Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Rik Van de Walle

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

Performance evaluation software moving object detection and tracking in videos

CERN Document Server

Karasulu, Bahadir

2013-01-01

Performance Evaluation Software: Moving Object Detection and Tracking in Videos introduces a software approach for the real-time evaluation and performance comparison of the methods specializing in moving object detection and/or tracking (D&T) in video processing. Digital video content analysis is an important item for multimedia content-based indexing (MCBI), content-based video retrieval (CBVR) and visual surveillance systems. There are some frequently-used generic algorithms for video object D&T in the literature, such as Background Subtraction (BS), Continuously Adaptive Mean-shift (CMS),

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

Directory of Open Access Journals (Sweden)

Ming Xue

2014-02-01

Full Text Available 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.

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

Science.gov (United States)

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.

Target Tracking of a Linear Time Invariant System under Irregular Sampling

Directory of Open Access Journals (Sweden)

Jin Xue-Bo

2012-11-01

Full Text Available Due to event-triggered sampling in a system, or maybe with the aim of reducing data storage, tracking many applications will encounter irregular sampling time. By calculating the matrix exponential using an inverse Laplace transform, this paper transforms the irregular sampling tracking problem to the problem of tracking with time-varying parameters of a system. Using the common Kalman filter, the developed method is used to track a target for the simulated trajectory and video tracking. The results of simulation experiments have shown that it can obtain good estimation performance even at a very high irregular rate of measurement sampling time.

High-throughput phenotyping of plant resistance to aphids by automated video tracking.

Science.gov (United States)

Kloth, Karen J; Ten Broeke, Cindy Jm; Thoen, Manus Pm; Hanhart-van den Brink, Marianne; Wiegers, Gerrie L; Krips, Olga E; Noldus, Lucas Pjj; Dicke, Marcel; Jongsma, Maarten A

2015-01-01

Piercing-sucking insects are major vectors of plant viruses causing significant yield losses in crops. Functional genomics of plant resistance to these insects would greatly benefit from the availability of high-throughput, quantitative phenotyping methods. We have developed an automated video tracking platform that quantifies aphid feeding behaviour on leaf discs to assess the level of plant resistance. Through the analysis of aphid movement, the start and duration of plant penetrations by aphids were estimated. As a case study, video tracking confirmed the near-complete resistance of lettuce cultivar 'Corbana' against Nasonovia ribisnigri (Mosely), biotype Nr:0, and revealed quantitative resistance in Arabidopsis accession Co-2 against Myzus persicae (Sulzer). The video tracking platform was benchmarked against Electrical Penetration Graph (EPG) recordings and aphid population development assays. The use of leaf discs instead of intact plants reduced the intensity of the resistance effect in video tracking, but sufficiently replicated experiments resulted in similar conclusions as EPG recordings and aphid population assays. One video tracking platform could screen 100 samples in parallel. Automated video tracking can be used to screen large plant populations for resistance to aphids and other piercing-sucking insects.

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

International Nuclear Information System (INIS)

Anderson, Robert J.

2014-01-01

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, more 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.

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

Energy Technology Data Exchange (ETDEWEB)

Anderson, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

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, more 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.

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

Energy Technology Data Exchange (ETDEWEB)

Anderson, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Robotic and Security Systems Dept.

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, more 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.

Optimal path planning for video-guided smart munitions via multitarget tracking

Science.gov (United States)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

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

Science.gov (United States)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

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

Video-based measurements for wireless capsule endoscope tracking

International Nuclear Information System (INIS)

Spyrou, Evaggelos; Iakovidis, Dimitris K

2014-01-01

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

Video-based measurements for wireless capsule endoscope tracking

Science.gov (United States)

Spyrou, Evaggelos; Iakovidis, Dimitris K.

2014-01-01

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

Multi-view video segmentation and tracking for video surveillance

Science.gov (United States)

Mohammadi, Gelareh; Dufaux, Frederic; Minh, Thien Ha; Ebrahimi, Touradj

2009-05-01

Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the different viewpoints. The technical problems in multiple camera systems are several: installation, calibration, objects matching, switching, data fusion, and occlusion handling. In this paper, we address the issue of tracking moving objects in an environment covered by multiple un-calibrated cameras with overlapping fields of view, typical of most surveillance setups. Our main objective is to create a framework that can be used to integrate objecttracking information from multiple video sources. Basically, the proposed technique consists of the following steps. We first perform a single-view tracking algorithm on each camera view, and then apply a consistent object labeling algorithm on all views. In the next step, we verify objects in each view separately for inconsistencies. Correspondent objects are extracted through a Homography transform from one view to the other and vice versa. Having found the correspondent objects of different views, we partition each object into homogeneous regions. In the last step, we apply the Homography transform to find the region map of first view in the second view and vice versa. For each region (in the main frame and mapped frame) a set of descriptors are extracted to find the best match between two views based on region descriptors similarity. This method is able to deal with multiple objects. Track management issues such as occlusion, appearance and disappearance of objects are resolved using information from all views. This method is capable of tracking rigid and deformable objects and this versatility lets it to be suitable for different application scenarios.

Study on the Detection of Moving Target in the Mining Method Based on Hybrid Algorithm for Sports Video Analysis

Directory of Open Access Journals (Sweden)

Huang Tian

2014-10-01

Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.

Object tracking using multiple camera video streams

Science.gov (United States)

Mehrubeoglu, Mehrube; Rojas, Diego; McLauchlan, Lifford

2010-05-01

Two synchronized cameras are utilized to obtain independent video streams to detect moving objects from two different viewing angles. The video frames are directly correlated in time. Moving objects in image frames from the two cameras are identified and tagged for tracking. One advantage of such a system involves overcoming effects of occlusions that could result in an object in partial or full view in one camera, when the same object is fully visible in another camera. Object registration is achieved by determining the location of common features in the moving object across simultaneous frames. Perspective differences are adjusted. Combining information from images from multiple cameras increases robustness of the tracking process. Motion tracking is achieved by determining anomalies caused by the objects' movement across frames in time in each and the combined video information. The path of each object is determined heuristically. Accuracy of detection is dependent on the speed of the object as well as variations in direction of motion. Fast cameras increase accuracy but limit the speed and complexity of the algorithm. Such an imaging system has applications in traffic analysis, surveillance and security, as well as object modeling from multi-view images. The system can easily be expanded by increasing the number of cameras such that there is an overlap between the scenes from at least two cameras in proximity. An object can then be tracked long distances or across multiple cameras continuously, applicable, for example, in wireless sensor networks for surveillance or navigation.

Real-time WAMI streaming target tracking in fog

Science.gov (United States)

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.

‘PhysTrack’: a Matlab based environment for video tracking of kinematics in the physics laboratory

Science.gov (United States)

Umar Hassan, Muhammad; Sabieh Anwar, Muhammad

2017-07-01

In the past two decades, several computer software tools have been developed to investigate the motion of moving bodies in physics laboratories. In this article we report a Matlab based video tracking library, PhysTrack, primarily designed to investigate kinematics. We compare PhysTrack with other commonly available video tracking tools and outline its salient features. The general methodology of the whole video tracking process is described with a step by step explanation of several functionalities. Furthermore, results of some real physics experiments are also provided to demonstrate the working of the automated video tracking, data extraction, data analysis and presentation tools that come with this development environment. We believe that PhysTrack will be valuable for the large community of physics teachers and students already employing Matlab.

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

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

Science.gov (United States)

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.

A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos

KAUST Repository

Wu, Baoyuan

2016-10-25

Face clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face clustering and face tracking from real world videos. The motivation for the proposed research is that face clustering and face tracking can provide useful information and constraints to each other, thus can bootstrap and improve the performances of each other. To this end, we introduce a Coupled Hidden Markov Random Field (CHMRF) to simultaneously model face clustering, face tracking, and their interactions. We provide an effective algorithm based on constrained clustering and optimal tracking for the joint optimization of cluster labels and face tracking. We demonstrate significant improvements over state-of-the-art results in face clustering and tracking on several videos.

Evaluation of a video-based head motion tracking system for dedicated brain PET

Science.gov (United States)

Anishchenko, S.; Beylin, D.; Stepanov, P.; Stepanov, A.; Weinberg, I. N.; Schaeffer, S.; Zavarzin, V.; Shaposhnikov, D.; Smith, M. F.

2015-03-01

Unintentional head motion during Positron Emission Tomography (PET) data acquisition can degrade PET image quality and lead to artifacts. Poor patient compliance, head tremor, and coughing are examples of movement sources. Head motion due to patient non-compliance can be an issue with the rise of amyloid brain PET in dementia patients. To preserve PET image resolution and quantitative accuracy, head motion can be tracked and corrected in the image reconstruction algorithm. While fiducial markers can be used, a contactless approach is preferable. A video-based head motion tracking system for a dedicated portable brain PET scanner was developed. Four wide-angle cameras organized in two stereo pairs are used for capturing video of the patient's head during the PET data acquisition. Facial points are automatically tracked and used to determine the six degree of freedom head pose as a function of time. The presented work evaluated the newly designed tracking system using a head phantom and a moving American College of Radiology (ACR) phantom. The mean video-tracking error was 0.99±0.90 mm relative to the magnetic tracking device used as ground truth. Qualitative evaluation with the ACR phantom shows the advantage of the motion tracking application. The developed system is able to perform tracking with accuracy close to millimeter and can help to preserve resolution of brain PET images in presence of movements.

Tracking of Individuals in Very Long Video Sequences

DEFF Research Database (Denmark)

Fihl, Preben; Corlin, Rasmus; Park, Sangho

2006-01-01

In this paper we present an approach for automatically detecting and tracking humans in very long video sequences. The detection is based on background subtraction using a multi-mode Codeword method. We enhance this method both in terms of representation and in terms of automatically updating...

Video-based Chinese Input System via Fingertip Tracking

Directory of Open Access Journals (Sweden)

Chih-Chang Yu

2012-10-01

Full Text Available In this paper, we propose a system to detect and track fingertips online and recognize Mandarin Phonetic Symbol (MPS for user-friendly Chinese input purposes. Using fingertips and cameras to replace pens and touch panels as input devices could reduce the cost and improve the ease-of-use and comfort of computer-human interface. In the proposed framework, particle filters with enhanced appearance models are applied for robust fingertip tracking. Afterwards, MPS combination recognition is performed on the tracked fingertip trajectories using Hidden Markov Models. In the proposed system, the fingertips of the users could be robustly tracked. Also, the challenges of entering, leaving and virtual strokes caused by video-based fingertip input can be overcome. Experimental results have shown the feasibility and effectiveness of the proposed work.

EVA: laparoscopic instrument tracking based on Endoscopic Video Analysis for psychomotor skills assessment.

Science.gov (United States)

Oropesa, Ignacio; Sánchez-González, Patricia; Chmarra, Magdalena K; Lamata, Pablo; Fernández, Alvaro; Sánchez-Margallo, Juan A; Jansen, Frank Willem; Dankelman, Jenny; Sánchez-Margallo, Francisco M; Gómez, Enrique J

2013-03-01

The EVA (Endoscopic Video Analysis) tracking system is a new system for extracting motions of laparoscopic instruments based on nonobtrusive video tracking. The feasibility of using EVA in laparoscopic settings has been tested in a box trainer setup. EVA makes use of an algorithm that employs information of the laparoscopic instrument's shaft edges in the image, the instrument's insertion point, and the camera's optical center to track the three-dimensional position of the instrument tip. A validation study of EVA comprised a comparison of the measurements achieved with EVA and the TrEndo tracking system. To this end, 42 participants (16 novices, 22 residents, and 4 experts) were asked to perform a peg transfer task in a box trainer. Ten motion-based metrics were used to assess their performance. Construct validation of the EVA has been obtained for seven motion-based metrics. Concurrent validation revealed that there is a strong correlation between the results obtained by EVA and the TrEndo for metrics, such as path length (ρ = 0.97), average speed (ρ = 0.94), or economy of volume (ρ = 0.85), proving the viability of EVA. EVA has been successfully validated in a box trainer setup, showing the potential of endoscopic video analysis to assess laparoscopic psychomotor skills. The results encourage further implementation of video tracking in training setups and image-guided surgery.

Multiscale Architectures and Parallel Algorithms for Video Object Tracking

Science.gov (United States)

2011-10-01

larger number of cores using the IBM QS22 Blade for handling higher video processing workloads (but at higher cost per core), low power consumption and...Cell/B.E. Blade processors which have a lot more main memory but also higher power consumption . More detailed performance figures for HD and SD video...Parallelism in Algorithms and Architectures, pages 289–298, 2007. [3] S. Ali and M. Shah. COCOA - Tracking in aerial imagery. In Daniel J. Henry

AUTOMATIC FAST VIDEO OBJECT DETECTION AND TRACKING ON VIDEO SURVEILLANCE SYSTEM

Directory of Open Access Journals (Sweden)

V. Arunachalam

2012-08-01

Full Text Available This paper describes the advance techniques for object detection and tracking in video. Most visual surveillance systems start with motion detection. Motion detection methods attempt to locate connected regions of pixels that represent the moving objects within the scene; different approaches include frame-to-frame difference, background subtraction and motion analysis. The motion detection can be achieved by Principle Component Analysis (PCA and then separate an objects from background using background subtraction. The detected object can be segmented. Segmentation consists of two schemes: one for spatial segmentation and the other for temporal segmentation. Tracking approach can be done in each frame of detected Object. Pixel label problem can be alleviated by the MAP (Maximum a Posteriori technique.

The effect of action video game playing on sensorimotor learning: Evidence from a movement tracking task.

Science.gov (United States)

Gozli, Davood G; Bavelier, Daphne; Pratt, Jay

2014-10-12

Research on the impact of action video game playing has revealed performance advantages on a wide range of perceptual and cognitive tasks. It is not known, however, if playing such games confers similar advantages in sensorimotor learning. To address this issue, the present study used a manual motion-tracking task that allowed for a sensitive measure of both accuracy and improvement over time. When the target motion pattern was consistent over trials, gamers improved with a faster rate and eventually outperformed non-gamers. Performance between the two groups, however, did not differ initially. When the target motion was inconsistent, changing on every trial, results revealed no difference between gamers and non-gamers. Together, our findings suggest that video game playing confers no reliable benefit in sensorimotor control, but it does enhance sensorimotor learning, enabling superior performance in tasks with consistent and predictable structure. Copyright © 2014. Published by Elsevier B.V.

Hypersonic sliding target tracking in near space

Directory of Open Access Journals (Sweden)

Xiang-yu Zhang

2015-12-01

Full Text Available To improve the tracking accuracy of hypersonic sliding target in near space, the influence of target hypersonic movement on radar detection and tracking is analyzed, and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed (ECEF coordinate. Based on the analysis of effect of target hypersonic movement, a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch. The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space. The high dynamic biases are further eliminated by the cancellation processing of different radars, in which the track association problem can be solved when the dynamic biases are low. An IMM algorithm based on constant acceleration (CA, constant turning (CT and Singer models is used to achieve the hypersonic sliding target tracking in near space. Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.

Extracting 3d Semantic Information from Video Surveillance System Using Deep Learning

Science.gov (United States)

Zhang, J. S.; Cao, J.; Mao, B.; Shen, D. Q.

2018-04-01

At present, intelligent video analysis technology has been widely used in various fields. Object tracking is one of the important part of intelligent video surveillance, but the traditional target tracking technology based on the pixel coordinate system in images still exists some unavoidable problems. Target tracking based on pixel can't reflect the real position information of targets, and it is difficult to track objects across scenes. Based on the analysis of Zhengyou Zhang's camera calibration method, this paper presents a method of target tracking based on the target's space coordinate system after converting the 2-D coordinate of the target into 3-D coordinate. It can be seen from the experimental results: Our method can restore the real position change information of targets well, and can also accurately get the trajectory of the target in space.

Exploiting target amplitude information to improve multi-target tracking

Science.gov (United States)

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.

Video Surveillance using a Multi-Camera Tracking and Fusion System

OpenAIRE

Zhang , Zhong; Scanlon , Andrew; Yin , Weihong; Yu , Li; Venetianer , Péter L.

2008-01-01

International audience; Usage of intelligent video surveillance (IVS) systems is spreading rapidly. These systems are being utilized in a wide range of applications. In most cases, even in multi-camera installations, the video is processed independently in each feed. This paper describes a system that fuses tracking information from multiple cameras, thus vastly expanding its capabilities. The fusion relies on all cameras being calibrated to a site map, while the individual sensors remain lar...

