGEOS) (US), Starlette (France), Ajisai (Japan), and Etalon I and II (USSR). The satellites to be launched, LAGEOS II and III (US & Italy), and Stella (France), will be injected into orbits that differ from the existing constellation so that geodetic and gravimetric quantities are sampled to enhance their resolution and accuracy. An examination of various possible tracking strategies adopted by the network of laser tracking stations has revealed that the recovery of precise geodetic parameters can be obtained over shorter intervals than is currently obtainable with the present constellation of satellites. This is particularly important in the planning of mobile laser tracking operations, given a network of permanently operating tracking sites. Through simulations, it is shown that laser tracking of certain satellite passes, pre-selected to provide optimal sky-coverage, provides the means to acquire a sufficient amount of data to allow the recovery of 1 cm station positions.

SIFT-based dense pixel tracking on 0.35 T cine-MR images acquired during image-guided radiation therapy with application to gating optimization

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

Mazur, Thomas R., E-mail: tmazur@radonc.wustl.edu, E-mail: hli@radonc.wustl.edu; Fischer-Valuck, Benjamin W.; Wang, Yuhe

position and a tolerable margin about this position—derived from a probability density function that is constructed using tracking results obtained just prior to treatment. Results: The feasibility of applying the matching objective for SIFT descriptors toward pixel-by-pixel tracking on cine-MR acquisitions was first retrospectively demonstrated for 19 treatments (spanning various sites). Both with and without motion correction based on harmonic analysis, sub-pixel MTEs were obtained. A mean DSC value spanning all patients of 0.916 ± 0.001 was obtained without motion correction, with DSC values exceeding 0.85 for all patients considered. While most patients show accurate tracking without motion correction, harmonic analysis does yield substantial gain in accuracy (defined using HDs) for three particularly challenging subjects. An application of tracking toward a gating optimization procedure was then demonstrated that should allow a physician to balance beam-on time and tissue sparing in a patient-specific manner by tuning several intuitive parameters. Conclusions: Tracking results show high fidelity in assessing intrafractional motion observed on cine-MR acquisitions. Incorporating harmonic analysis during a training period improves the robustness of the tracking for challenging targets. The concomitant gating optimization procedure should allow for physicians to quantitatively assess gating effectiveness quickly just prior to treatment in a patient-specific manner.« less

White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.

PubMed

Dellani, Paulo R; Glaser, Martin; Wille, Paulo R; Vucurevic, Goran; Stadie, Axel; Bauermann, Thomas; Tropine, Andrei; Perneczky, Axel; von Wangenheim, Aldo; Stoeter, Peter

2007-03-01

Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation.

Audio Tracking in Noisy Environments by Acoustic Map and Spectral Signature.

PubMed

Crocco, Marco; Martelli, Samuele; Trucco, Andrea; Zunino, Andrea; Murino, Vittorio

2018-05-01

A novel method is proposed for generic target tracking by audio measurements from a microphone array. To cope with noisy environments characterized by persistent and high energy interfering sources, a classification map (CM) based on spectral signatures is calculated by means of a machine learning algorithm. Next, the CM is combined with the acoustic map, describing the spatial distribution of sound energy, in order to obtain a cleaned joint map in which contributions from the disturbing sources are removed. A likelihood function is derived from this map and fed to a particle filter yielding the target location estimation on the acoustic image. The method is tested on two real environments, addressing both speaker and vehicle tracking. The comparison with a couple of trackers, relying on the acoustic map only, shows a sharp improvement in performance, paving the way to the application of audio tracking in real challenging environments.

Using environmental public health tracking to identify community targets for public health actions in childhood lead poisoning in Wisconsin.

PubMed

Berney, Dawn; Camponeschi, Jenny; Coons, Marjorie; Creswell, Paul D; Schirmer, Joe; Walsh, Reghan

2015-01-01

In an effort to improve the ability of local public health departments to target resources to the highest need regions, the Wisconsin Environmental Public Health Tracking (WI EPHT) Program worked to enhance its public portal to benefit the Wisconsin Childhood Lead Poisoning Prevention Program (WCLPPP) and other programs. The WI EPHT Program conducted this enhancement in collaboration with WCLPPP. The WI EPHT enhanced public portal is the next phase of Wisconsin's ongoing efforts in environmental public health tracking. As part of this process, this new mapping application includes mapping capacity that provides information on childhood lead testing and results at county and census tract levels in Wisconsin. The WI EPHT Program will update its public portal to have the capability to map data at a subcounty level (ie, census tract or zip code) for some data topics when such data are available. This tool is available to local public health departments and other public health organizations throughout Wisconsin as a resource to identify communities most affected by the Centers for Disease Control and Prevention's new guidelines with regard to childhood lead poisoning. The collaboration between WI EPHT and WCLPPP on updating and enhancing the portal exemplifies the power of environmental health data to inform a more accurate understanding of public health problems.

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

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Gao, Changsheng; Jing, Wuxing

2018-03-01

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

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

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.

Micro-miniature radio frequency transmitter for communication and tracking applications

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

Crutcher, R.I.; Emery, M.S.; Falter, K.G.

1996-12-31

A micro-miniature radio frequency (rf) transmitter has been developed and demonstrated by the Oak Ridge National Laboratory. The objective of the rf transmitter development was to maximize the transmission distance while drastically shrinking the overall transmitter size, including antenna. Based on analysis and testing, an application-specific integrated circuit (ASIC) with a 16-GHz gallium arsenide (GaAs) oscillator and integrated on-chip antenna was designed and fabricated using microwave monolithic integrated circuit (MMIC) technology. Details of the development and the results of various field tests will be discussed. The rf transmitter is applicable to covert surveillance and tracking scenarios due to its smallmore » size of 2.2 x 2.2 mm, including the antenna. Additionally, the 16-GHz frequency is well above the operational range of consumer-grade radio scanners, providing a degree of protection from unauthorized interception. Variations of the transmitter design have been demonstrated for tracking and tagging beacons, transmission of digital data, and transmission of real-time analog video from a surveillance camera. Preliminary laboratory measurements indicate adaptability to direct-sequence spread-spectrum transmission, providing a low probability of intercept and/or detection. Concepts related to law enforcement applications will be presented.« less

Square tracking sensor for autonomous helicopter hover stabilization

NASA Astrophysics Data System (ADS)

Oertel, Carl-Henrik

1995-06-01

Sensors for synthetic vision are needed to extend the mission profiles of helicopters. A special task for various applications is the autonomous position hold of a helicopter above a ground fixed or moving target. As a proof of concept for a general synthetic vision solution a restricted machine vision system, which is capable of locating and tracking a special target, was developed by the Institute of Flight Mechanics of Deutsche Forschungsanstalt fur Luft- und Raumfahrt e.V. (i.e., German Aerospace Research Establishment). This sensor, which is specialized to detect and track a square, was integrated in the fly-by-wire helicopter ATTHeS (i.e., Advanced Technology Testing Helicopter System). An existing model following controller for the forward flight condition was adapted for the hover and low speed requirements of the flight vehicle. The special target, a black square with a length of one meter, was mounted on top of a car. Flight tests demonstrated the automatic stabilization of the helicopter above the moving car by synthetic vision.

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

PubMed

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

2012-12-14

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

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

PubMed Central

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

2012-01-01

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

Space-based IR tracking bias removal using background star observations

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

Reallocating attention during multiple object tracking.

PubMed

Ericson, Justin M; Christensen, James C

2012-07-01

Wolfe, Place, and Horowitz (Psychonomic Bulletin & Review 14:344-349, 2007) found that participants were relatively unaffected by selecting and deselecting targets while performing a multiple object tracking task, such that maintaining tracking was possible for longer durations than the few seconds typically studied. Though this result was generally consistent with other findings on tracking duration (Franconeri, Jonathon, & Scimeca Psychological Science 21:920-925, 2010), it was inconsistent with research involving cuing paradigms, specifically precues (Pylyshyn & Annan Spatial Vision 19:485-504, 2006). In the present research, we broke down the addition and removal of targets into separate conditions and incorporated a simple performance model to evaluate the costs associated with the selection and deselection of moving targets. Across three experiments, we demonstrated evidence against a cost being associated with any shift in attention, but rather that varying the type of cue used for target deselection produces no additional cost to performance and that hysteresis effects are not induced by a reduction in tracking load.

GeoTrack: bio-inspired global video tracking by networks of unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Barooah, Prabir; Collins, Gaemus E.; Hespanha, João P.

2009-05-01

Research from the Institute for Collaborative Biotechnologies (ICB) at the University of California at Santa Barbara (UCSB) has identified swarming algorithms used by flocks of birds and schools of fish that enable these animals to move in tight formation and cooperatively track prey with minimal estimation errors, while relying solely on local communication between the animals. This paper describes ongoing work by UCSB, the University of Florida (UF), and the Toyon Research Corporation on the utilization of these algorithms to dramatically improve the capabilities of small unmanned aircraft systems (UAS) to cooperatively locate and track ground targets. Our goal is to construct an electronic system, called GeoTrack, through which a network of hand-launched UAS use dedicated on-board processors to perform multi-sensor data fusion. The nominal sensors employed by the system will EO/IR video cameras on the UAS. When GMTI or other wide-area sensors are available, as in a layered sensing architecture, data from the standoff sensors will also be fused into the GeoTrack system. The output of the system will be position and orientation information on stationary or mobile targets in a global geo-stationary coordinate system. The design of the GeoTrack system requires significant advances beyond the current state-of-the-art in distributed control for a swarm of UAS to accomplish autonomous coordinated tracking; target geo-location using distributed sensor fusion by a network of UAS, communicating over an unreliable channel; and unsupervised real-time image-plane video tracking in low-powered computing platforms.