Underwater Acoustic Target Tracking: A Review

Science.gov (United States)

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

Real-time logo detection and tracking in video

Science.gov (United States)

George, M.; Kehtarnavaz, N.; Rahman, M.; Carlsohn, M.

2010-05-01

This paper presents a real-time implementation of a logo detection and tracking algorithm in video. The motivation of this work stems from applications on smart phones that require the detection of logos in real-time. For example, one application involves detecting company logos so that customers can easily get special offers in real-time. This algorithm uses a hybrid approach by initially running the Scale Invariant Feature Transform (SIFT) algorithm on the first frame in order to obtain the logo location and then by using an online calibration of color within the SIFT detected area in order to detect and track the logo in subsequent frames in a time efficient manner. The results obtained indicate that this hybrid approach allows robust logo detection and tracking to be achieved in real-time.

Kalman Filter Based Tracking in an Video Surveillance System

Directory of Open Access Journals (Sweden)

SULIMAN, C.

2010-05-01

Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

Automatic tracking of cells for video microscopy in patch clamp experiments.

Science.gov (United States)

Peixoto, Helton M; Munguba, Hermany; Cruz, Rossana M S; Guerreiro, Ana M G; Leao, Richardson N

2014-06-20

Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. The techniques of digital image processing used in this work are an important addition to the set of microscopy

Contextual analysis of videos

CERN Document Server

Thida, Myo; Monekosso, Dorothy

2013-01-01

Video context analysis is an active and vibrant research area, which provides means for extracting, analyzing and understanding behavior of a single target and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics: 1) counting number of people in the scene 2) tracking individuals in a crowd and 3) understanding behavior of a single target or multiple targets in the scene.

Thermal Tracking of Sports Players

Directory of Open Access Journals (Sweden)

Rikke Gade

2014-07-01

Full Text Available We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

Thermal tracking of sports players.

Science.gov (United States)

Gade, Rikke; Moeslund, Thomas B

2014-07-29

We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

IFE Target Injection Tracking and Position Prediction Update

International Nuclear Information System (INIS)

Petzoldt, Ronald W.; Jonestrask, Kevin

2005-01-01

To achieve high gain in an inertial fusion energy power plant, driver beams must hit direct drive targets with ±20 μm accuracy (±100 μm for indirect drive). Targets will have to be tracked with even greater accuracy. The conceptual design for our tracking system, which predicts target arrival position and timing based on position measurements outside of the reaction chamber was previously described. The system has been built and has begun tracking targets at the first detector station. Additional detector stations are being modified for increased field of view. After three tracking stations are operational, position predictions at the final station will be compared to position measurements at that station as a measure of target position prediction accuracy.The as-installed design will be described together with initial target tracking and position prediction accuracy results. Design modifications that allow for improved accuracy and/or in-chamber target tracking will also be presented

A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

Directory of Open Access Journals (Sweden)

Chang Yao-Jen

2002-01-01

Full Text Available This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network and the H.324 WAN (wide-area network users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

Science.gov (United States)

Lin, Chia-Wen; Chang, Yao-Jen; Wang, Chih-Ming; Chen, Yung-Chang; Sun, Ming-Ting

2002-12-01

This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU) for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network) and the H.324 WAN (wide-area network) users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

A survey on the automatic object tracking technology using video signals

International Nuclear Information System (INIS)

Lee, Jae Cheol; Jun, Hyeong Seop; Choi, Yu Rak; Kim, Jae Hee

2003-01-01

Recently, automatic identification and tracking of the object are actively studied according to the rapid development of signal processing and vision technology using improved hardware and software. The object tracking technology can be applied to various fields such as road watching of the vehicles, weather satellite, traffic observation, intelligent remote video-conferences and autonomous mobile robots. Object tracking system receives subsequent pictures from the camera and detects motions of the objects in these pictures. In this report, we investigate various object tracking techniques such as brightness change using histogram characteristic, differential image analysis, contour and feature extraction, and try to find proper methods that can be used to mobile robots actually

Heterogeneous CPU-GPU moving targets detection for UAV video

Science.gov (United States)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

Computer-aided target tracking in motion analysis studies

Science.gov (United States)

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

1990-08-01

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

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

Directory of Open Access Journals (Sweden)

Xin Li

2014-06-01

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

Robust infrared target tracking using discriminative and generative approaches

Science.gov (United States)

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.

Qualitative Video Analysis of Track-Cycling Team Pursuit in World-Class Athletes.

Science.gov (United States)

Sigrist, Samuel; Maier, Thomas; Faiss, Raphael

2017-11-01

Track-cycling team pursuit (TP) is a highly technical effort involving 4 athletes completing 4 km from a standing start, often in less than 240 s. Transitions between athletes leading the team are obviously of utmost importance. To perform qualitative video analyses of transitions of world-class athletes in TP competitions. Videos captured at 100 Hz were recorded for 77 races (including 96 different athletes) in 5 international track-cycling competitions (eg, UCI World Cups and World Championships) and analyzed for the 12 best teams in the UCI Track Cycling TP Olympic ranking. During TP, 1013 transitions were evaluated individually to extract quantitative (eg, average lead time, transition number, length, duration, height in the curve) and qualitative (quality of transition start, quality of return at the back of the team, distance between third and returning rider score) variables. Determination of correlation coefficients between extracted variables and end time allowed assessment of relationships between variables and relevance of the video analyses. Overall quality of transitions and end time were significantly correlated (r = .35, P = .002). Similarly, transition distance (r = .26, P = .02) and duration (r = .35, P = .002) were positively correlated with end time. Conversely, no relationship was observed between transition number, average lead time, or height reached in the curve and end time. Video analysis of TP races highlights the importance of quality transitions between riders, with preferably swift and short relays rather than longer lead times for faster race times.

Precise Object Tracking under Deformation

International Nuclear Information System (INIS)

Saad, M.H.

2010-01-01

The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results. xiiiThe precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high

Tracking of ball and players in beach volleyball videos.

Directory of Open Access Journals (Sweden)

Gabriel Gomez

Full Text Available This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points.

Tracking of Ball and Players in Beach Volleyball Videos

Science.gov (United States)

Gomez, Gabriel; Herrera López, Patricia; Link, Daniel; Eskofier, Bjoern

2014-01-01

This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points. PMID:25426936

Quantitative analysis of spider locomotion employing computer-automated video tracking

DEFF Research Database (Denmark)

Baatrup, E; Bayley, M

1993-01-01

The locomotor activity of adult specimens of the wolf spider Pardosa amentata was measured in an open-field setup, using computer-automated colour object video tracking. The x,y coordinates of the animal in the digitized image of the test arena were recorded three times per second during four...

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2015-05-01

Motion video analysis is a challenging task, especially in real-time applications. In most safety and security critical applications, a human observer is an obligatory part of the overall analysis system. Over the last years, substantial progress has been made in the development of automated image exploitation algorithms. Hence, we investigate how the benefits of automated video analysis can be integrated suitably into the current video exploitation systems. In this paper, a system design is introduced which strives to combine both the qualities of the human observer's perception and the automated algorithms, thus aiming to improve the overall performance of a real-time video analysis system. The system design builds on prior work where we showed the benefits for the human observer by means of a user interface which utilizes the human visual focus of attention revealed by the eye gaze direction for interaction with the image exploitation system; eye tracker-based interaction allows much faster, more convenient, and equally precise moving target acquisition in video images than traditional computer mouse selection. The system design also builds on prior work we did on automated target detection, segmentation, and tracking algorithms. Beside the system design, a first pilot study is presented, where we investigated how the participants (all non-experts in video analysis) performed in initializing an object tracking subsystem by selecting a target for tracking. Preliminary results show that the gaze + key press technique is an effective, efficient, and easy to use interaction technique when performing selection operations on moving targets in videos in order to initialize an object tracking function.

Tracking a convoy of multiple targets using acoustic sensor data

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Ji Xiong

2014-04-01

Full Text Available 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%.

PageRank tracker: from ranking to tracking.

Science.gov (United States)

Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

2014-06-01

Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

Linear array of photodiodes to track a human speaker for video recording

International Nuclear Information System (INIS)

DeTone, D; Neal, H; Lougheed, R

2012-01-01

Communication and collaboration using stored digital media has garnered more interest by many areas of business, government and education in recent years. This is due primarily to improvements in the quality of cameras and speed of computers. An advantage of digital media is that it can serve as an effective alternative when physical interaction is not possible. Video recordings that allow for viewers to discern a presenter's facial features, lips and hand motions are more effective than videos that do not. To attain this, one must maintain a video capture in which the speaker occupies a significant portion of the captured pixels. However, camera operators are costly, and often do an imperfect job of tracking presenters in unrehearsed situations. This creates motivation for a robust, automated system that directs a video camera to follow a presenter as he or she walks anywhere in the front of a lecture hall or large conference room. Such a system is presented. The system consists of a commercial, off-the-shelf pan/tilt/zoom (PTZ) color video camera, a necklace of infrared LEDs and a linear photodiode array detector. Electronic output from the photodiode array is processed to generate the location of the LED necklace, which is worn by a human speaker. The computer controls the video camera movements to record video of the speaker. The speaker's vertical position and depth are assumed to remain relatively constant– the video camera is sent only panning (horizontal) movement commands. The LED necklace is flashed at 70Hz at a 50% duty cycle to provide noise-filtering capability. The benefit to using a photodiode array versus a standard video camera is its higher frame rate (4kHz vs. 60Hz). The higher frame rate allows for the filtering of infrared noise such as sunlight and indoor lighting–a capability absent from other tracking technologies. The system has been tested in a large lecture hall and is shown to be effective.

Linear array of photodiodes to track a human speaker for video recording

Science.gov (United States)

DeTone, D.; Neal, H.; Lougheed, R.

2012-12-01

Communication and collaboration using stored digital media has garnered more interest by many areas of business, government and education in recent years. This is due primarily to improvements in the quality of cameras and speed of computers. An advantage of digital media is that it can serve as an effective alternative when physical interaction is not possible. Video recordings that allow for viewers to discern a presenter's facial features, lips and hand motions are more effective than videos that do not. To attain this, one must maintain a video capture in which the speaker occupies a significant portion of the captured pixels. However, camera operators are costly, and often do an imperfect job of tracking presenters in unrehearsed situations. This creates motivation for a robust, automated system that directs a video camera to follow a presenter as he or she walks anywhere in the front of a lecture hall or large conference room. Such a system is presented. The system consists of a commercial, off-the-shelf pan/tilt/zoom (PTZ) color video camera, a necklace of infrared LEDs and a linear photodiode array detector. Electronic output from the photodiode array is processed to generate the location of the LED necklace, which is worn by a human speaker. The computer controls the video camera movements to record video of the speaker. The speaker's vertical position and depth are assumed to remain relatively constant- the video camera is sent only panning (horizontal) movement commands. The LED necklace is flashed at 70Hz at a 50% duty cycle to provide noise-filtering capability. The benefit to using a photodiode array versus a standard video camera is its higher frame rate (4kHz vs. 60Hz). The higher frame rate allows for the filtering of infrared noise such as sunlight and indoor lighting-a capability absent from other tracking technologies. The system has been tested in a large lecture hall and is shown to be effective.

A digital video tracking system

Science.gov (United States)

Giles, M. K.

1980-01-01

The Real-Time Videotheodolite (RTV) was developed in connection with the requirement to replace film as a recording medium to obtain the real-time location of an object in the field-of-view (FOV) of a long focal length theodolite. Design philosophy called for a system capable of discriminatory judgment in identifying the object to be tracked with 60 independent observations per second, capable of locating the center of mass of the object projection on the image plane within about 2% of the FOV in rapidly changing background/foreground situations, and able to generate a predicted observation angle for the next observation. A description is given of a number of subsystems of the RTV, taking into account the processor configuration, the video processor, the projection processor, the tracker processor, the control processor, and the optics interface and imaging subsystem.

Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches

Directory of Open Access Journals (Sweden)

Zhen Jia

2008-12-01

Full Text Available This paper surveys the developments of last 10 years in the area of vision based target tracking for autonomous vehicles navigation. First, the motivations and applications of using vision based target tracking for autonomous vehicles navigation are presented in the introduction section. It can be concluded that it is very necessary to develop robust visual target tracking based navigation algorithms for the broad applications of autonomous vehicles. Then this paper reviews the recent techniques in three different categories: vision based target tracking for the applications of land, underwater and aerial vehicles navigation. Next, the increasing trends of using data fusion for visual target tracking based autonomous vehicles navigation are discussed. Through data fusion the tracking performance is improved and becomes more robust. Based on the review, the remaining research challenges are summarized and future research directions are investigated.

Određivanje daljine cilja pomoću video senzora i analiza uticaja grešaka i šuma merenja / Target range evaluation using video sensor and analysis of the influence of measurement noise and errors

Directory of Open Access Journals (Sweden)

Dragoslav Ugarak

2006-01-01

Full Text Available U radu je opisan matematički model određivanja daljine cilja obradom video snimaka u toku praćenja. Analizirani su doprinosi parametara koji utiču na veličinu grešaka i određene su vrednosti standardnog odstupanja. / This paper presents mathematical model of determining target range by analyzing video frame during the tracking. The contribution of effective parameters to accuracy are analyzed and values of standard deviation are determined.

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Yin Wang

2015-12-01

Full Text Available There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for the next hop with the highest potential bandwidth capacity to resume communication. Key to this strategy is that each node merely maintains two parameters that contain its historical bandwidth varying trend and then predict its near future bandwidth capacity. Then, the forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by the sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environments.

A discriminative structural similarity measure and its application to video-volume registration for endoscope three-dimensional motion tracking.

Science.gov (United States)

Luo, Xiongbiao; Mori, Kensaku

2014-06-01

Endoscope 3-D motion tracking, which seeks to synchronize pre- and intra-operative images in endoscopic interventions, is usually performed as video-volume registration that optimizes the similarity between endoscopic video and pre-operative images. The tracking performance, in turn, depends significantly on whether a similarity measure can successfully characterize the difference between video sequences and volume rendering images driven by pre-operative images. The paper proposes a discriminative structural similarity measure, which uses the degradation of structural information and takes image correlation or structure, luminance, and contrast into consideration, to boost video-volume registration. By applying the proposed similarity measure to endoscope tracking, it was demonstrated to be more accurate and robust than several available similarity measures, e.g., local normalized cross correlation, normalized mutual information, modified mean square error, or normalized sum squared difference. Based on clinical data evaluation, the tracking error was reduced significantly from at least 14.6 mm to 4.5 mm. The processing time was accelerated more than 30 frames per second using graphics processing unit.

Occlusion Handling in Videos Object Tracking: A Survey

International Nuclear Information System (INIS)

Lee, B Y; Liew, L H; Cheah, W S; Wang, Y C

2014-01-01

Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

Occlusion Handling in Videos Object Tracking: A Survey

Science.gov (United States)

Lee, B. Y.; Liew, L. H.; Cheah, W. S.; Wang, Y. C.