Computing the apparent centroid of radar targets

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

Lee, C.E.

1996-12-31

A high-frequency multibounce radar scattering code was used as a simulation platform for demonstrating an algorithm to compute the ARC of specific radar targets. To illustrate this simulation process, several targets models were used. Simulation results for a sphere model were used to determine the errors of approximation associated with the simulation; verifying the process. The severity of glint induced tracking errors was also illustrated using a model of an F-15 aircraft. It was shown, in a deterministic manner, that the ARC of a target can fall well outside its physical extent. Finally, the apparent radar centroid simulation based onmore » a ray casting procedure is well suited for use on most massively parallel computing platforms and could lead to the development of a near real-time radar tracking simulation for applications such as endgame fuzing, survivability, and vulnerability analyses using specific radar targets and fuze algorithms.« less

Effect of cross-correlation on track-to-track fusion

NASA Astrophysics Data System (ADS)

Saha, Rajat K.

1994-07-01

Since the advent of target tracking systems employing a diverse mixture of sensors, there has been increasing recognition by air defense system planners and other military system analysts of the need to integrate these tracks so that a clear air picture can be obtained in a command center. A popular methodology to achieve this goal is to perform track-to-track fusion, which performs track-to-track association as well as kinematic state vector fusion. This paper seeks to answer analytically the extent of improvement achievable by means of kinetic state vector fusion when the tracks are obtained from dissimilar sensors (e.g., Radar/ESM/IRST/IFF). It is well known that evaluation of the performance of state vector fusion algorithms at steady state must take into account the effects of cross-correlation between eligible tracks introduced by the input noise which, unfortunately, is often neglected because of added computational complexity. In this paper, an expression for the steady-state cross-covariance matrix for a 2D state vector track-to-track fusion is obtained. This matrix is shown to be a function of the parameters of the Kalman filters associated with the candidate tracks being fused. Conditions for positive definiteness of the cross-covariance matrix have been derived and the effect of positive definiteness on performance of track-to-track fusion is also discussed.

Performance Analysis of Digital Tracking Loops for Telemetry Ranging Applications

NASA Astrophysics Data System (ADS)

Vilnrotter, V.; Hamkins, J.; Xie, H.; Ashrafi, S.

2015-08-01

In this article, we analyze mathematical models of digital loops used to track the phase and timing of communications and navigation signals. The limits on the accuracy of phase and timing estimates play a critical role in the accuracy achievable in telemetry ranging applications. We describe in detail a practical algorithm to compute the loop parameters for discrete update (DU) and continuous update (CU) loop formulations, and we show that a simple power-series approximation to the DU model is valid over a large range of time-bandwidth product . Several numerical examples compare the estimation error variance of the DU and CU models to each other and to Cramer-Rao lower bounds. Finally, the results are applied to the problem of ranging, by evaluating the performance of a phase-locked loop designed to track a typical ambiguity-resolving pseudonoise (PN) code received and demodulated at the spacecraft on the uplink part of the two-way ranging link, and a data transition tracking loop (DTTL) on the downlink part.

Tracking targeted bimodal nanovaccines: immune responses and routing in cells, tissue, and whole organism.

PubMed

Cruz, Luis J; Tacken, Paul J; Zeelenberg, Ingrid S; Srinivas, Mangala; Bonetto, Fernando; Weigelin, Bettina; Eich, Christina; de Vries, I Jolanda; Figdor, Carl G

2014-12-01

Dendritic cells (DCs) are the most potent antigen-presenting cells (APCs), involved in the induction of immunity and currently exploited for antitumor immunotherapies. An optimized noninvasive imaging modality capable of determining and quantifying DC-targeted nanoparticle (NP) trajectories could provide valuable information regarding therapeutic vaccine outcome. Here, targeted poly(d,l-lactide-co-glycolide) nanoparticles (PLGA NPs) recognizing DC receptors were equipped with superparamagnetic iron oxide particles (SPIO) or gold nanoparticles with fluorescently labeled antigen. The fluorescent label allowed for rapid analysis and quantification of DC-specific uptake of targeted PLGA NPs in comparison to uptake by other cells. Transmission electron microscopy (TEM) showed that a fraction of the encapsulated antigen reached the lysosomal compartment of DCs, where SPIO and gold were already partially released. However, part of the PLGA NPs localized within the cytoplasm, as confirmed by confocal microscopy. DCs targeted with NPs carrying SPIO or fluorescent antigen were detected within lymph nodes as early as 1 h after injection by magnetic resonance imaging (MRI). Despite the fact that targeting did not markedly affect PLGA NP biodistribution on organism and tissue level, it increased delivery of NPs to DCs residing in peripheral lymph nodes and resulted in enhanced T cell proliferation. In conclusion, two imaging agents within a single carrier allows tracking of targeted PLGA NPs at the subcellular, cellular, and organismal levels, thereby facilitating the rational design of in vivo targeted vaccination strategies.