2014-02-01

Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

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

Science.gov (United States)

Amoozegar, Farid

1999-08-01

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

Development of a video image-based QA system for the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system

Energy Technology Data Exchange (ETDEWEB)

Ebe, Kazuyu, E-mail: nrr24490@nifty.com; Tokuyama, Katsuichi; Baba, Ryuta; Ogihara, Yoshisada; Ichikawa, Kosuke; Toyama, Joji [Joetsu General Hospital, 616 Daido-Fukuda, Joetsu-shi, Niigata 943-8507 (Japan); Sugimoto, Satoru [Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421 (Japan); Utsunomiya, Satoru; Kagamu, Hiroshi; Aoyama, Hidefumi [Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510 (Japan); Court, Laurence [The University of Texas MD Anderson Cancer Center, Houston, Texas 77030-4009 (United States)

2015-08-15

Purpose: To develop and evaluate a new video image-based QA system, including in-house software, that can display a tracking state visually and quantify the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system. Methods: Sixteen trajectories in six patients with pulmonary cancer were obtained with the ExacTrac in the Vero4DRT system. Motion data in the cranio–caudal direction (Y direction) were used as the input for a programmable motion table (Quasar). A target phantom was placed on the motion table, which was placed on the 2D ionization chamber array (MatriXX). Then, the 4D modeling procedure was performed on the target phantom during a reproduction of the patient’s tumor motion. A substitute target with the patient’s tumor motion was irradiated with 6-MV x-rays under the surrogate infrared system. The 2D dose images obtained from the MatriXX (33 frames/s; 40 s) were exported to in-house video-image analyzing software. The absolute differences in the Y direction between the center of the exposed target and the center of the exposed field were calculated. Positional errors were observed. The authors’ QA results were compared to 4D modeling function errors and gimbal motion errors obtained from log analyses in the ExacTrac to verify the accuracy of their QA system. The patients’ tumor motions were evaluated in the wave forms, and the peak-to-peak distances were also measured to verify their reproducibility. Results: Thirteen of sixteen trajectories (81.3%) were successfully reproduced with Quasar. The peak-to-peak distances ranged from 2.7 to 29.0 mm. Three trajectories (18.7%) were not successfully reproduced due to the limited motions of the Quasar. Thus, 13 of 16 trajectories were summarized. The mean number of video images used for analysis was 1156. The positional errors (absolute mean difference + 2 standard deviation) ranged from 0.54 to 1.55 mm. The error values differed by less than 1 mm from 4D modeling function errors

Development of a video image-based QA system for the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system

International Nuclear Information System (INIS)

Ebe, Kazuyu; Tokuyama, Katsuichi; Baba, Ryuta; Ogihara, Yoshisada; Ichikawa, Kosuke; Toyama, Joji; Sugimoto, Satoru; Utsunomiya, Satoru; Kagamu, Hiroshi; Aoyama, Hidefumi; Court, Laurence

2015-01-01

Purpose: To develop and evaluate a new video image-based QA system, including in-house software, that can display a tracking state visually and quantify the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system. Methods: Sixteen trajectories in six patients with pulmonary cancer were obtained with the ExacTrac in the Vero4DRT system. Motion data in the cranio–caudal direction (Y direction) were used as the input for a programmable motion table (Quasar). A target phantom was placed on the motion table, which was placed on the 2D ionization chamber array (MatriXX). Then, the 4D modeling procedure was performed on the target phantom during a reproduction of the patient’s tumor motion. A substitute target with the patient’s tumor motion was irradiated with 6-MV x-rays under the surrogate infrared system. The 2D dose images obtained from the MatriXX (33 frames/s; 40 s) were exported to in-house video-image analyzing software. The absolute differences in the Y direction between the center of the exposed target and the center of the exposed field were calculated. Positional errors were observed. The authors’ QA results were compared to 4D modeling function errors and gimbal motion errors obtained from log analyses in the ExacTrac to verify the accuracy of their QA system. The patients’ tumor motions were evaluated in the wave forms, and the peak-to-peak distances were also measured to verify their reproducibility. Results: Thirteen of sixteen trajectories (81.3%) were successfully reproduced with Quasar. The peak-to-peak distances ranged from 2.7 to 29.0 mm. Three trajectories (18.7%) were not successfully reproduced due to the limited motions of the Quasar. Thus, 13 of 16 trajectories were summarized. The mean number of video images used for analysis was 1156. The positional errors (absolute mean difference + 2 standard deviation) ranged from 0.54 to 1.55 mm. The error values differed by less than 1 mm from 4D modeling function errors

Using Genetic Algorithm for Eye Detection and Tracking in Video Sequence

Directory of Open Access Journals (Sweden)

Takuya Akashi

2007-04-01

Full Text Available We propose a high-speed size and orientation invariant eye tracking method, which can acquire numerical parameters to represent the size and orientation of the eye. In this paper, we discuss that high tolerance in human head movement and real-time processing that are needed for many applications, such as eye gaze tracking. The generality of the method is also important. We use template matching with genetic algorithm, in order to overcome these problems. A high speed and accuracy tracking scheme using Evolutionary Video Processing for eye detection and tracking is proposed. Usually, a genetic algorithm is unsuitable for a real-time processing, however, we achieved real-time processing. The generality of this proposed method is provided by the artificial iris template used. In our simulations, an eye tracking accuracy is 97.9% and, an average processing time of 28 milliseconds per frame.

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

OpenAIRE

Zhang, Shun; Huang, Jia-Bin; Lim, Jongwoo; Gong, Yihong; Wang, Jinjun; Ahuja, Narendra; Yang, Ming-Hsuan

2017-01-01

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in scale, pose, expression, illumination, and make-up. Existing multi-target tracking methods often use low-level features which are not sufficiently discriminative for identifying faces with such large appearance variations. In this paper, we tackle this problem by learning discriminative, video-specific face representa...

Research on infrared small-target tracking technology under complex background

Science.gov (United States)

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

2012-10-01

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

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

Science.gov (United States)

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

Manifolds for pose tracking from monocular video

Science.gov (United States)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

Straight-Line Target Tracking for Unmanned Surface Vehicles

Directory of Open Access Journals (Sweden)

Morten Breivik

2008-10-01

Full Text Available This paper considers the subject of straight-line target tracking for unmanned surface vehicles (USVs. Target-tracking represents motion control scenarios where no information about the target behavior is known in advance, i.e., the path that the target traverses is not defined apriori. Specifically, this work presents the design of a motion control system which enables an underactuated USV to track a target that moves in a straight line at high speed. The motion control system employs a guidance principle originally developed for interceptor missiles, as well as a novel velocity controller inspired by maneuverability and agility concepts found in fighter aircraft literature. The performance of the suggested design is illustrated through full-scale USV experiments in the Trondheimsfjord.

Active Multimodal Sensor System for Target Recognition and Tracking.

Science.gov (United States)

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

2017-06-28

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.

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

Science.gov (United States)

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.

OpenCV and TYZX : video surveillance for tracking.

Energy Technology Data Exchange (ETDEWEB)

He, Jim; Spencer, Andrew; Chu, Eric

2008-08-01

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

OpenCV and TYZX : video surveillance for tracking

International Nuclear Information System (INIS)

He, Jim; Spencer, Andrew; Chu, Eric

2008-01-01

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

Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling.

Science.gov (United States)

Xing, Junliang; Ai, Haizhou; Liu, Liwei; Lao, Shihong

2011-06-01

Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.

Bayesian target tracking based on particle filter

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

Target-type probability combining algorithms for multisensor tracking

Science.gov (United States)

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.

Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation

OpenAIRE

McCall, J C; Trivedi, Mohan Manubhai

2006-01-01

Driver-assistance systems that monitor driver intent, warn drivers of lane departures, or assist in vehicle guidance are all being actively considered. It is therefore important to take a critical look at key aspects of these systems, one of which is lane-position tracking. It is for these driver-assistance objectives that motivate the development of the novel "video-based lane estimation and tracking" (VioLET) system. The system is designed using steerable filters for robust and accurate lan...

Advances in top-down and bottom-up approaches to video-based camera tracking

OpenAIRE

Marimón Sanjuán, David

2007-01-01

Video-based camera tracking consists in trailing the three dimensional pose followed by a mobile camera using video as sole input. In order to estimate the pose of a camera with respect to a real scene, one or more three dimensional references are needed. Examples of such references are landmarks with known geometric shape, or objects for which a model is generated beforehand. By comparing what is seen by a camera with what is geometrically known from reality, it is possible to recover the po...

Advances in top-down and bottom-up approaches to video-based camera tracking

OpenAIRE

Marimón Sanjuán, David; Ebrahimi, Touradj

2008-01-01

Video-based camera tracking consists in trailing the three dimensional pose followed by a mobile camera using video as sole input. In order to estimate the pose of a camera with respect to a real scene, one or more three dimensional references are needed. Examples of such references are landmarks with known geometric shape, or objects for which a model is generated beforehand. By comparing what is seen by a camera with what is geometrically known from reality, it is possible to recover the po...

Precise object tracking under deformation

International Nuclear Information System (INIS)

Saad, M.H

2010-01-01

The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This frame-work focuses on the precise object tracking under deformation such as scaling , rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results.

Multiple instance learning tracking method with local sparse representation

KAUST Repository

Xie, Chengjun

2013-10-01

When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

Collaborative In-Network Processing for Target Tracking

Directory of Open Access Journals (Sweden)

Juan Liu

2003-03-01

Full Text Available This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

Mouse short- and long-term locomotor activity analyzed by video tracking software.

Science.gov (United States)

York, Jason M; Blevins, Neil A; McNeil, Leslie K; Freund, Gregory G

2013-06-20

Locomotor activity (LMA) is a simple and easily performed measurement of behavior in mice and other rodents. Improvements in video tracking software (VTS) have allowed it to be coupled to LMA testing, dramatically improving specificity and sensitivity when compared to the line crossings method with manual scoring. In addition, VTS enables high-throughput experimentation. While similar to automated video tracking used for the open field test (OFT), LMA testing is unique in that it allows mice to remain in their home cage and does not utilize the anxiogenic stimulus of bright lighting during the active phase of the light-dark cycle. Traditionally, LMA has been used for short periods of time (mins), while longer movement studies (hrs-days) have often used implanted transmitters and biotelemetry. With the option of real-time tracking, long-, like short-term LMA testing, can now be conducted using videography. Long-term LMA testing requires a specialized, but easily constructed, cage so that food and water (which is usually positioned on the cage top) does not obstruct videography. Importantly, videography and VTS allows for the quantification of parameters, such as path of mouse movement, that are difficult or unfeasible to measure with line crossing and/or biotelemetry. In sum, LMA testing coupled to VTS affords a more complete description of mouse movement and the ability to examine locomotion over an extended period of time.

Fusion-based multi-target tracking and localization for intelligent surveillance systems

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-05-08

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

A lightweight target-tracking scheme using wireless sensor network

International Nuclear Information System (INIS)

Kuang, Xing-hong; Shao, Hui-he; Feng, Rui

2008-01-01

This paper describes a lightweight target-tracking scheme using wireless sensor network, where randomly distributed sensor nodes take responsibility for tracking the moving target based on the acoustic sensing signal. At every localization interval, a backoff timer algorithm is performed to elect the leader node and determine the transmission order of the localization nodes. An adaptive active region size algorithm based on the node density is proposed to select the optimal nodes taking part in localization. An improved particle filter algorithm performed by the leader node estimates the target state based on the selected nodes' acoustic energy measurements. Some refinements such as optimal linear combination algorithm, residual resampling algorithm, Markov chain Monte Carlo method are introduced in the scheme to improve the tracking performance. Simulation results validate the efficiency of the proposed tracking scheme

Homography-based multiple-camera person-tracking

Science.gov (United States)

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

Video motion detection for physical security applications

International Nuclear Information System (INIS)

Matter, J.C.

1990-01-01

Physical security specialists have been attracted to the concept of video motion detection for several years. Claimed potential advantages included additional benefit from existing video surveillance systems, automatic detection, improved performance compared to human observers, and cost-effectiveness. In recent years, significant advances in image-processing dedicated hardware and image analysis algorithms and software have accelerated the successful application of video motion detection systems to a variety of physical security applications. Early video motion detectors (VMDs) were useful for interior applications of volumetric sensing. Success depended on having a relatively well-controlled environment. Attempts to use these systems outdoors frequently resulted in an unacceptable number of nuisance alarms. Currently, Sandia National Laboratories (SNL) is developing several advanced systems that employ image-processing techniques for a broader set of safeguards and security applications. The Target Cueing and Tracking System (TCATS), the Video Imaging System for Detection, Tracking, and Assessment (VISDTA), the Linear Infrared Scanning Array (LISA); the Mobile Intrusion Detection and Assessment System (MIDAS), and the Visual Artificially Intelligent Surveillance (VAIS) systems are described briefly

INSPTRAX - The Inspection Targeting, Planning and Tracking Database

Data.gov (United States)

U.S. Environmental Protection Agency — The INSPTRAX System tracks Air, RCRA, and Water inspection targeting, planning and tracking information. It is used by the the Air, RCRA, and Water programs to input...

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

Science.gov (United States)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

Analysis of Dead Time and Implementation of Smith Predictor Compensation in Tracking Servo Systems for Small Unmanned Aerial Vehicles

National Research Council Canada - National Science Library

Brashear , Jr, Thomas J

2005-01-01

.... Gimbaled video camera systems, designed at NPS, use two servo actuators to command line of sight orientation via serial controller while tracking a target and is termed Visual Based Target Tracking (VBTT...

Data fusion for target tracking and classification with wireless sensor network

Science.gov (United States)

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).

Persistent Aerial Tracking

KAUST Repository

Mueller, Matthias

2016-04-13

In this thesis, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the rst evaluation of many state of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. We also present a simulator that can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV "in the field", as well as, generate synthetic but photo-realistic tracking datasets with free ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator will be made publicly available to the vision community to further research in the area of object tracking from UAVs. Additionally, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by \\'handing over the camera\\' from one UAV to another. We integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

A Benchmark and Simulator for UAV Tracking

KAUST Repository

Mueller, Matthias; Smith, Neil; Ghanem, Bernard

2016-01-01

In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state-of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. The simulator can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV “in the field”, as well as, generate synthetic but photo-realistic tracking datasets with automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.

A Benchmark and Simulator for UAV Tracking

KAUST Repository

Mueller, Matthias

2016-09-16

In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state-of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. The simulator can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV “in the field”, as well as, generate synthetic but photo-realistic tracking datasets with automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.

RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System

Directory of Open Access Journals (Sweden)

Weihua Liu

2015-01-01

Full Text Available The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered. Toward this end, in the facet of hand tracking, a joint observation model with the hand cues of skin saliency, motion and depth is integrated into particle filter in order to move particles to local peak in the likelihood. The proposed hand tracking method, namely, salient skin, motion, and depth based particle filter (SSMD-PF, is capable of improving the tracking accuracy considerably, in the context of the signer performing the gesture toward the camera device and in front of moving, cluttered backgrounds. In the facet of gesture recognition, a shape-order context descriptor on the basis of shape context is introduced, which can describe the gesture in spatiotemporal domain. The efficient shape-order context descriptor can reveal the shape relationship and embed gesture sequence order information into descriptor. Moreover, the shape-order context leads to a robust score for gesture invariant. Our approach is complemented with experimental results on the settings of the challenging hand-signed digits datasets and American sign language dataset, which corroborate the performance of the novel techniques.

Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

Science.gov (United States)

Peikon, Ian D; Fitzsimmons, Nathan A; Lebedev, Mikhail A; Nicolelis, Miguel A L

2009-06-15

Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos

KAUST Repository

Wu, Baoyuan; Hu, Bao-Gang; Ji, Qiang

2016-01-01

Face clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face

Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

Moving target tracking through distributed clustering in directional sensor networks.

Science.gov (United States)

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.

Toward automating Hammersmith pulled-to-sit examination of infants using feature point based video object tracking.

Science.gov (United States)

Dogra, Debi P; Majumdar, Arun K; Sural, Shamik; Mukherjee, Jayanta; Mukherjee, Suchandra; Singh, Arun

2012-01-01

Hammersmith Infant Neurological Examination (HINE) is a set of tests used for grading neurological development of infants on a scale of 0 to 3. These tests help in assessing neurophysiological development of babies, especially preterm infants who are born before (the fetus reaches) the gestational age of 36 weeks. Such tests are often conducted in the follow-up clinics of hospitals for grading infants with suspected disabilities. Assessment based on HINE depends on the expertise of the physicians involved in conducting the examinations. It has been noted that some of these tests, especially pulled-to-sit and lateral tilting, are difficult to assess solely based on visual observation. For example, during the pulled-to-sit examination, the examiner needs to observe the relative movement of the head with respect to torso while pulling the infant by holding wrists. The examiner may find it difficult to follow the head movement from the coronal view. Video object tracking based automatic or semi-automatic analysis can be helpful in this case. In this paper, we present a video based method to automate the analysis of pulled-to-sit examination. In this context, a dynamic programming and node pruning based efficient video object tracking algorithm has been proposed. Pulled-to-sit event detection is handled by the proposed tracking algorithm that uses a 2-D geometric model of the scene. The algorithm has been tested with normal as well as marker based videos of the examination recorded at the neuro-development clinic of the SSKM Hospital, Kolkata, India. It is found that the proposed algorithm is capable of estimating the pulled-to-sit score with sensitivity (80%-92%) and specificity (89%-96%).

Video Views and Reviews: Golgi Export, Targeting, and Plasma Membrane Caveolae

Science.gov (United States)

Watters, Christopher

2004-01-01

In this article, the author reviews videos from "Molecular Biology of the Cell (MBC)" depicting various aspects of plasma membrane (PM) dynamics, including the targeting of newly synthesized components and the organization of those PM invaginations called caveolae. The papers accompanying these videos describe, respectively, the constitutive…

Super-resolution imaging applied to moving object tracking

Science.gov (United States)

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

2017-10-01

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

Through-Wall Multiple Targets Vital Signs Tracking Based on VMD Algorithm

Directory of Open Access Journals (Sweden)

Jiaming Yan

2016-08-01

Full Text Available Targets located at the same distance are easily neglected in most through-wall multiple targets detecting applications which use the single-input single-output (SISO ultra-wideband (UWB radar system. In this paper, a novel multiple targets vital signs tracking algorithm for through-wall detection using SISO UWB radar has been proposed. Taking advantage of the high-resolution decomposition of the Variational Mode Decomposition (VMD based algorithm, the respiration signals of different targets can be decomposed into different sub-signals, and then, we can track the time-varying respiration signals accurately when human targets located in the same distance. Intensive evaluation has been conducted to show the effectiveness of our scheme with a 0.15 m thick concrete brick wall. Constant, piecewise-constant and time-varying vital signs could be separated and tracked successfully with the proposed VMD based algorithm for two targets, even up to three targets. For the multiple targets’ vital signs tracking issues like urban search and rescue missions, our algorithm has superior capability in most detection applications.