Spatio-temporal features for tracking and quadruped/biped discrimination

NASA Astrophysics Data System (ADS)

Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

2012-05-01

Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

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.

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.

A Freehand Ultrasound Elastography System with Tracking for In-vivo Applications

PubMed Central

Foroughi, Pezhman; Kang, Hyun-Jae; Carnegie, Daniel A.; van Vledder, Mark G.; Choti, Michael A.; Hager, Gregory D.; Boctor, Emad M.

2012-01-01

Ultrasound transducers are commonly tracked in modern ultrasound navigation/guidance systems. In this paper, we demonstrate the advantages of incorporating tracking information into ultrasound elastography for clinical applications. First, we address a common limitation of freehand palpation: speckle decorrelation due to out-of-plane probe motion. We show that by automatically selecting pairs of radio frequency (RF) frames with minimal lateral and out-of-plane motions combined with a fast and robust displacement estimation technique greatly improves in-vivo elastography results. We also use tracking information and image quality measure to fuse multiple images with similar strain that are taken roughly from the same location to obtain a high quality elastography image. Finally, we show that tracking information can be used to give the user partial control over the rate of compression. Our methods are tested on tissue mimicking phantom and experiments have been conducted on intra-operative data acquired during animal and human experiments involving liver ablation. Our results suggest that in challenging clinical conditions, our proposed method produces reliable strain images and eliminates the need for a manual search through the ultrasound data in order to find RF pairs suitable for elastography. PMID:23257351

Evaluation of Dose Uncertainty to the Target Associated With Real-Time Tracking Intensity-Modulated Radiation Therapy Using the CyberKnife Synchrony System.

PubMed

Iwata, Hiromitsu; Inoue, Mitsuhiro; Shiomi, Hiroya; Murai, Taro; Tatewaki, Koshi; Ohta, Seiji; Okawa, Kohei; Yokota, Naoki; Shibamoto, Yuta

2016-02-01

We investigated the dose uncertainty caused by errors in real-time tracking intensity-modulated radiation therapy (IMRT) using the CyberKnife Synchrony Respiratory Tracking System (SRTS). Twenty lung tumors that had been treated with non-IMRT real-time tracking using CyberKnife SRTS were used for this study. After validating the tracking error in each case, we did 40 IMRT planning using 8 different collimator sizes for the 20 patients. The collimator size was determined for each planning target volume (PTV); smaller ones were one-half, and larger ones three-quarters, of the PTV diameter. The planned dose was 45 Gy in 4 fractions prescribed at 95% volume border of the PTV. Thereafter, the tracking error in each case was substituted into calculation software developed in house and randomly added in the setting of each beam. The IMRT planning incorporating tracking errors was simulated 1000 times, and various dose data on the clinical target volume (CTV) were compared with the original data. The same simulation was carried out by changing the fraction number from 1 to 6 in each IMRT plan. Finally, a total of 240 000 plans were analyzed. With 4 fractions, the change in the CTV maximum and minimum doses was within 3.0% (median) for each collimator. The change in D99 and D95 was within 2.0%. With decreases in the fraction number, the CTV coverage rate and the minimum dose decreased and varied greatly. The accuracy of real-time tracking IMRT delivered in 4 fractions using CyberKnife SRTS was considered to be clinically acceptable. © The Author(s) 2014.

Incorporating Target Priorities in the Sensor Tasking Reward Function

NASA Astrophysics Data System (ADS)

Gehly, S.; Bennett, J.

2016-09-01

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

Targeting neurotransmitter receptors with nanoparticles in vivo allows single-molecule tracking in acute brain slices

NASA Astrophysics Data System (ADS)

Varela, Juan A.; Dupuis, Julien P.; Etchepare, Laetitia; Espana, Agnès; Cognet, Laurent; Groc, Laurent

2016-03-01

Single-molecule imaging has changed the way we understand many biological mechanisms, particularly in neurobiology, by shedding light on intricate molecular events down to the nanoscale. However, current single-molecule studies in neuroscience have been limited to cultured neurons or organotypic slices, leaving as an open question the existence of fast receptor diffusion in intact brain tissue. Here, for the first time, we targeted dopamine receptors in vivo with functionalized quantum dots and were able to perform single-molecule tracking in acute rat brain slices. We propose a novel delocalized and non-inflammatory way of delivering nanoparticles (NPs) in vivo to the brain, which allowed us to label and track genetically engineered surface dopamine receptors in neocortical neurons, revealing inherent behaviour and receptor activity regulations. We thus propose a NP-based platform for single-molecule studies in the living brain, opening new avenues of research in physiological and pathological animal models.