A game theory approach to target tracking in sensor networks.

Science.gov (United States)

Gu, Dongbing

2011-02-01

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

Target tracking using DMLC for volumetric modulated arc therapy: A simulation study

Energy Technology Data Exchange (ETDEWEB)

Sun Baozhou; Rangaraj, Dharanipathy; Papiez, Lech; Oddiraju, Swetha; Yang Deshan; Li, H. Harold [Department of Radiation Oncology, School of Medicine, Washington University, 4921 Parkview Place, St. Louis, Missouri 63110 (United States); Department of Radiation Oncology, Southwestern Medical Center, University of Texas, Dallas, Texas 75390 (United States); Department of Radiation Oncology, School of Medicine, Washington University, 4921 Parkview Place, St. Louis, Missouri 63110 (United States)

2010-12-15

Purpose: Target tracking using dynamic multileaf collimator (DMLC) is a promising approach for intrafraction motion management in radiation therapy. The purpose of this work is to develop a DMLC tracking algorithm capable of delivering volumetric-modulated arc therapy (VMAT) to the targets that experience two-dimensional (2D) rigid motion in the beam's eye view. Methods: The problem of VMAT delivery to moving targets is formulated as a control problem with constraints. The relationships between gantry speed, gantry acceleration, MLC leaf-velocity, dose rate, and target motion are derived. An iterative search algorithm is developed to find numerical solutions for efficient delivery of a specific VMAT plan to the moving target using 2D DMLC tracking. The delivery of five VMAT lung plans is simulated. The planned and delivered fluence maps in the target-reference frame are calculated and compared. Results: The simulation demonstrates that the 2D tracking algorithm is capable of delivering the VMAT plan to a moving target fast and accurately without violating the machine constraints and the integrity of the treatment plan. The average delivery time is only 29 s longer than that of no-tracking delivery, 101 versus 72 s, respectively. The fluence maps are normalized to 200 MU and the average root-mean-square error between the desired and the delivered fluence is 2.1 MU, compared to 14.8 MU for no-tracking and 3.6 MU for one-dimensional tracking. Conclusions: A locally optimal MLC tracking algorithm for VMAT delivery is proposed, aiming at shortest delivery time while maintaining treatment plan invariant. The inconsequential increase of treatment time due to DMLC tracking is clinically desirable, which makes VMAT with DMLC tracking attractive in treating moving tumors.

The Bering Target Tracking Instrumentation

DEFF Research Database (Denmark)

Denver, Troelz; Jørgensen, John Leif; Betto, Maurizio

2003-01-01

The key science instrument on the Bering satellite mission is a relative small telescope with an entrance aperture of 300 mm and a focal length between 500 and 1000 mm. The detection of potential targets is performed by one of the target scanning advanced stellar compasses (ASCs). This procedure...... results in a simple prioritized list of right ascension, declination, proper motion and intensity of each prospective target. The telescope itself has a dedicated ASC Camera Head Unit (CHU) mounted on the secondary mirror, largely co-aligned with the telescope. This CHU accurately determines the telescope......'s pointing direction. To achieve fast tracking over a large solid angle, the telescope pointing is achieved by means of a folding mirror in the optical pathway. When a prospective target approaches the telescope FOV, the ASC on the secondary will guide the folding mirror into position such that the target...

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

Science.gov (United States)

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.

Improving Global Multi-target Tracking with Local Updates

DEFF Research Database (Denmark)

Milan, Anton; Gade, Rikke; Dick, Anthony

2014-01-01

-target tracker, if they result in a reduction in the global cost function. Since tracking failures typically arise when targets become occluded, we propose a local data association scheme to maintain the target identities in these situations. We demonstrate a reduction of up to 50% in the global cost function...

Moving Target Tracking through Distributed Clustering in Directional Sensor Networks

Directory of Open Access Journals (Sweden)

Asma Enayet

2014-12-01

Full Text Available 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.

Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

Institute of Scientific and Technical Information of China (English)

YU Wenyong

2006-01-01

A control strategy for real-time target tracking for wheeled mobile robots is presented. Using a modified Kalman filter for environment perception, a novel tracking control law derived from Lyapunov stability theory is introduced. Tuning of linear velocity and angular velocity with mechanical constraints is applied. The proposed control system can simultaneously solve the target trajectory prediction, real-time tracking, and posture regulation problems of a wheeled mobile robot. Experimental results illustrate the effectiveness of the proposed tracking control laws.

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

Science.gov (United States)

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.

Random Scenario Generation for a Multiple Target Tracking Environment Evaluation

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar

2006-01-01

, which were normally crossing targets, was to test the efficiency of the track splitting algorithm for different situations. However this approach only gives a measure of performance for a specific, possibly unrealistic, scenario and it was felt appropriate to develop procedures that would enable a more...... general performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the track splitting algorithm using Kalman filters is used and a couple of tracking performance parameters are computed to investigate such random scenarios....

Tracking target objects orbiting earth using satellite-based telescopes

Science.gov (United States)

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.

Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images.

Science.gov (United States)

Kim, Sohyun; Jang, Gwang-Il; Kim, Sungho; Kim, Junmo

2018-03-27

This paper proposes the automatic coast mode tracking of centroid trackers for infrared images to overcome the target occlusion status. The centroid tracking method, using only the brightness information of an image, is still widely used in infrared imaging tracking systems because it is difficult to extract meaningful features from infrared images. However, centroid trackers are likely to lose the track because they are highly vulnerable to screened status by the clutter or background. Coast mode, one of the tracking modes, maintains the servo slew rate with the tracking rate right before the loss of track. The proposed automatic coast mode tracking method makes decisions regarding entering coast mode by the prediction of target occlusion and tries to re-lock the target and resume the tracking after blind time. This algorithm comprises three steps. The first step is the prediction process of the occlusion by checking both matters which have target-likelihood brightness and which may screen the target despite different brightness. The second step is the process making inertial tracking commands to the servo. The last step is the process of re-locking a target based on the target modeling of histogram ratio. The effectiveness of the proposed algorithm is addressed by presenting experimental results based on computer simulation with various test imagery sequences compared to published tracking algorithms. The proposed algorithm is tested under a real environment with a naval electro-optical tracking system (EOTS) and airborne EO/IR system.

Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images

Directory of Open Access Journals (Sweden)

Sohyun Kim

2018-03-01

Full Text Available This paper proposes the automatic coast mode tracking of centroid trackers for infrared images to overcome the target occlusion status. The centroid tracking method, using only the brightness information of an image, is still widely used in infrared imaging tracking systems because it is difficult to extract meaningful features from infrared images. However, centroid trackers are likely to lose the track because they are highly vulnerable to screened status by the clutter or background. Coast mode, one of the tracking modes, maintains the servo slew rate with the tracking rate right before the loss of track. The proposed automatic coast mode tracking method makes decisions regarding entering coast mode by the prediction of target occlusion and tries to re-lock the target and resume the tracking after blind time. This algorithm comprises three steps. The first step is the prediction process of the occlusion by checking both matters which have target-likelihood brightness and which may screen the target despite different brightness. The second step is the process making inertial tracking commands to the servo. The last step is the process of re-locking a target based on the target modeling of histogram ratio. The effectiveness of the proposed algorithm is addressed by presenting experimental results based on computer simulation with various test imagery sequences compared to published tracking algorithms. The proposed algorithm is tested under a real environment with a naval electro-optical tracking system (EOTS and airborne EO/IR system.

TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

Directory of Open Access Journals (Sweden)

C. Jehan

2016-06-01

Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

An improved multi-domain convolution tracking algorithm

Science.gov (United States)

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.

An Integral Model for Target Tracking Based on the Use of a WSN

Directory of Open Access Journals (Sweden)

Pietro Manzoni

2013-06-01

Full Text Available The use of wireless sensor networks (WSN in tracking applications is growing at a fast pace. In these applications, the sensor nodes discover, monitor and track an event or target object. A significant number of proposals relating the use of WSNs for target tracking have been published to date. However, they either focus on the tracking algorithm or on the communication protocol, and none of them address the problem integrally. In this paper, a comprehensive proposal for target detection and tracking is discussed. We introduce a tracking algorithm to detect and estimate a target location. Moreover, we introduce a low-overhead routing protocol to be used along with our tracking algorithm. The proposed algorithm has low computational complexity and has been designed considering the use of a mobile sink while generating minimal delay and packet loss. We also discuss the results of the evaluation of the proposed algorithms.

EXPERIMENTAL TARGET INJECTION AND TRACKING SYSTEM CONSTRUCTION AND SINGLE SHOT TESTING

International Nuclear Information System (INIS)

PETZOLDT, R.W.; ALEXANDER, N.B.; DRAKE, T.J.; GOODIN, D.T; JONESTRACK, K; VERMILLION, B.A

2003-01-01

Targets must be injected into an IFE power plant at a rate of approximately 5 to 10 Hz. Targets must be tracked very accurately to allow driver beams to be aligned with defined points on the targets with accuracy ± 150 (micro)m for indirect drive and ± 20 (micro)m for direct drive. An experimental target injection and tracking system has been constructed at General Atomics. The injector system will be used as a tool for testing the survivability of various target designs and provide feedback to the target designers. Helium gas propels the targets down an 8 m gun barrel up to 400 m/s. Direct-drive targets are protected in the barrel by sabots that are spring loaded to separate into two halves after acceleration. A sabot deflector directs the sabot halves away from the target injection path. Targets will be optically tracked with laser beams and line-scan cameras. Target position and arrival time will be predicted in real time based on early target position measurements. The system installation will be described. System testing to overcome excessive projectile wear and debris in the gun barrel is presented

A ground moving target emergency tracking method for catastrophe rescue

Science.gov (United States)

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

Robust Tracking with Discriminative Ranking Middle-Level Patches

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Hong Liu

2014-04-01

Full Text Available The appearance model has been shown to be essential for robust visual tracking since it is the basic criterion to locating targets in video sequences. Though existing tracking-by-detection algorithms have shown to be greatly promising, they still suffer from the drift problem, which is caused by updating appearance models. In this paper, we propose a new appearance model composed of ranking middle-level patches to capture more object distinctiveness than traditional tracking-by-detection models. Targets and backgrounds are represented by both low-level bottom-up features and high-level top-down patches, which can compensate each other. Bottom-up features are defined at the pixel level, and each feature gets its discrimination score through selective feature attention mechanism. In top-down feature extraction, rectangular patches are ranked according to their bottom-up discrimination scores, by which all of them are clustered into irregular patches, named ranking middle-level patches. In addition, at the stage of classifier training, the online random forests algorithm is specially refined to reduce drifting problems. Experiments on challenging public datasets and our test videos demonstrate that our approach can effectively prevent the tracker drifting problem and obtain competitive performance in visual tracking.

Ballistic target tracking algorithm based on improved particle filtering

Science.gov (United States)

Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

2015-10-01

Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

Feature Quantization and Pooling for Videos

Science.gov (United States)

2014-05-01

less vertical motion. The exceptions are videos from the classes of biking (mainly due to the camera tracking fast bikers), jumping on a trampoline ...tracking the bikers; the jumping videos, featuring people on trampolines , the swing videos, which are usually recorded in profile view, and the walking

Analysis of LFM-waveform Libraries for Cognitive Tracking Maneuvering Targets

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Wang Hongyan

2016-01-01

Full Text Available Based on the idea of the waveform agility in cognitive radars，the waveform libraries for maneuvering target tracking are discussed. LFM-waveform libraries are designed according to different combinations of chirp parameters and FrFT rotation angles. By applying the interact multiple model (IMM algorithm in tracking maneuvering targets, transmitted waveform is called real time from the LFM-waveform libraries. The waveforms are selected from the library according to the criterion of maximum mutual information between the current state of knowledge of the model and the measurement. Simulation results show that waveform library containing certain amount LFM-waveforms can improve the performance of cognitive tracking radar.

A Bayesian solution to multi-target tracking problems with mixed labelling

NARCIS (Netherlands)

Aoki, E.H.; Boers, Y.; Svensson, Lennart; Mandal, Pranab K.; Bagchi, Arunabha

In Multi-Target Tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastly covered in literature and has been previously formulated using Bayesian recursion. However, the existing literature lacks an appropriate measure of uncertainty related to the assigned labels which

Final Report: Non-Visible, Automated Target Acquisition and Tracking

Energy Technology Data Exchange (ETDEWEB)

Ziock, Klaus-Peter [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fabris, Lorenzo [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Goddard, James K. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hornback, Donald Eric [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Karnowski, Thomas Paul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Newby, Jason [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2016-10-01

The Roadside Tracker (RST) represents a new approach to radiation portal monitors. It uses a combination of gamma-ray and visible-light imaging to localize gamma-ray radiation sources to individual vehicles in free-flowing, multi-lane traffic. Deployed as two trailers that are parked on either side of the roadway (Fig. 1); the RST scans passing traffic with two large gamma-ray imagers, one mounted in each trailer. The system compensates for vehicle motion through the imager’s fields of view by using automated target acquisition and tracking (TAT) software applied to a stream of video images. Once a vehicle has left the field of view, the radiation image of that vehicle is analyzed for the presence of a source, and if one is found, an alarm is sounded. The gamma-ray image is presented to the operator together with the video image of the traffic stream when the vehicle was approximately closest to the system (Fig. 2). The offending vehicle is identified with a bounding box to distinguish it from other vehicles that might be present at the same time. The system was developed under a previous grant from the Department of Homeland Security’s (DHS’s) Domestic Nuclear Detection Office (DNDO). This report documents work performed with follow-on funding from DNDO to further advance the development of the RST. Specifically, the primary thrust was to extend the performance envelope of the system by replacing the visible-light video cameras used by the TAT software with sensors that would allow operation at night and during inclement weather. In particular, it was desired to allow operation after dark without requiring external lighting. As part of this work, the system software was also upgraded to allow the use of 64-bit computers, the current generation operating system (OS), software development environment (Windows 7 vs. Windows XP, and current Visual Studio.Net), and improved software version controls (GIT vs. Source Safe.) With the upgraded performance allowed by

A Single Unexpected Change in Target- but Not Distractor Motion Impairs Multiple Object Tracking

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Hauke S. Meyerhoff

2013-02-01

Full Text Available Recent research addresses the question whether motion information of multiple objects contributes to maintaining a selection of objects across a period of motion. Here, we investigate whether target and/or distractor motion information is used during attentive tracking. We asked participants to track four objects and changed either the motion direction of targets, the motion direction of distractors, neither, or both during a brief flash in the middle of a tracking interval. We observed that a single direction change of targets is sufficient to impair tracking performance. In contrast, changing the motion direction of distractors had no effect on performance. This indicates that target- but not distractor motion information is evaluated during tracking.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Models and Algorithms for Tracking Target with Coordinated Turn Motion

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Xianghui Yuan

2014-01-01

Full Text Available Tracking target with coordinated turn (CT motion is highly dependent on the models and algorithms. First, the widely used models are compared in this paper—coordinated turn (CT model with known turn rate, augmented coordinated turn (ACT model with Cartesian velocity, ACT model with polar velocity, CT model using a kinematic constraint, and maneuver centered circular motion model. Then, in the single model tracking framework, the tracking algorithms for the last four models are compared and the suggestions on the choice of models for different practical target tracking problems are given. Finally, in the multiple models (MM framework, the algorithm based on expectation maximization (EM algorithm is derived, including both the batch form and the recursive form. Compared with the widely used interacting multiple model (IMM algorithm, the EM algorithm shows its effectiveness.