Deployment Design of Wireless Sensor Network for Simple Multi-Point Surveillance of a Moving Target

PubMed Central

Tsukamoto, Kazuya; Ueda, Hirofumi; Tamura, Hitomi; Kawahara, Kenji; Oie, Yuji

2009-01-01

In this paper, we focus on the problem of tracking a moving target in a wireless sensor network (WSN), in which the capability of each sensor is relatively limited, to construct large-scale WSNs at a reasonable cost. We first propose two simple multi-point surveillance schemes for a moving target in a WSN and demonstrate that one of the schemes can achieve high tracking probability with low power consumption. In addition, we examine the relationship between tracking probability and sensor density through simulations, and then derive an approximate expression representing the relationship. As the results, we present guidelines for sensor density, tracking probability, and the number of monitoring sensors that satisfy a variety of application demands. PMID:22412326

Online Tracking

MedlinePlus

... used to track you on all kinds of internet-connected devices that have browsers, such as smart phones, tablets, laptop and desktop computers. How does tracking in mobile apps occur? When you access mobile applications, companies don’t have access to ...

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.

Application of enteric viruses for fecal pollution source tracking in environmental waters

EPA Science Inventory

Microbial source tracking (MST) tools are used to identify sources of fecal pollution for accurately assessing public health risk and implementing best management practices (BMPs). This review focuses on the potential of enteric viruses for MST applications. Following host infect...

Applications of Cosmic Muon Tracking at Shallow Depth Underground

NASA Astrophysics Data System (ADS)

Oláh, L.; Barnaföldi, G. G.; Hamar, G.; Melegh, H. G.; Surányi, G.; Varga, D.

2014-06-01

A portable cosmic muon telescope has been developed for environmental and geophysical applications, as well as cosmic background measurements for nuclear research in underground labs by the REGARD group (Wigner RCP of the HAS and Eötvös Loránd University collaboration on gaseous detector R&D). The modular, low power consuming (5 W) Close Cathode Chamber-based tracking system has 10 mrad angular resolution with its sensitive area of 0.1 m2. The angular distribution of cosmic muons has been measured at shallow depth underground (< 70 meter-rock-equivalent) in four different remote locations. Application of cosmic muon detection for the reconstruction of underground caverns and building structures are demonstrated by the measurements.

Target-Tracking Camera for a Metrology System

NASA Technical Reports Server (NTRS)

Liebe, Carl; Bartman, Randall; Chapsky, Jacob; Abramovici, Alexander; Brown, David

2009-01-01

An analog electronic camera that is part of a metrology system measures the varying direction to a light-emitting diode that serves as a bright point target. In the original application for which the camera was developed, the metrological system is used to determine the varying relative positions of radiating elements of an airborne synthetic aperture-radar (SAR) antenna as the airplane flexes during flight; precise knowledge of the relative positions as a function of time is needed for processing SAR readings. It has been common metrology system practice to measure the varying direction to a bright target by use of an electronic camera of the charge-coupled-device or active-pixel-sensor type. A major disadvantage of this practice arises from the necessity of reading out and digitizing the outputs from a large number of pixels and processing the resulting digital values in a computer to determine the centroid of a target: Because of the time taken by the readout, digitization, and computation, the update rate is limited to tens of hertz. In contrast, the analog nature of the present camera makes it possible to achieve an update rate of hundreds of hertz, and no computer is needed to determine the centroid. The camera is based on a position-sensitive detector (PSD), which is a rectangular photodiode with output contacts at opposite ends. PSDs are usually used in triangulation for measuring small distances. PSDs are manufactured in both one- and two-dimensional versions. Because it is very difficult to calibrate two-dimensional PSDs accurately, the focal-plane sensors used in this camera are two orthogonally mounted one-dimensional PSDs.

Development of a one-dimensional Position Sensitive Detector for tracking applications

NASA Astrophysics Data System (ADS)