Acquisition, tracking, and pointing IV; Proceedings of the Meeting, Orlando, FL, Apr. 19, 20, 1990

Science.gov (United States)

Gowrinathan, Sankaran

1990-09-01

Various papers on acquisition, tracking, and pointing are presented. Individual topics addressed include: backlash control techniques in geared servo mechanics; optical fiber and photodetector array for robotic seam tracking; star trackers for spacecraft applications; Starfire optical range tracking system for the 1.5 m telescope; real-time video image centroid tracker; optical alignment with a beamwalk system; line-of-sight stabilization requirements for target tracking system; image quality with narrow beam illumination in an active tracking system; IR sensor data fusion for target detection, identification, and tracking; target location and pointing algorithm for a three-axis stabilized line scanner. Also discussed are: adaptive control system techniques applied to inertial stabilization systems; supervisory control of electrooptic tracking and pointing; position loop compensation for flex-pivot-mounted gimbal stabilization systems; advanced testing methods for acquisition, tracking, and pointing; development of kinmatics for gimballed mirror systems.

Color and motion-based particle filter target tracking in a network of overlapping cameras with multi-threading and GPGPU Rastreo de objetivos por medio de filtros de partículas basados en color y movimiento en una red de cámaras con multi-hilo y GPGPU

Directory of Open Access Journals (Sweden)

Jorge Francisco Madrigal Díaz

2013-03-01

Full Text Available This paper describes an efficient implementation of multiple-target multiple-view tracking in video-surveillance sequences. It takes advantage of the capabilities of multiple core Central Processing Units (CPUs and of graphical processing units under the Compute Unifie Device Arquitecture (CUDA framework. The principle of our algorithm is 1 in each video sequence, to perform tracking on all persons to track by independent particle filters and 2 to fuse the tracking results of all sequences. Particle filters belong to the category of recursive Bayesian filters. They update a Monte-Carlo representation of the posterior distribution over the target position and velocity. For this purpose, they combine a probabilistic motion model, i.e. prior knowledge about how targets move (e.g. constant velocity and a likelihood model associated to the observations on targets. At this first level of single video sequences, the multi-threading library Threading Buildings Blocks (TBB has been used to parallelize the processing of the per-target independent particle filters. Afterwards at the higher level, we rely on General Purpose Programming on Graphical Processing Units (generally termed as GPGPU through CUDA in order to fuse target-tracking data collected on multiple video sequences, by solving the data association problem. Tracking results are presented on various challenging tracking datasets.Este artículo describe una implementación eficiente de un algoritmo de seguimiento de múlti­ples objetivos en múltiples vistas en secuencias de video vigilancia. Aprovecha las capacidades de las Unidades Centrales de Procesamiento (CPUs, por sus siglas en inglés de múltiples núcleos y de las unidades de procesamiento gráfico, bajo el entorno de desarrollo de Arquitec­tura Unificada de Dispositivos de Cómputo (CUDA, por sus siglas en inglés. El principio de nuestro algoritmo es: 1 aplicar el seguimiento visual en cada secuencia de video sobre todas las

Moving Shadow Detection in Video Using Cepstrum

Directory of Open Access Journals (Sweden)

Fuat Cogun

2013-01-01

Full Text Available Moving shadows constitute problems in various applications such as image segmentation and object tracking. The main cause of these problems is the misclassification of the shadow pixels as target pixels. Therefore, the use of an accurate and reliable shadow detection method is essential to realize intelligent video processing applications. In this paper, a cepstrum-based method for moving shadow detection is presented. The proposed method is tested on outdoor and indoor video sequences using well-known benchmark test sets. To show the improvements over previous approaches, quantitative metrics are introduced and comparisons based on these metrics are made.

Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

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Jing Liu

2012-01-01

Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

Real-Time FPGA-Based Object Tracker with Automatic Pan-Tilt Features for Smart Video Surveillance Systems

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Sanjay Singh

2017-05-01

Full Text Available The design of smart video surveillance systems is an active research field among the computer vision community because of their ability to perform automatic scene analysis by selecting and tracking the objects of interest. In this paper, we present the design and implementation of an FPGA-based standalone working prototype system for real-time tracking of an object of interest in live video streams for such systems. In addition to real-time tracking of the object of interest, the implemented system is also capable of providing purposive automatic camera movement (pan-tilt in the direction determined by movement of the tracked object. The complete system, including camera interface, DDR2 external memory interface controller, designed object tracking VLSI architecture, camera movement controller and display interface, has been implemented on the Xilinx ML510 (Virtex-5 FX130T FPGA Board. Our proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576 resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object.

Video stimuli reduce object-directed imitation accuracy: a novel two-person motion-tracking approach.

Science.gov (United States)

Reader, Arran T; Holmes, Nicholas P

2015-01-01

Imitation is an important form of social behavior, and research has aimed to discover and explain the neural and kinematic aspects of imitation. However, much of this research has featured single participants imitating in response to pre-recorded video stimuli. This is in spite of findings that show reduced neural activation to video vs. real life movement stimuli, particularly in the motor cortex. We investigated the degree to which video stimuli may affect the imitation process using a novel motion tracking paradigm with high spatial and temporal resolution. We recorded 14 positions on the hands, arms, and heads of two individuals in an imitation experiment. One individual freely moved within given parameters (moving balls across a series of pegs) and a second participant imitated. This task was performed with either simple (one ball) or complex (three balls) movement difficulty, and either face-to-face or via a live video projection. After an exploratory analysis, three dependent variables were chosen for examination: 3D grip position, joint angles in the arm, and grip aperture. A cross-correlation and multivariate analysis revealed that object-directed imitation task accuracy (as represented by grip position) was reduced in video compared to face-to-face feedback, and in complex compared to simple difficulty. This was most prevalent in the left-right and forward-back motions, relevant to the imitator sitting face-to-face with the actor or with a live projected video of the same actor. The results suggest that for tasks which require object-directed imitation, video stimuli may not be an ecologically valid way to present task materials. However, no similar effects were found in the joint angle and grip aperture variables, suggesting that there are limits to the influence of video stimuli on imitation. The implications of these results are discussed with regards to previous findings, and with suggestions for future experimentation.

Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Juan Feng

2016-01-01

Full Text Available In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

Method for Multiple Targets Tracking in Cognitive Radar Based on Compressed Sensing

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Yang Jun

2016-02-01

Full Text Available A multiple targets cognitive radar tracking method based on Compressed Sensing (CS is proposed. In this method, the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario. The echo signal is sparsely expressed. The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely, and subsequently, the restruction of measurement signal under the down-sampling condition is realized. On the receiving end, after considering that the problems that traditional particle filter suffers from degeneracy, and require a large number of particles, the particle swarm optimization particle filter is used to track the targets. On the transmitting end, the Posterior Cramér-Rao Bounds (PCRB of the tracking accuracy is deduced, and the radar waveform parameters are further cognitively designed using PCRB. Simulation results show that the proposed method can not only reduce the data quantity, but also provide a better tracking performance compared with traditional method.

Video-Guidance Design for the DART Rendezvous Mission

Science.gov (United States)

Ruth, Michael; Tracy, Chisholm

2004-01-01

NASA's Demonstration of Autonomous Rendezvous Technology (DART) mission will validate a number of different guidance technologies, including state-differenced GPS transfers and close-approach video guidance. The video guidance for DART will employ NASA/Marshall s Advanced Video Guidance Sensor (AVGS). This paper focuses on the terminal phase of the DART mission that includes close-approach maneuvers under AVGS guidance. The closed-loop video guidance design for DART is driven by a number of competing requirements, including a need for maximizing tracking bandwidths while coping with measurement noise and the need to minimize RCS firings. A range of different strategies for attitude control and docking guidance have been considered for the DART mission, and design decisions are driven by a goal of minimizing both the design complexity and the effects of video guidance lags. The DART design employs an indirect docking approach, in which the guidance position targets are defined using relative attitude information. Flight simulation results have proven the effectiveness of the video guidance design.

Target injection and tracking for inertial fusion energy

Energy Technology Data Exchange (ETDEWEB)

Petzoldt, R.W. [Lawrence Livermore National Lab., CA (United States); Moir, R.W. [Lawrence Livermore National Lab., CA (United States)

1996-11-01

In an inertial fusion power plant, several cryogenic targets must be injected each second into a reaction chamber with speeds of about 100 m s{sup -1}. This speed can be achieved with an acceleration in the range from 1000 to 10 000 m s{sup -2}. The total accuracy of driver beam pointing and target position prediction must be less than {+-}0.6 mm for a 3 mm beam spot radius. A 0.1 {mu}m thick dual membrane supporting the capsule in the hohlraum will allow nearly 2000 m s{sup -2} acceleration. The strength of frozen DT in the capsule is calculated to allow acceleration in excess of 10 000 m s{sup -2} if the DT temperature is less than 17 K. A gas gun is the preferred device for injecting indirect drive targets owing to its simplicity and proven reliability. The amount of gas required for each target (about 10-100 mg) is acceptable. A revolver loading mechanism is recommendced with a cam-operated poppet valve to control the gas flow. Slots near the muzzle of the gun barrel are recommended to vent gas and thereby to improve accuracy and to aid gas pumping. Optical target tracking and electronic timing devices can predict target arrival time with sufficient accuracy. Target steering by electrostatic deflection of the in-flight target is shown to be feasible and would avoid the need to point the beams actively. Calculations show that induced tumble from electrostatically steering the target is not excessive. An experiment has been designed to develop target injection and to verify the predicted accuracy of sequential injection and tracking of multiple targets. (orig.)

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

Directory of Open Access Journals (Sweden)

Meiqin Liu

2017-12-01

Full Text Available 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.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

OpenAIRE

Kia, Chua; Arshad, Mohd Rizal

2006-01-01

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system ...

Efficient characterization of labeling uncertainty in closely-spaced targets tracking

NARCIS (Netherlands)

Moreno Leon, Carlos; Moreno Leon, Carlos; Driessen, Hans; Mandal, Pranab K.

2016-01-01

In this paper we propose a novel solution to the labeled multi-target tracking problem. The method presented is specially effective in scenarios where the targets have once moved in close proximity. When this is the case, disregarding the labeling uncertainty present in a solution (after the targets

Estimation of Radar Cross Section of a Target under Track

Directory of Open Access Journals (Sweden)

Hong Sun-Mog

2010-01-01

Full Text Available In allocating radar beam for tracking a target, it is attempted to maintain the signal-to-noise ratio (SNR of signal returning from the illuminated target close to an optimum value for efficient track updates. An estimate of the average radar cross section (RCS of the target is required in order to adjust transmitted power based on the estimate such that a desired SNR can be realized. In this paper, a maximum-likelihood (ML approach is presented for estimating the average RCS, and a numerical solution to the approach is proposed based on a generalized expectation maximization (GEM algorithm. Estimation accuracy of the approach is compared to that of a previously reported procedure.

Event-triggered cooperative target tracking in wireless sensor networks

Directory of Open Access Journals (Sweden)

Lu Kelin

2016-10-01

Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

Development of target-tracking algorithms using neural network

Energy Technology Data Exchange (ETDEWEB)

Park, Dong Sun; Lee, Joon Whaoan; Yoon, Sook; Baek, Seong Hyun; Lee, Myung Jae [Chonbuk National University, Chonjoo (Korea)

1998-04-01

The utilization of remote-control robot system in atomic power plants or nuclear-related facilities grows rapidly, to protect workers form high radiation environments. Such applications require complete stability of the robot system, so that precisely tracking the robot is essential for the whole system. This research is to accomplish the goal by developing appropriate algorithms for remote-control robot systems. A neural network tracking system is designed and experimented to trace a robot Endpoint. This model is aimed to utilized the excellent capabilities of neural networks; nonlinear mapping between inputs and outputs, learning capability, and generalization capability. The neural tracker consists of two networks for position detection and prediction. Tracking algorithms are developed and experimented for the two models. Results of the experiments show that both models are promising as real-time target-tracking systems for remote-control robot systems. (author). 10 refs., 47 figs.

Real-time vehicle detection and tracking in video based on faster R-CNN

Science.gov (United States)

Zhang, Yongjie; Wang, Jian; Yang, Xin

2017-08-01

Vehicle detection and tracking is a significant part in auxiliary vehicle driving system. Using the traditional detection method based on image information has encountered enormous difficulties, especially in complex background. To solve this problem, a detection method based on deep learning, Faster R-CNN, which has very high detection accuracy and flexibility, is introduced. An algorithm of target tracking with the combination of Camshift and Kalman filter is proposed for vehicle tracking. The computation time of Faster R-CNN cannot achieve realtime detection. We use multi-thread technique to detect and track vehicle by parallel computation for real-time application.

IMRT delivery to a moving target by dynamic MLC tracking: delivery for targets moving in two dimensions in the beam's eye view

International Nuclear Information System (INIS)

McQuaid, D; Webb, S

2006-01-01

A new modification of the dynamic multileaf collimator (dMLC) delivery technique for intensity-modulated therapy (IMRT) is outlined. This technique enables the tracking of a target moving through rigid-body translations in a 2D trajectory in the beam's eye view. The accuracy of the delivery versus that of deliveries with no tracking and of 1D tracking techniques is quantified with clinically derived intensity-modulated beams (IMBs). Leaf trajectories calculated in the target-reference frame were iteratively synchronized assuming regular target motion. This allowed the leaves defined in the lab-reference frame to simultaneously follow the target motion and to deliver the required IMB without violation of the leaf maximum-velocity constraint. The leaves are synchronized until the gradient of the leaf position at every instant is less than a calculated maximum. The delivered fluence in the target-reference frame was calculated with a simple primary-fluence model. The new 2D tracking technique was compared with the delivered fluence produced by no-tracking deliveries and by 1D tracking deliveries for 33 clinical IMBs. For the clinical IMBs normalized to a maximum fluence of 200 MUs, the rms difference between the desired and the delivered IMB was 15.6 ± 3.3 MU for the case of a no-tracking delivery, 7.9 ± 1.6 MU for the case where only the primary component of motion was corrected and 5.1 ± 1.1 MU for the 2D tracking delivery. The residual error is due to interpolation and sampling effects. The 2D tracking delivery technique requires an increase in the delivery time evaluated as between 0 and 50% of the unsynchronized delivery time for each beam with a mean increase of 13% for the IMBs tested. The 2D tracking dMLC delivery technique allows an optimized IMB to be delivered to moving targets with increased accuracy and with acceptable increases in delivery time. When combined with real-time knowledge of the target motion at delivery time, this technique facilitates

Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

Directory of Open Access Journals (Sweden)

Michael Rudzsky

2008-01-01

Full Text Available We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.

A high precision video-electronic measuring system for use with solid state track detectors

International Nuclear Information System (INIS)

Schott, J.U.; Schopper, E.; Staudte, R.

1976-01-01

A video-electronic image analyzing system Quantimet 720 has been modified to meet the requirements of the measurement of tracks of nuclear particles in solid state track detectors with resulting improvement of precision, speed, and the elimination of subjective influences. A microscope equipped with an automatic XY stage projects the image onto the cathode of a vidicon-amplifier. Within the TV-picture generated, characterized by the coordinate XY in the specimen, we determine coordinates xy of events by setting cross lines on the screen which correspond to a digital accuracy of 0.1 μm at the position of the object. Automatic movement in Z-direction can be performed by stepping motor and measured electronically, or continously by setting electric voltage on a piezostrictive support of the objective. (orig.) [de

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

Science.gov (United States)

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Spatio-temporal features for tracking and quadruped/biped discrimination

Science.gov (United States)

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.

Classification of Birds and Bats Using Flight Tracks

Energy Technology Data Exchange (ETDEWEB)

Cullinan, Valerie I.; Matzner, Shari; Duberstein, Corey A.

2015-05-01

Classification of birds and bats that use areas targeted for offshore wind farm development and the inference of their behavior is essential to evaluating the potential effects of development. The current approach to assessing the number and distribution of birds at sea involves transect surveys using trained individuals in boats or airplanes or using high-resolution imagery. These approaches are costly and have safety concerns. Based on a limited annotated library extracted from a single-camera thermal video, we provide a framework for building models that classify birds and bats and their associated behaviors. As an example, we developed a discriminant model for theoretical flight paths and applied it to data (N = 64 tracks) extracted from 5-min video clips. The agreement between model- and observer-classified path types was initially only 41%, but it increased to 73% when small-scale jitter was censored and path types were combined. Classification of 46 tracks of bats, swallows, gulls, and terns on average was 82% accurate, based on a jackknife cross-validation. Model classification of bats and terns (N = 4 and 2, respectively) was 94% and 91% correct, respectively; however, the variance associated with the tracks from these targets is poorly estimated. Model classification of gulls and swallows (N ≥ 18) was on average 73% and 85% correct, respectively. The models developed here should be considered preliminary because they are based on a small data set both in terms of the numbers of species and the identified flight tracks. Future classification models would be greatly improved by including a measure of distance between the camera and the target.

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

Science.gov (United States)

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.

KOLAM: a cross-platform architecture for scalable visualization and tracking in wide-area imagery

Science.gov (United States)

Fraser, Joshua; Haridas, Anoop; Seetharaman, Guna; Rao, Raghuveer M.; Palaniappan, Kannappan

2013-05-01

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness.

Multi-agent target tracking using particle filters enhanced with context data

CSIR Research Space (South Africa)

Claessens, R

2015-05-01

Full Text Available The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence...

Passive target tracking using marginalized particle filter

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

A marginalized particle filtering(MPF)approach is proposed for target tracking under the background of passive measurement.Essentially,the MPF is a combination of particle filtering technique and Kalman filter.By making full use of marginalization,the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter,and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter.Simulation studies are performed on an illustrative example,and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation.Real data test results also validate the effectiveness of the presented method.

Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

Science.gov (United States)

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

2014-11-11

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.

Quantitative analysis of the improvement in omnidirectional maritime surveillance and tracking due to real-time image enhancement

Science.gov (United States)

de Villiers, Jason P.; Bachoo, Asheer K.; Nicolls, Fred C.; le Roux, Francois P. J.

2011-05-01

Tracking targets in a panoramic image is in many senses the inverse problem of tracking targets with a narrow field of view camera on a pan-tilt pedestal. In a narrow field of view camera tracking a moving target, the object is constant and the background is changing. A panoramic camera is able to model the entire scene, or background, and those areas it cannot model well are the potential targets and typically subtended far fewer pixels in the panoramic view compared to the narrow field of view. The outputs of an outward staring array of calibrated machine vision cameras are stitched into a single omnidirectional panorama and used to observe False Bay near Simon's Town, South Africa. A ground truth data-set was created by geo-aligning the camera array and placing a differential global position system receiver on a small target boat thus allowing its position in the array's field of view to be determined. Common tracking techniques including level-sets, Kalman filters and particle filters were implemented to run on the central processing unit of the tracking computer. Image enhancement techniques including multi-scale tone mapping, interpolated local histogram equalisation and several sharpening techniques were implemented on the graphics processing unit. An objective measurement of each tracking algorithm's robustness in the presence of sea-glint, low contrast visibility and sea clutter - such as white caps is performed on the raw recorded video data. These results are then compared to those obtained with the enhanced video data.

Code domain steganography in video tracks

Science.gov (United States)

Rymaszewski, Sławomir

2008-01-01

This article is dealing with a practical method of hiding secret information in video stream. Method is dedicated for MPEG-2 stream. The algorithm takes to consider not only MPEG video coding scheme described in standard but also bits PES-packets encapsulation in MPEG-2 Program Stream (PS). This modification give higher capacity and more effective bit rate control for output stream than previously proposed methods.

A low-cost test-bed for real-time landmark tracking

Science.gov (United States)

Csaszar, Ambrus; Hanan, Jay C.; Moreels, Pierre; Assad, Christopher

2007-04-01

A low-cost vehicle test-bed system was developed to iteratively test, refine and demonstrate navigation algorithms before attempting to transfer the algorithms to more advanced rover prototypes. The platform used here was a modified radio controlled (RC) car. A microcontroller board and onboard laptop computer allow for either autonomous or remote operation via a computer workstation. The sensors onboard the vehicle represent the types currently used on NASA-JPL rover prototypes. For dead-reckoning navigation, optical wheel encoders, a single axis gyroscope, and 2-axis accelerometer were used. An ultrasound ranger is available to calculate distance as a substitute for the stereo vision systems presently used on rovers. The prototype also carries a small laptop computer with a USB camera and wireless transmitter to send real time video to an off-board computer. A real-time user interface was implemented that combines an automatic image feature selector, tracking parameter controls, streaming video viewer, and user generated or autonomous driving commands. Using the test-bed, real-time landmark tracking was demonstrated by autonomously driving the vehicle through the JPL Mars yard. The algorithms tracked rocks as waypoints. This generated coordinates calculating relative motion and visually servoing to science targets. A limitation for the current system is serial computing-each additional landmark is tracked in order-but since each landmark is tracked independently, if transferred to appropriate parallel hardware, adding targets would not significantly diminish system speed.

A novel visual saliency detection method for infrared video sequences

Science.gov (United States)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs

Directory of Open Access Journals (Sweden)

Mousumi Ahmed

2016-02-01

Full Text Available This paper presents an estimation based backstepping like control law design for an Unmanned Aerial Vehicle (UAV to track a moving target in 3-D space. A ground-based sensor or an onboard seeker antenna provides range, azimuth angle, and elevation angle measurements to a chaser UAV that implements an extended Kalman filter (EKF to estimate the full state of the target. A nonlinear controller then utilizes this estimated target state and the chaser’s state to provide speed, flight path, and course/heading angle commands to the chaser UAV. Tracking performance with respect to measurement uncertainty is evaluated for three cases: (1 stationary white noise; (2 stationary colored noise and (3 non-stationary (range correlated white noise. Furthermore, in an effort to improve tracking performance, the measurement model is made more realistic by taking into consideration range-dependent uncertainties in the measurements, i.e., as the chaser closes in on the target, measurement uncertainties are reduced in the EKF, thus providing the UAV with more accurate control commands. Simulation results for these cases are shown to illustrate target state estimation and trajectory tracking performance.

Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Voit, Michael; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2017-05-01

Real-time motion video analysis is a challenging and exhausting task for the human observer, particularly in safety and security critical domains. Hence, customized video analysis systems providing functions for the analysis of subtasks like motion detection or target tracking are welcome. While such automated algorithms relieve the human operators from performing basic subtasks, they impose additional interaction duties on them. Prior work shows that, e.g., for interaction with target tracking algorithms, a gaze-enhanced user interface is beneficial. In this contribution, we present an investigation on interaction with an independent motion detection (IDM) algorithm. Besides identifying an appropriate interaction technique for the user interface - again, we compare gaze-based and traditional mouse-based interaction - we focus on the benefit an IDM algorithm might provide for an UAS video analyst. In a pilot study, we exposed ten subjects to the task of moving target detection in UAS video data twice, once performing with automatic support, once performing without it. We compare the two conditions considering performance in terms of effectiveness (correct target selections). Additionally, we report perceived workload (measured using the NASA-TLX questionnaire) and user satisfaction (measured using the ISO 9241-411 questionnaire). The results show that a combination of gaze input and automated IDM algorithm provides valuable support for the human observer, increasing the number of correct target selections up to 62% and reducing workload at the same time.

Siamese convolutional networks for tracking the spine motion

Science.gov (United States)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System

Directory of Open Access Journals (Sweden)

Van-Han Nguyen

2015-03-01

Full Text Available 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.

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

Science.gov (United States)

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.

Robot Visual Tracking via Incremental Self-Updating of Appearance Model

Directory of Open Access Journals (Sweden)

Danpei Zhao

2013-09-01

Full Text Available This paper proposes a target tracking method called Incremental Self-Updating Visual Tracking for robot platforms. Our tracker treats the tracking problem as a binary classification: the target and the background. The greyscale, HOG and LBP features are used in this work to represent the target and are integrated into a particle filter framework. To track the target over long time sequences, the tracker has to update its model to follow the most recent target. In order to deal with the problems of calculation waste and lack of model-updating strategy with the traditional methods, an intelligent and effective online self-updating strategy is devised to choose the optimal update opportunity. The strategy of updating the appearance model can be achieved based on the change in the discriminative capability between the current frame and the previous updated frame. By adjusting the update step adaptively, severe waste of calculation time for needless updates can be avoided while keeping the stability of the model. Moreover, the appearance model can be kept away from serious drift problems when the target undergoes temporary occlusion. The experimental results show that the proposed tracker can achieve robust and efficient performance in several benchmark-challenging video sequences with various complex environment changes in posture, scale, illumination and occlusion.

ANNOTATION SUPPORTED OCCLUDED OBJECT TRACKING

Directory of Open Access Journals (Sweden)

Devinder Kumar

2012-08-01

Full Text Available Tracking occluded objects at different depths has become as extremely important component of study for any video sequence having wide applications in object tracking, scene recognition, coding, editing the videos and mosaicking. The paper studies the ability of annotation to track the occluded object based on pyramids with variation in depth further establishing a threshold at which the ability of the system to track the occluded object fails. Image annotation is applied on 3 similar video sequences varying in depth. In the experiment, one bike occludes the other at a depth of 60cm, 80cm and 100cm respectively. Another experiment is performed on tracking humans with similar depth to authenticate the results. The paper also computes the frame by frame error incurred by the system, supported by detailed simulations. This system can be effectively used to analyze the error in motion tracking and further correcting the error leading to flawless tracking. This can be of great interest to computer scientists while designing surveillance systems etc.

Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

Directory of Open Access Journals (Sweden)

M. Sanjeev Arulampalam

2004-11-01

Full Text Available We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs. Three different (PFs are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS framework. The proposed filters are (i multiple model PF (MMPF, (ii auxiliary MMPF (AUX-MMPF, and (iii jump Markov system PF (JMS-PF. The performance of these filters is compared with that of standard interacting multiple model (IMM-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i single-sensor case, (ii multisensor case, and (iii tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

Postural sway and gaze can track the complex motion of a visual target.

Directory of Open Access Journals (Sweden)

Vassilia Hatzitaki

Full Text Available Variability is an inherent and important feature of human movement. This variability has form exhibiting a chaotic structure. Visual feedback training using regular predictive visual target motions does not take into account this essential characteristic of the human movement, and may result in task specific learning and loss of visuo-motor adaptability. In this study, we asked how well healthy young adults can track visual target cues of varying degree of complexity during whole-body swaying in the Anterior-Posterior (AP and Medio-Lateral (ML direction. Participants were asked to track three visual target motions: a complex (Lorenz attractor, a noise (brown and a periodic (sine moving target while receiving online visual feedback about their performance. Postural sway, gaze and target motion were synchronously recorded and the degree of force-target and gaze-target coupling was quantified using spectral coherence and Cross-Approximate entropy. Analysis revealed that both force-target and gaze-target coupling was sensitive to the complexity of the visual stimuli motions. Postural sway showed a higher degree of coherence with the Lorenz attractor than the brown noise or sinusoidal stimulus motion. Similarly, gaze was more synchronous with the Lorenz attractor than the brown noise and sinusoidal stimulus motion. These results were similar regardless of whether tracking was performed in the AP or ML direction. Based on the theoretical model of optimal movement variability tracking of a complex signal may provide a better stimulus to improve visuo-motor adaptation and learning in postural control.

Opportune acquisition and tracking time for the fast-moving targets in a ground-based telescope

Science.gov (United States)

Chen, Juan; Wang, Jianli; Chen, Tao

2004-10-01

Acquisition is defined as identification for a fixed target in the related field of sight (FOS), while tracking means the sway of the telescope's axis of sight (AOS). The automatic acquisition and tracking is a process in which the operating way of the telescope should be switched from guiding to automatic tracking. There are some kinds of method to improve the acquisition and tracking ability for fast moving targets: to extend the acquisition and tracking FOS with memory and storage information of the sensor system; the multimode control to improve the dynamic property of the servo system; to choose an opportune time for acquisition and tracking; to select the control regulator parameter in every working states. If the processor of the CCD sensor can temporarily remember and save the information of the target before it moves out of the FOS, correspondingly, the FOS may be extended. The data forecast technology is used to store the target information. The automatic interception experiments are carried out to verify the control strategy.

Real-time video analysis for retail stores

Science.gov (United States)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

Science.gov (United States)

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�

Persistent Aerial Tracking system for UAVs

KAUST Repository

Mueller, Matthias; Sharma, Gopal; Smith, Neil; Ghanem, Bernard

2016-01-01

In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

Persistent Aerial Tracking system for UAVs

KAUST Repository

Mueller, Matthias

2016-12-19

In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

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

Directory of Open Access Journals (Sweden)

Anthony Hoak

2017-03-01

Full Text Available 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.

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

Science.gov (United States)

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.

Impact of Target Distance, Target Size, and Visual Acuity on the Video Head Impulse Test.

Science.gov (United States)

Judge, Paul D; Rodriguez, Amanda I; Barin, Kamran; Janky, Kristen L

2018-05-01

The video head impulse test (vHIT) assesses the vestibulo-ocular reflex. Few have evaluated whether environmental factors or visual acuity influence the vHIT. The purpose of this study was to evaluate the influence of target distance, target size, and visual acuity on vHIT outcomes. Thirty-eight normal controls and 8 subjects with vestibular loss (VL) participated. vHIT was completed at 3 distances and with 3 target sizes. Normal controls were subdivided on the basis of visual acuity. Corrective saccade frequency, corrective saccade amplitude, and gain were tabulated. In the normal control group, there were no significant effects of target size or visual acuity for any vHIT outcome parameters; however, gain increased as target distance decreased. The VL group demonstrated higher corrective saccade frequency and amplitude and lower gain as compared with controls. In conclusion, decreasing target distance increases gain for normal controls but not subjects with VL. Preliminarily, visual acuity does not affect vHIT outcomes.

Lung tumor tracking in fluoroscopic video based on optical flow

International Nuclear Information System (INIS)

Xu Qianyi; Hamilton, Russell J.; Schowengerdt, Robert A.; Alexander, Brian; Jiang, Steve B.

2008-01-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (∼0.7 mm) in the best case and 2.8 pixels (∼1.4 mm) in the worst case for the five patients studied.

Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

Directory of Open Access Journals (Sweden)

Mohammadreza Asghari Oskoei

2017-11-01

Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

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

Science.gov (United States)

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

2012-01-01

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

Classification of video sequences into chosen generalized use classes of target size and lighting level.

Science.gov (United States)

Leszczuk, Mikołaj; Dudek, Łukasz; Witkowski, Marcin

The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

Multi-Target Tracking via Mixed Integer Optimization

Science.gov (United States)

2016-05-13

an easily interpretable global objective function. Furthermore, we propose a greedy heuristic which quickly finds good solutions. We extend both the... heuristic and the MIO model to scenarios with missed detections and false alarms. Index Terms—optimization; multi-target tracking; data asso- ciation...energy in [14] and then again as a minimization of discrete-continuous energy in [15]. These algorithms aim to more accurately represent the nature of the

A new user-assisted segmentation and tracking technique for an object-based video editing system

Science.gov (United States)

Yu, Hong Y.; Hong, Sung-Hoon; Lee, Mike M.; Choi, Jae-Gark

2004-03-01

This paper presents a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on these results, we have developed objects based video editing system with several convenient editing functions.

Local characterization of hindered Brownian motion by using digital video microscopy and 3D particle tracking

Energy Technology Data Exchange (ETDEWEB)

Dettmer, Simon L.; Keyser, Ulrich F.; Pagliara, Stefano [Cavendish Laboratory, University of Cambridge, 19 J J Thomson Avenue, Cambridge CB3 0HE (United Kingdom)

2014-02-15

In this article we present methods for measuring hindered Brownian motion in the confinement of complex 3D geometries using digital video microscopy. Here we discuss essential features of automated 3D particle tracking as well as diffusion data analysis. By introducing local mean squared displacement-vs-time curves, we are able to simultaneously measure the spatial dependence of diffusion coefficients, tracking accuracies and drift velocities. Such local measurements allow a more detailed and appropriate description of strongly heterogeneous systems as opposed to global measurements. Finite size effects of the tracking region on measuring mean squared displacements are also discussed. The use of these methods was crucial for the measurement of the diffusive behavior of spherical polystyrene particles (505 nm diameter) in a microfluidic chip. The particles explored an array of parallel channels with different cross sections as well as the bulk reservoirs. For this experiment we present the measurement of local tracking accuracies in all three axial directions as well as the diffusivity parallel to the channel axis while we observed no significant flow but purely Brownian motion. Finally, the presented algorithm is suitable also for tracking of fluorescently labeled particles and particles driven by an external force, e.g., electrokinetic or dielectrophoretic forces.

Application results for an augmented video tracker

Science.gov (United States)

Pierce, Bill

1991-08-01

The Relay Mirror Experiment (RME) is a research program to determine the pointing accuracy and stability levels achieved when a laser beam is reflected by the RME satellite from one ground station to another. This paper reports the results of using a video tracker augmented with a quad cell signal to improve the RME ground station tracking system performance. The video tracker controls a mirror to acquire the RME satellite, and provides a robust low bandwidth tracking loop to remove line of sight (LOS) jitter. The high-passed, high-gain quad cell signal is added to the low bandwidth, low-gain video tracker signal to increase the effective tracking loop bandwidth, and significantly improves LOS disturbance rejection. The quad cell augmented video tracking system is analyzed, and the math model for the tracker is developed. A MATLAB model is then developed from this, and performance as a function of bandwidth and disturbances is given. Improvements in performance due to the addition of the video tracker and the augmentation with the quad cell are provided. Actual satellite test results are then presented and compared with the simulated results.