Lydecker, Leigh Kent, IV

Optical Position Sensitive Detectors (PSDs) are a non-contact method of tracking the location of a light spot. Silicon-based versions of such sensors are fabricated with standard CMOS processing, are inexpensive and provide a real-time, analog signal output corresponding to the position of the light spot. Because they are non-contact, they do not degrade over time from surface friction due to repetitive sliding motion associated with standard full contact sliding potentiometers. This results in long, reliable device lifetimes. In this work, an innovative PSD was developed to replace the linear hard contact potentiometer currently being used in a human-computer interface architecture. First, a basic lateral effect PSD was developed to provide real-time positioning of the mouthpiece used in the interface architecture which tracks along a single axis. During the course of this work, multiple device geometries were fabricated and analyzed resulting in a down selection of a final design. This final device design was then characterized in terms of resolution and responsivity and produced in larger quantities as initial prototypes for the test product integration. Finally, an electronic readout circuit was developed in order to interface the dual- line lateral effect PSD developed in this thesis with specifications required for product integration. To simplify position sensing, an innovative type of optical position sensor was developed using a linear photodiodes with back-to-back connections. This so- called Self-Balancing Position Sensitive Detector (SBPSD) requires significantly fewer processing steps than the basic lateral effect position sensitive detector discussed above and eliminates the need for external readout circuitry entirely. Prototype devices were fabricated in this work, and the performance characteristics of these devices were established paving the way for ultimate integration into the target product as well as additional applications.

Combining user logging with eye tracking for interactive and dynamic applications.

PubMed

Ooms, Kristien; Coltekin, Arzu; De Maeyer, Philippe; Dupont, Lien; Fabrikant, Sara; Incoul, Annelies; Kuhn, Matthias; Slabbinck, Hendrik; Vansteenkiste, Pieter; Van der Haegen, Lise

2015-12-01

User evaluations of interactive and dynamic applications face various challenges related to the active nature of these displays. For example, users can often zoom and pan on digital products, and these interactions cause changes in the extent and/or level of detail of the stimulus. Therefore, in eye tracking studies, when a user's gaze is at a particular screen position (gaze position) over a period of time, the information contained in this particular position may have changed. Such digital activities are commonplace in modern life, yet it has been difficult to automatically compare the changing information at the viewed position, especially across many participants. Existing solutions typically involve tedious and time-consuming manual work. In this article, we propose a methodology that can overcome this problem. By combining eye tracking with user logging (mouse and keyboard actions) with cartographic products, we are able to accurately reference screen coordinates to geographic coordinates. This referencing approach allows researchers to know which geographic object (location or attribute) corresponds to the gaze coordinates at all times. We tested the proposed approach through two case studies, and discuss the advantages and disadvantages of the applied methodology. Furthermore, the applicability of the proposed approach is discussed with respect to other fields of research that use eye tracking-namely, marketing, sports and movement sciences, and experimental psychology. From these case studies and discussions, we conclude that combining eye tracking and user-logging data is an essential step forward in efficiently studying user behavior with interactive and static stimuli in multiple research fields.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

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

I’ll Be Back: On the Multiple Lives of Users of a Mobile Activity Tracking Application

PubMed Central

Lin, Zhiyuan; Althoff, Tim; Leskovec, Jure

2018-01-01

Mobile health applications that track activities, such as exercise, sleep, and diet, are becoming widely used. While these activity tracking applications have the potential to improve our health, user engagement and retention are critical factors for their success. However, long-term user engagement patterns in real-world activity tracking applications are not yet well understood. Here we study user engagement patterns within a mobile physical activity tracking application consisting of 115 million logged activities taken by over a million users over 31 months. Specifically, we show that over 75% of users return and re-engage with the application after prolonged periods of inactivity, no matter the duration of the inactivity. We find a surprising result that the re-engagement usage patterns resemble those of the start of the initial engagement period, rather than being a simple continuation of the end of the initial engagement period. This evidence points to a conceptual model of multiple lives of user engagement, extending the prevalent single life view of user activity. We demonstrate that these multiple lives occur because the users have a variety of different primary intents or goals for using the app. These primary intents are associated with how long each life lasts and how likely the user is to re-engage for a new life. We find evidence for users being more likely to stop using the app once they achieved their primary intent or goal (e.g., weight loss). However, these users might return once their original intent resurfaces (e.g., wanting to lose newly gained weight). We discuss implications of the multiple life paradigm and propose a novel prediction task of predicting the number of lives of a user. Based on insights developed in this work, including a marker of improved primary intent performance, our prediction models achieve 71% ROC AUC. Overall, our research has implications for modeling user re-engagement in health activity tracking applications and

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.

UWB Tracking Algorithms: AOA and TDOA

NASA Technical Reports Server (NTRS)

Ni, Jianjun David; Arndt, D.; Ngo, P.; Gross, J.; Refford, Melinda

2006-01-01

Ultra-Wideband (UWB) tracking prototype systems are currently under development at NASA Johnson Space Center for various applications on space exploration. For long range applications, a two-cluster Angle of Arrival (AOA) tracking method is employed for implementation of the tracking system; for close-in applications, a Time Difference of Arrival (TDOA) positioning methodology is exploited. Both AOA and TDOA are chosen to utilize the achievable fine time resolution of UWB signals. This talk presents a brief introduction to AOA and TDOA methodologies. The theoretical analysis of these two algorithms reveal the affecting parameters impact on the tracking resolution. For the AOA algorithm, simulations show that a tracking resolution less than 0.5% of the range can be achieved with the current achievable time resolution of UWB signals. For the TDOA algorithm used in close-in applications, simulations show that the (sub-inch) high tracking resolution is achieved with a chosen tracking baseline configuration. The analytical and simulated results provide insightful guidance for the UWB tracking system design.

Learning the trajectory of a moving visual target and evolution of its tracking in the monkey

PubMed Central

Bourrelly, Clara; Quinet, Julie; Cavanagh, Patrick

2016-01-01

An object moving in the visual field triggers a saccade that brings its image onto the fovea. It is followed by a combination of slow eye movements and catch-up saccades that try to keep the target image on the fovea as long as possible. The accuracy of this ability to track the “here-and-now” location of a visual target contrasts with the spatiotemporally distributed nature of its encoding in the brain. We show in six experimentally naive monkeys how this performance is acquired and gradually evolves during successive daily sessions. During the early exposure, the tracking is mostly saltatory, made of relatively large saccades separated by low eye velocity episodes, demonstrating that accurate (here and now) pursuit is not spontaneous and that gaze direction lags behind its location most of the time. Over the sessions, while the pursuit velocity is enhanced, the gaze is more frequently directed toward the current target location as a consequence of a 25% reduction in the number of catch-up saccades and a 37% reduction in size (for the first saccade). This smoothing is observed at several scales: during the course of single trials, across the set of trials within a session, and over successive sessions. We explain the neurophysiological processes responsible for this combined evolution of saccades and pursuit in the absence of stringent training constraints. More generally, our study shows that the oculomotor system can be used to discover the neural mechanisms underlying the ability to synchronize a motor effector with a dynamic external event. PMID:27683886

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.

Proton induced target fragmentation studies on solid state nuclear track detectors using Carbon radiators

NASA Astrophysics Data System (ADS)

Szabó, J.; Pálfalvi, J. K.; Strádi, A.; Bilski, P.; Swakoń, J.; Stolarczyk, L.

2018-04-01

One of the limiting factors of an astronaut's career is the dose received from space radiation. High energy protons, being the main components of the complex radiation field present on a spacecraft, give a significant contribution to the dose. To investigate the behavior of solid state nuclear track detectors (SSNTDs) if they are irradiated by such particles, SSNTD stacks containing carbon blocks were exposed to high energy proton beams (70, 100, 150 and 230 MeV) at the Proteus cyclotron, IFJ PAN -Krakow. The incident protons cannot be detected directly; however, tracks of secondary particles, recoils and fragments of the constituent atoms of the detector material and of the carbon radiator are formed. It was found that as the proton energy increases, the number of tracks induced in the PADC material by secondary particles decreases. From the measured geometrical parameters of the tracks the linear energy transfer (LET) spectrum and the dosimetric quantities were determined, applying appropriate calibration. In the LET spectra the LET range of the most important secondary particles could be identified and their abundance showed differences in the spectra if the detectors were short or long etched. The LET spectra obtained on the SSNTDs irradiated by protons were compared to LET spectra of detectors flown on the International Space Station (ISS): they were quite similar, resulting in a quality factor difference of only 5%. Thermoluminescent detectors (TLDs) were applied in each case to measure the dose from primary protons and other lower LET particles present in space. Comparing and analyzing the results of the TLD and SSNTD measurements, it was obtained that proton induced target fragments contributed to the total absorbed dose in 3.2% and to the dose equivalent in 14.2% in this particular space experiment.

Development of a 750x750 pixels CMOS imager sensor for tracking applications

NASA Astrophysics Data System (ADS)

Larnaudie, Franck; Guardiola, Nicolas; Saint-Pé, Olivier; Vignon, Bruno; Tulet, Michel; Davancens, Robert; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Estribeau, Magali

2017-11-01

Solid-state optical sensors are now commonly used in space applications (navigation cameras, astronomy imagers, tracking sensors...). Although the charge-coupled devices are still widely used, the CMOS image sensor (CIS), which performances are continuously improving, is a strong challenger for Guidance, Navigation and Control (GNC) systems. This paper describes a 750x750 pixels CMOS image sensor that has been specially designed and developed for star tracker and tracking sensor applications. Such detector, that is featuring smart architecture enabling very simple and powerful operations, is built using the AMIS 0.5μm CMOS technology. It contains 750x750 rectangular pixels with 20μm pitch. The geometry of the pixel sensitive zone is optimized for applications based on centroiding measurements. The main feature of this device is the on-chip control and timing function that makes the device operation easier by drastically reducing the number of clocks to be applied. This powerful function allows the user to operate the sensor with high flexibility: measurement of dark level from masked lines, direct access to the windows of interest… A temperature probe is also integrated within the CMOS chip allowing a very precise measurement through the video stream. A complete electro-optical characterization of the sensor has been performed. The major parameters have been evaluated: dark current and its uniformity, read-out noise, conversion gain, Fixed Pattern Noise, Photo Response Non Uniformity, quantum efficiency, Modulation Transfer Function, intra-pixel scanning. The characterization tests are detailed in the paper. Co60 and protons irradiation tests have been also carried out on the image sensor and the results are presented. The specific features of the 750x750 image sensor such as low power CMOS design (3.3V, power consumption<100mW), natural windowing (that allows efficient and robust tracking algorithms), simple proximity electronics (because of the on

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

PubMed

Huang, Lvwen; Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-08-23

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor

PubMed Central

Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-01-01

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields. PMID:28832520

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

NASA Astrophysics Data System (ADS)

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

2011-05-01

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

Application of Multifunctional Doppler LIDAR for Noncontact Track Speed, Distance, and Curvature Assessment

NASA Astrophysics Data System (ADS)

Munoz, Joshua

The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheelmounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to highfidelity distance and curvature data through utilization of processor clock rate and left-and rightrail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a "Hy-Rail" utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in

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

PubMed

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

2015-08-30

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

Computing Satellite Maneuvers For A Repeating Ground Track

NASA Technical Reports Server (NTRS)

Shapiro, Bruce

1994-01-01

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

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

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.

Application of target costing in machining

NASA Astrophysics Data System (ADS)

Gopalakrishnan, Bhaskaran; Kokatnur, Ameet; Gupta, Deepak P.

2004-11-01

In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.

A generalized target theory and its applications.

PubMed

Zhao, Lei; Mi, Dong; Hu, Bei; Sun, Yeqing

2015-09-28

Different radiobiological models have been proposed to estimate the cell-killing effects, which are very important in radiotherapy and radiation risk assessment. However, most applied models have their own scopes of application. In this work, by generalizing the relationship between "hit" and "survival" in traditional target theory with Yager negation operator in Fuzzy mathematics, we propose a generalized target model of radiation-induced cell inactivation that takes into account both cellular repair effects and indirect effects of radiation. The simulation results of the model and the rethinking of "the number of targets in a cell" and "the number of hits per target" suggest that it is only necessary to investigate the generalized single-hit single-target (GSHST) in the present theoretical frame. Analysis shows that the GSHST model can be reduced to the linear quadratic model and multitarget model in the low-dose and high-dose regions, respectively. The fitting results show that the GSHST model agrees well with the usual experimental observations. In addition, the present model can be used to effectively predict cellular repair capacity, radiosensitivity, target size, especially the biologically effective dose for the treatment planning in clinical applications.

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.

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

PubMed

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

2008-05-01

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

Commercial associative memory performance for applications in track-based triggers at the Large Hadron Collider

NASA Astrophysics Data System (ADS)

Webster, Jordan

2017-01-01

Dense track environments in pp collisions at the Large Hadron Collider (LHC) motivate the use of triggers with dedicated hardware for fast track reconstruction. The ATLAS Collaboration is in the process of implementing a Fast Tracker (FTK) trigger upgrade, in which Content Addressable Memories (CAMs) will be used to rapidly match hit patterns with large banks of simulated tracks. The FTK CAMs are produced primarily at the University of Pisa. However, commercial CAM technology is rapidly developing due to applications in computer networking devices. This poster presents new studies comparing FTK CAMs to cutting-edge ternary CAMs developed by Cavium. The comparison is intended to guide the design of future track-based trigger systems for the next Phase at the LHC.

A hybrid mobile-based patient location tracking system for personal healthcare applications.

PubMed

Chew, S H; Chong, P A; Gunawan, E; Goh, K W; Kim, Y; Soh, C B

2006-01-01

In the next generation of Infocommunications, mobile Internet-enabled devices and third generation mobile communication networks have become reality, location based services (LBS) are expected to be a major area of growth. Providing information, content and services through positioning technologies forms the platform for new services for users and developers, as well as creating new revenue channels for service providers. These crucial advances in location based services have opened up new opportunities in real time patient tracking for personal healthcare applications. In this paper, a hybrid mobile-based location technique using the global positioning system (GPS) and cellular mobile network infrastructure is employed to provide the location tracking capability. This function will be integrated into the patient location tracking system (PLTS) to assist caregivers or family members in locating patients such as elderly or dependents when required, especially in emergencies. The capability of this PLTS is demonstrated through a series of location detection tests conducted over different operating conditions. Although the model is at its initial stage of development, it has shown relatively good accuracy for position tracking and potential of using integrated wireless technology to enhance the existing personal healthcare communication system through location based services.

76 FR 6369 - Changes To Implement the Prioritized Examination Track (Track I) of the Enhanced Examination...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-04

... (Track I), providing fast examination for applicants desiring it, upon payment of the applicable fee and... examiners or supervisory patent examiners, specialized examiner training for fast track processing...