Measuring coseismic displacements with point-like targets offset tracking

KAUST Repository

Hu, Xie; Wang, Teng; Liao, Mingsheng

2014-01-01

Offset tracking is an important complement to measure large ground displacements in both azimuth and range dimensions where synthetic aperture radar (SAR) interferometry is unfeasible. Subpixel offsets can be obtained by searching for the cross-correlation peak calculated from the match patches uniformly distributed on two SAR images. However, it has its limitations, including redundant computation and incorrect estimations on decorrelated patches. In this letter, we propose a simple strategy that performs offset tracking on detected point-like targets (PT). We first detect image patches within bright PT by using a sinc-like template from a single SAR image and then perform offset tracking on them to obtain the pixel shifts. Compared with the standard method, the application on the 2010 M 7.2 El Mayor-Cucapah earthquake shows that the proposed PT offset tracking can significantly increase the cross-correlation and thus result in both efficiency and reliability improvements. © 2013 IEEE.

Dazzle camouflage, target tracking, and the confusion effect.

Science.gov (United States)

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.

Reduced bandwidth video for remote vehicle operations

Energy Technology Data Exchange (ETDEWEB)

Noell, T.E.; DePiero, F.W.

1993-08-01

Oak Ridge National Laboratory staff have developed a video compression system for low-bandwidth remote operations. The objective is to provide real-time video at data rates comparable to available tactical radio links, typically 16 to 64 thousand bits per second (kbps), while maintaining sufficient quality to achieve mission objectives. The system supports both continuous lossy transmission of black and white (gray scale) video for remote driving and progressive lossless transmission of black and white images for remote automatic target acquisition. The average data rate of the resulting bit stream is 64 kbps. This system has been demonstrated to provide video of sufficient quality to allow remote driving of a High-Mobility Multipurpose Wheeled Vehicle at speeds up to 15 mph (24.1 kph) on a moguled dirt track. The nominal driving configuration provides a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of {approximately}1s. This paper reviews the system approach and implementation, and further describes some of our experiences when using the system to support remote driving.

Quantifying sublethal effects of glyphosate and Roundup® to Daphnia magna using a fluorescence based enzyme activity assay and video tracking

DEFF Research Database (Denmark)

Roslev, Peter; R. Hansen, Lone; Ørsted, Michael

Glyphosate (N-(phosphonomethyl)glycine) is the active ingredient in a range of popular broad-spectrum, non-selective herbicide formulations. The toxicity of this herbicide to non-target aquatic organisms such as Daphnia magna is often evaluated using conventional toxicity assays that focus...... on endpoints such as immobility and mortality. In this study, we investigated sublethal effects of glyphosate and Roundup® to D. magna using video tracking for quantifying behavioral changes, and a novel fluorescence based assay for measuring in vivo hydrolytic enzyme activity (FLEA assay). Roundup® exposure...... resulted in concentration-dependent inhibition of alkaline phosphatase activity in D. magna. The inhibition of alkaline phosphatase by Roundup® was temperature-dependent with lowest inhibition at 14 °C and greater inhibition at 20 and 26 °C. Exposure of D. magna to sublethal concentrations of glyphosate...

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

Science.gov (United States)

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

2018-01-01

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

Urbanism on Track : Application of tracking technologies in urbanism

NARCIS (Netherlands)

Van der Hoeven, F.D.; Van Schaick, J.; Van der Spek, S.C.; Smit, M.G.J.

2008-01-01

Tracking technologies such as GPS, mobile phone tracking, video and RFID monitoring are rapidly becoming part of daily life. Technological progress offers huge possibilities for studying human activity patterns in time and space in new ways. Delft University of Technology (TU Delft) held an

Target tracking control and semi-physical simulation of Qball-X4 quad-rotor unmanned aerial vehicle

Directory of Open Access Journals (Sweden)

Lu Liu

2017-01-01

Full Text Available In this article, a set of integrated ground target tracking flight system has been proposed based on the Qball-X4 quad-rotor unmanned aerial vehicle hardware platform and the QuaRC software platform. Both of the hardware and software platforms are developed by Quanser Company, Canada. The proposed tracking and positioning algorithm could be divided into several stages. First, a tracker is developed based on an optical flow method to track the target; and then, in order to improve the reliability of tracking algorithm and also help in retrieving the lost target, a cascade target detector is developed; meanwhile, a model updated scheme aiming at some possible errors in tracking and detecting process is presented based on Positive-Negative (P-N learning system; at last, a monocular visual positioning system is designed based on the corresponding navigation message. In addition, the effectiveness of the proposed flight control system is verified by both simulation and hardware-in-loop system results in several tracking flight tests.

DMLC motion tracking of moving targets for intensity modulated arc therapy treatment

DEFF Research Database (Denmark)

Zimmerman, Jens; Korreman, Stine; Persson, Gitte

2009-01-01

(DMLC). The aim of this work was to evaluate the dose delivered to moving targets using the RapidArc (Varian Medical Systems, Inc.) technology with and without a DMLC tracking algorithm. MATERIAL AND METHODS: A Varian Clinac iX was equipped with a preclinical RapidArc and a 3D DMLC tracking application......) and state (1). CONCLUSIONS: DMLC tracking together with RapidArc make a feasible combination and is capable of improving the dose distribution delivered to a moving target. It seems to be of importance to minimize noise influencing the tracking, to gain the full benefit from the application........ A motion platform was placed on the couch, with the detectors on top: a PTW seven29 and a Scandidos Delta4. One lung plan and one prostate plan were delivered. Motion was monitored using a Real-time Position Management (RPM) system. Reference measurements were performed for both plans with both detectors...

Near real-time bi-planar fluoroscopic tracking system for the video tumor fighter

International Nuclear Information System (INIS)

Lawson, M.A.; Wika, K.G.; Gillies, G.T.; Ritter, R.C.

1991-01-01

The authors have developed software capable of the three-dimensional tracking of objects in the brain volume, and the subsequent overlaying of an image of the object onto previously obtained MR or CT scans. This software has been developed for use with the Magnetic Stereotaxis System (MSS), also called the Video Tumor Fighter (VTF). The software was written for s Sun 4/110 SPARC workstation with an ANDROX ICS-400 image processing card installed to manage this task. At present, the system uses input from two orthogonally- oriented, visible-light cameras and simulated scene to determine the three-dimensional position of the object of interest. The coordinates are then transformed into MR or CT coordinates and an image of the object is displayed in the appropriate intersecting MR slice on a computer screen. This paper describes the tracking algorithm and discusses how it was implemented in software. The system's hardware is also described. The limitations of the present system are discussed and plans for incorporating bi-planar, x-ray fluoroscopy are presented

Video tracking and post-mortem analysis of dust particles from all tungsten ASDEX Upgrade

Energy Technology Data Exchange (ETDEWEB)

Endstrasser, N., E-mail: Nikolaus.Endstrasser@ipp.mpg.de [Max-Planck-Insitut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Brochard, F. [Institut Jean Lamour, Nancy-Universite, Bvd. des Aiguillettes, F-54506 Vandoeuvre (France); Rohde, V., E-mail: Volker.Rohde@ipp.mpg.de [Max-Planck-Insitut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Balden, M. [Max-Planck-Insitut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Lunt, T.; Bardin, S.; Briancon, J.-L. [Institut Jean Lamour, Nancy-Universite, Bvd. des Aiguillettes, F-54506 Vandoeuvre (France); Neu, R. [Max-Planck-Insitut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany)

2011-08-01

2D dust particle trajectories are extracted from fast framing camera videos of ASDEX Upgrade (AUG) by a new time- and resource-efficient code and classified into stationary hot spots, single-frame events and real dust particle fly-bys. Using hybrid global and local intensity thresholding and linear trajectory extrapolation individual particles could be tracked up to 80 ms. Even under challenging conditions such as high particle density and strong vacuum vessel illumination all particles detected for more than 50 frames are tracked correctly. During campaign 2009 dust has been trapped on five silicon wafer dust collectors strategically positioned within the vacuum vessel of the full tungsten AUG. Characterisation of the outer morphology and determination of the elemental composition of 5 x 10{sup 4} particles were performed via automated SEM-EDX analysis. A dust classification scheme based on these parameters was defined with the goal to link the particles to their most probable production sites.

Joint passive radar tracking and target classification using radar cross section

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Intelligent video surveillance systems

CERN Document Server

Dufour, Jean-Yves

2012-01-01

Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi

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

Science.gov (United States)

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.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

NARCIS (Netherlands)

Zachiu, Cornel; Ries, Mario G; Ramaekers, Pascal; Guey, Jean-Luc; Moonen, Chrit T W; de Senneville, Baudouin Denis

2017-01-01

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

Robust Object Tracking with a Hierarchical Ensemble Framework

Science.gov (United States)

2016-10-09

consistency in the target bounding box level while we take this into con - sideration by employing an adaptive Kalman filter. Therefore our method is more...hu- man videos with occlusions(OCC), deformation( DEF ), back- ground clutter(BC), scale variations(SV), fast motion(FM) and illumination variation(IV... con - volutional features for visual tracking,” in Proceedings of the IEEE International Conference on Computer Vision, pp. 3074–3082, 2015. 445

Visual Analytics and Storytelling through Video

Energy Technology Data Exchange (ETDEWEB)

Wong, Pak C.; Perrine, Kenneth A.; Mackey, Patrick S.; Foote, Harlan P.; Thomas, Jim

2005-10-31

This paper supplements a video clip submitted to the Video Track of IEEE Symposium on Information Visualization 2005. The original video submission applies a two-way storytelling approach to demonstrate the visual analytics capabilities of a new visualization technique. The paper presents our video production philosophy, describes the plot of the video, explains the rationale behind the plot, and finally, shares our production experiences with our readers.

Region descriptors for automatic classification of small sea targets in infrared video

NARCIS (Netherlands)

Mouthaan, M.M.; Broek, S.P. van den; Hendriks, E.A.; Schwering, P.B.W.

2011-01-01

We evaluate the performance of different key-point detectors and region descriptors when used for automatic classification of small sea targets in infrared video. In our earlier research performed on this subject as well as in other literature, many different region descriptors have been proposed.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Supertracker: A Programmable Parallel Pipeline Arithmetic Processor For Auto-Cueing Target Processing

Science.gov (United States)

Mack, Harold; Reddi, S. S.

1980-04-01

Supertracker represents a programmable parallel pipeline computer architecture that has been designed to meet the real time image processing requirements of auto-cueing target data processing. The prototype bread-board currently under development will be designed to perform input video preprocessing and processing for 525-line and 875-line TV formats FLIR video, automatic display gain and contrast control, and automatic target cueing, classification, and tracking. The video preprocessor is capable of performing operations full frames of video data in real time, e.g., frame integration, storage, 3 x 3 convolution, and neighborhood processing. The processor architecture is being implemented using bit-slice microprogrammable arithmetic processors, operating in parallel. Each processor is capable of up to 20 million operations per second. Multiple frame memories are used for additional flexibility.

Hardware accelerator design for tracking in smart camera

Science.gov (United States)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Vohra, Anil

2011-10-01

Smart Cameras are important components in video analysis. For video analysis, smart cameras needs to detect interesting moving objects, track such objects from frame to frame, and perform analysis of object track in real time. Therefore, the use of real-time tracking is prominent in smart cameras. The software implementation of tracking algorithm on a general purpose processor (like PowerPC) could achieve low frame rate far from real-time requirements. This paper presents the SIMD approach based hardware accelerator designed for real-time tracking of objects in a scene. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA. Resulted frame rate is 30 frames per second for 250x200 resolution video in gray scale.

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Science.gov (United States)

Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P; Zelikowsky, Moriel; Navonne, Santiago G; Perona, Pietro; Anderson, David J

2015-09-22

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

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

Science.gov (United States)

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.

Tracking a "facer's" behavior in a public plaza

DEFF Research Database (Denmark)

2014-01-01

The video shows the tracking of a "facer's" behavior in a public plaza using a thermal camera (non-privacy violating) and a visualization of the tracks in a space-time cube in a 3D GIS. The tracking data is used in my PhD project on Human Movement Patterns in Smart Cities. The recording and analy...... and analysis of the thermal video has been made in collaboration with Rikke Gade from the Visual Analytics of People Lab at Aalborg University.......The video shows the tracking of a "facer's" behavior in a public plaza using a thermal camera (non-privacy violating) and a visualization of the tracks in a space-time cube in a 3D GIS. The tracking data is used in my PhD project on Human Movement Patterns in Smart Cities. The recording...

First Demonstration of Combined kV/MV Image-Guided Real-Time Dynamic Multileaf-Collimator Target Tracking

International Nuclear Information System (INIS)

Cho, Byungchul; Poulsen, Per R.; Sloutsky, Alex; Sawant, Amit; Keall, Paul J.

2009-01-01

Purpose: For intrafraction motion management, a real-time tracking system was developed by combining fiducial marker-based tracking via simultaneous kilovoltage (kV) and megavoltage (MV) imaging and a dynamic multileaf collimator (DMLC) beam-tracking system. Methods and Materials: The integrated tracking system employed a Varian Trilogy system equipped with kV/MV imaging systems and a Millennium 120-leaf MLC. A gold marker in elliptical motion (2-cm superior-inferior, 1-cm left-right, 10 cycles/min) was simultaneously imaged by the kV and MV imagers at 6.7 Hz and segmented in real time. With these two-dimensional projections, the tracking software triangulated the three-dimensional marker position and repositioned the MLC leaves to follow the motion. Phantom studies were performed to evaluate time delay from image acquisition to MLC adjustment, tracking error, and dosimetric impact of target motion with and without tracking. Results: The time delay of the integrated tracking system was ∼450 ms. The tracking error using a prediction algorithm was 0.9 ± 0.5 mm for the elliptical motion. The dose distribution with tracking showed better target coverage and less dose to surrounding region over no tracking. The failure rate of the gamma test (3%/3-mm criteria) was 22.5% without tracking but was reduced to 0.2% with tracking. Conclusion: For the first time, a complete tracking system combining kV/MV image-guided target tracking and DMLC beam tracking was demonstrated. The average geometric error was less than 1 mm, and the dosimetric error was negligible. This system is a promising method for intrafraction motion management.

Composite Wavelet Filters for Enhanced Automated Target Recognition

Science.gov (United States)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Droplet morphometry and velocimetry (DMV): a video processing software for time-resolved, label-free tracking of droplet parameters.

Science.gov (United States)

Basu, Amar S

2013-05-21

Emerging assays in droplet microfluidics require the measurement of parameters such as drop size, velocity, trajectory, shape deformation, fluorescence intensity, and others. While micro particle image velocimetry (μPIV) and related techniques are suitable for measuring flow using tracer particles, no tool exists for tracking droplets at the granularity of a single entity. This paper presents droplet morphometry and velocimetry (DMV), a digital video processing software for time-resolved droplet analysis. Droplets are identified through a series of image processing steps which operate on transparent, translucent, fluorescent, or opaque droplets. The steps include background image generation, background subtraction, edge detection, small object removal, morphological close and fill, and shape discrimination. A frame correlation step then links droplets spanning multiple frames via a nearest neighbor search with user-defined matching criteria. Each step can be individually tuned for maximum compatibility. For each droplet found, DMV provides a time-history of 20 different parameters, including trajectory, velocity, area, dimensions, shape deformation, orientation, nearest neighbour spacing, and pixel statistics. The data can be reported via scatter plots, histograms, and tables at the granularity of individual droplets or by statistics accrued over the population. We present several case studies from industry and academic labs, including the measurement of 1) size distributions and flow perturbations in a drop generator, 2) size distributions and mixing rates in drop splitting/merging devices, 3) efficiency of single cell encapsulation devices, 4) position tracking in electrowetting operations, 5) chemical concentrations in a serial drop dilutor, 6) drop sorting efficiency of a tensiophoresis device, 7) plug length and orientation of nonspherical plugs in a serpentine channel, and 8) high throughput tracking of >250 drops in a reinjection system. Performance metrics

Quantitative analysis of the improvement in high zoom maritime tracking due to real-time image enhancement

CSIR Research Space (South Africa)

Bachoo, AK

2011-04-01

Full Text Available This work aims to evaluate the improvement in the performance of tracking small maritime targets due to real-time enhancement of the video streams from high zoom cameras on pan-tilt pedestal. Due to atmospheric conditions these images can frequently...

Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance

Directory of Open Access Journals (Sweden)

Xenofon Koutsoukos

2013-05-01

Full Text Available With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS and Quality-of-Information (QoI metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.

Signal Detection, Target Tracking and Differential Geometry Applications to Statistical Inference

National Research Council Canada - National Science Library

Rao, C

1997-01-01

Signal detection and target tracking. A novel method known as polynomial rooting approach is proposed to obtain estimates of frequencies, amplitudes and noise variance of two-dimensional exponential signals...

Medical Imaging for the Tracking of Micromotors.

Science.gov (United States)

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.

Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Feng Juan

2013-10-01

Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

Automated intelligent video surveillance system for ships

Science.gov (United States)

Wei, Hai; Nguyen, Hieu; Ramu, Prakash; Raju, Chaitanya; Liu, Xiaoqing; Yadegar, Jacob

2009-05-01

To protect naval and commercial ships from attack by terrorists and pirates, it is important to have automatic surveillance systems able to detect, identify, track and alert the crew on small watercrafts that might pursue malicious intentions, while ruling out non-threat entities. Radar systems have limitations on the minimum detectable range and lack high-level classification power. In this paper, we present an innovative Automated Intelligent Video Surveillance System for Ships (AIVS3) as a vision-based solution for ship security. Capitalizing on advanced computer vision algorithms and practical machine learning methodologies, the developed AIVS3 is not only capable of efficiently and robustly detecting, classifying, and tracking various maritime targets, but also able to fuse heterogeneous target information to interpret scene activities, associate targets with levels of threat, and issue the corresponding alerts/recommendations to the man-in- the-loop (MITL). AIVS3 has been tested in various maritime scenarios and shown accurate and effective threat detection performance. By reducing the reliance on human eyes to monitor cluttered scenes, AIVS3 will save the manpower while increasing the accuracy in detection and identification of asymmetric attacks for ship protection.

A Bayesian analysis of the mixed labelling phenomenon in two-target tracking

NARCIS (Netherlands)

Aoki, E.H.; Boers, Y.; Svensson, L.; Mandal, Pranab K.; Bagchi, Arunabha

In mulit-target tracking and labelling (MTTL), mixed labelling corresponds to a situation where there is ambiguity in labelling, i.e. in the assignment of labels to locations (where a "location" here means simply an unlabelled single-target state. The phenomenon is well-known in literature, and

Interaction of 80 MeV PI+ with different targets: Track detector studies

Energy Technology Data Exchange (ETDEWEB)

Tabassum, L; Chohan, A S [Government Coll., Lahore. (Pakistan) Deptt. of Physics Khan, H.A. (Pakistan Inst. of Nuclear Science and Technology, Islamabad (Pakistan). Nuclear Engineering Div.)

1990-04-01

CR-39 and mica track detectors have been used in the study of the interactions of 80 MeV PI+ with thin targets of Bi, Pb, Ho, Sb. The binary fission cross sections, the length and angular distributions of etched tracks have been obtained. The cross-section values obtained by using CR-39 are higher as compared to those obtained with mica. (author).

Interaction of 80 MeV PI+ with different targets: Track detector studies

International Nuclear Information System (INIS)

Tabassum, L.; Chohan, A.S.

1990-01-01

CR-39 and mica track detectors have been used in the study of the interactions of 80 MeV PI+ with thin targets of Bi, Pb, Ho, Sb. The binary fission cross sections, the length and angular distributions of etched tracks have been obtained. The cross-section values obtained by using CR-39 are higher as compared to those obtained with mica. (author)

Automatic measurement for solid state track detectors

International Nuclear Information System (INIS)

Ogura, Koichi

1982-01-01

Since in solid state track detectors, their tracks are measured with a microscope, observers are forced to do hard works that consume time and labour. This causes to obtain poor statistic accuracy or to produce personal error. Therefore, many researches have been done to aim at simplifying and automating track measurement. There are two categories in automating the measurement: simple counting of the number of tracks and the requirements to know geometrical elements such as the size of tracks or their coordinates as well as the number of tracks. The former is called automatic counting and the latter automatic analysis. The method to generally evaluate the number of tracks in automatic counting is the estimation of the total number of tracks in the total detector area or in a field of view of a microscope. It is suitable for counting when the track density is higher. The method to count tracks one by one includes the spark counting and the scanning microdensitometer. Automatic analysis includes video image analysis in which the high quality images obtained with a high resolution video camera are processed with a micro-computer, and the tracks are automatically recognized and measured by feature extraction. This method is described in detail. In many kinds of automatic measurements reported so far, frequently used ones are ''spark counting'' and ''video image analysis''. (Wakatsuki, Y.)

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2005-09-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2008-11-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Classification of dual language audio-visual content: Introduction to the VideoCLEF 2008 pilot benchmark evaluation task

NARCIS (Netherlands)

Larson, M.; Newman, E.; Jones, G.J.F.; Köhler, J.; Larson, M.; de Jong, F.M.G.; Kraaij, W.; Ordelman, R.J.F.

2008-01-01

VideoCLEF is a new track for the CLEF 2008 campaign. This track aims to develop and evaluate tasks in analyzing multilingual video content. A pilot of a Vid2RSS task involving assigning thematic class labels to video kicks off the VideoCLEF track in 2008. Task participants deliver classification

Video redaction: a survey and comparison of enabling technologies

Science.gov (United States)

Sah, Shagan; Shringi, Ameya; Ptucha, Raymond; Burry, Aaron; Loce, Robert

2017-09-01

With the prevalence of video recordings from smart phones, dash cams, body cams, and conventional surveillance cameras, privacy protection has become a major concern, especially in light of legislation such as the Freedom of Information Act. Video redaction is used to obfuscate sensitive and personally identifiable information. Today's typical workflow involves simple detection, tracking, and manual intervention. Automated methods rely on accurate detection mechanisms being paired with robust tracking methods across the video sequence to ensure the redaction of all sensitive information while minimizing spurious obfuscations. Recent studies have explored the use of convolution neural networks and recurrent neural networks for object detection and tracking. The present paper reviews the redaction problem and compares a few state-of-the-art detection, tracking, and obfuscation methods as they relate to redaction. The comparison introduces an evaluation metric that is specific to video redaction performance. The metric can be evaluated in a manner that allows balancing the penalty for false negatives and false positives according to the needs of particular application, thereby assisting in the selection of component methods and their associated hyperparameters such that the redacted video has fewer frames that require manual review.

Robust online tracking via adaptive samples selection with saliency detection

Science.gov (United States)

Yan, Jia; Chen, Xi; Zhu, QiuPing

2013-12-01

Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

Research on Key Technologies of Network Centric System Distributed Target Track Fusion

Directory of Open Access Journals (Sweden)

Yi Mao

2017-01-01

Full Text Available To realize common tactical picture in network-centered system, this paper proposes a layered architecture for distributed information processing and a method for distributed track fusion on the basis of analyzing the characteristics of network-centered systems. Basing on the noncorrelation of three-dimensional measurement of surveillance and reconnaissance sensors under polar coordinates, it also puts forward an algorithm for evaluating track quality (TQ using statistical decision theory. According to simulation results, the TQ value is associated with the measurement accuracy of sensors and the motion state of targets, which is well matched with the convergence process of tracking filters. Besides, the proposed algorithm has good reliability and timeliness in track quality evaluation.

An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhijun Yu

2009-01-01

Full Text Available This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR is chosen there as reference node for time difference of arrive (TDOA calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.

Image-based tracking and sensor resource management for UAVs in an urban environment

Science.gov (United States)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

Electronic evaluation for video commercials by impression index.

Science.gov (United States)

Kong, Wanzeng; Zhao, Xinxin; Hu, Sanqing; Vecchiato, Giovanni; Babiloni, Fabio

2013-12-01

How to evaluate the effect of commercials is significantly important in neuromarketing. In this paper, we proposed an electronic way to evaluate the influence of video commercials on consumers by impression index. The impression index combines both the memorization and attention index during consumers observing video commercials by tracking the EEG activity. It extracts features from scalp EEG to evaluate the effectiveness of video commercials in terms of time-frequency-space domain. And, the general global field power was used as an impression index for evaluation of video commercial scenes as time series. Results of experiment demonstrate that the proposed approach is able to track variations of the cerebral activity related to cognitive task such as observing video commercials, and help to judge whether the scene in video commercials is impressive or not by EEG signals.

Automated Indexing and Search of Video Data in Large Collections with inVideo

Directory of Open Access Journals (Sweden)

Shuangbao Paul Wang

2017-08-01

Full Text Available In this paper, we present a novel system, inVideo, for automatically indexing and searching videos based on the keywords spoken in the audio track and the visual content of the video frames. Using the highly efficient video indexing engine we developed, inVideo is able to analyze videos using machine learning and pattern recognition without the need for initial viewing by a human. The time-stamped commenting and tagging features refine the accuracy of search results. The cloud-based implementation makes it possible to conduct elastic search, augmented search, and data analytics. Our research shows that inVideo presents an efficient tool in processing and analyzing videos and increasing interactions in video-based online learning environment. Data from a cybersecurity program with more than 500 students show that applying inVideo to current video material, interactions between student-student and student-faculty increased significantly across 24 sections program-wide.

Target Response Adaptation for Correlation Filter Tracking

KAUST Repository

Bibi, Adel Aamer

2016-09-16

Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

Real time tracking by LOPF algorithm with mixture model

Science.gov (United States)

Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

2007-11-01

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

Enhancement system of nighttime infrared video image and visible video image

Science.gov (United States)

Wang, Yue; Piao, Yan

2016-11-01

Visibility of Nighttime video image has a great significance for military and medicine areas, but nighttime video image has so poor quality that we can't recognize the target and background. Thus we enhance the nighttime video image by fuse infrared video image and visible video image. According to the characteristics of infrared and visible images, we proposed improved sift algorithm andαβ weighted algorithm to fuse heterologous nighttime images. We would deduced a transfer matrix from improved sift algorithm. The transfer matrix would rapid register heterologous nighttime images. And theαβ weighted algorithm can be applied in any scene. In the video image fusion system, we used the transfer matrix to register every frame and then used αβ weighted method to fuse every frame, which reached the time requirement soft video. The fused video image not only retains the clear target information of infrared video image, but also retains the detail and color information of visible video image and the fused video image can fluency play.

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

Directory of Open Access Journals (Sweden)

Mohammad Javad Shafiee

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

Application of Fractional Fourier Transform to Moving Target Indication via Along-Track Interferometry

Directory of Open Access Journals (Sweden)

Chiu Shen

2005-01-01

Full Text Available A relatively unknown yet powerful technique, the so-called fractional Fourier transform (FrFT, is applied to SAR along-track interferometry (SAR-ATI in order to estimate moving target parameters. By mapping a target's signal onto a fractional Fourier axis, the FrFT permits a constant-velocity target to be focused in the fractional Fourier domain thereby affording orders of magnitude improvement in SCR. Moving target velocity and position parameters are derived and expressed in terms of an optimum fractional angle and a measured fractional Fourier position , allowing a target to be accurately repositioned and its velocity components computed without actually forming an SAR image. The new estimation algorithm is compared with the matched filter bank approach, showing some of the advantages of the FrFT method. The proposed technique is applied to the data acquired by the two-aperture CV580 airborne radar system configured in its along-track mode. Results show that the method is effective in estimating target velocity and position parameters.

Thermal Tracking of Sports Players

DEFF Research Database (Denmark)

Gade, Rikke; Moeslund, Thomas B.

2014-01-01

We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline...

Simulation of Anti-occlusion Arithmetic in Real-time Tracking of Video Objects%抗遮挡视频图像目标实时跟踪的仿真研究

Institute of Scientific and Technical Information of China (English)

赵林; 冯燕; 吕维

2011-01-01

In the tracking of moving targets in video, occlusion can make the appearance clues of the tracked targets such as the size and the colour lose reliability, and this can cause the wrong recognition and the inaccurate tracking. To overcome the problem, this paper presents an anti-occlusion tracking arithmetic which is based on the prediction of the target state and the scaning of local optical flow. Whether the target is in occlusion is predicted by employing the Kalman filtering and the colour feature. ff the object is in occlusion, the object information is updated by optimal positioning information of the local optical flow scaning. Experimental results produced by the Directshow software show that the algorithm can accurately track the moving object occluded by background or by other objects under the premise of the real-time requirement.%在视频运动目标跟踪中,遮挡的出现会使所跟踪目标的尺寸和色彩等外观线索失去可靠性,容易造成误识别,进而导致对于目标的错误跟踪.为了克服这一问题,提出了一种基于目标状态预测和局部光流扫描的抗遮挡跟踪算法.算法根据卡尔曼滤波和目标颜色特征信息,预测各目标是否处于遮挡状态,在目标处于遮挡的情况下,通过由局部光流扫描得到的最佳定位信息更新目标信息.在Directshow软件下的仿真结果表明,所提出算法能够在保证实时性的前提下,在运动目标被背景遮挡或被其它目标遮挡时均能实现较准确跟踪.

Video Game Use and Cognitive Performance: Does It Vary with the Presence of Problematic Video Game Use?

OpenAIRE

Collins, Emily; Freeman, Jonathan

2014-01-01

Action video game players have been found to outperform nonplayers on a variety of cognitive tasks. However, several failures to replicate these video game player advantages have indicated that this relationship may not be straightforward. Moreover, despite the discovery that problematic video game players do not appear to demonstrate the same superior performance as nonproblematic video game players in relation to multiple object tracking paradigms, this has not been investigated for other t...

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

Science.gov (United States)

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…

Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

Directory of Open Access Journals (Sweden)

Hamza Benzerrouk

2018-03-01

Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

Target tracking using a 2D radar

CSIR Research Space (South Africa)

Kriel, M

2012-08-01

Full Text Available stream_source_info Kriel_2012.pdf.txt stream_content_type text/plain stream_size 29522 Content-Encoding ISO-8859-1 stream_name Kriel_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 737 33 Target Tracking Using....410634] 0.000019 [ 0.000020]4000.0 0 0 250.0 3D AASC 3D AASC 3D AASC Er ro r (m ) Er ro r (m ) E rr o r (m ) Time (s) 0 0 250.0Time (s) 0 0 250.0Time (s) AACT : AASC : AACT : AASC : AACT : 4000.0 4000.0 FIGURE 33...

Robust online face tracking-by-detection

NARCIS (Netherlands)

Comaschi, F.; Stuijk, S.; Basten, T.; Corporaal, H.

2016-01-01

The problem of online face tracking from unconstrained videos is still unresolved. Challenges range from coping with severe online appearance variations to coping with occlusion. We propose RFTD (Robust Face Tracking-by-Detection), a system which combines tracking and detection into a single

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

Directory of Open Access Journals (Sweden)

Anne-Marie Brouwer

2017-05-01

Full Text Available 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.

Fall detection in the elderly by head-tracking

OpenAIRE

Yu, Miao; Naqvi, Syed Mohsen; Chambers, Jonathan

2009-01-01

In the paper, we propose a fall detection method based on head tracking within a smart home environment equipped with video cameras. A motion history image and code-book background subtraction are combined to determine whether large movement occurs within the scene. Based on the magnitude of the movement information, particle filters with different state models are used to track the head. The head tracking procedure is performed in two video streams taken bytwoseparatecamerasandthree-dimension...

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

International Nuclear Information System (INIS)

Ingram, S; Rao, A; Wendt, R; Castillo, R; Court, L; Yang, J; Beadle, B

2014-01-01

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

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

Institute of Scientific and Technical Information of China (English)

LI Shuo; TAO Ran

2006-01-01

We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

Science.gov (United States)

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

GPU-accelerated 3-D model-based tracking

International Nuclear Information System (INIS)

Brown, J Anthony; Capson, David W

2010-01-01

Model-based approaches to tracking the pose of a 3-D object in video are effective but computationally demanding. While statistical estimation techniques, such as the particle filter, are often employed to minimize the search space, real-time performance remains unachievable on current generation CPUs. Recent advances in graphics processing units (GPUs) have brought massively parallel computational power to the desktop environment and powerful developer tools, such as NVIDIA Compute Unified Device Architecture (CUDA), have provided programmers with a mechanism to exploit it. NVIDIA GPUs' single-instruction multiple-thread (SIMT) programming model is well-suited to many computer vision tasks, particularly model-based tracking, which requires several hundred 3-D model poses to be dynamically configured, rendered, and evaluated against each frame in the video sequence. Using 6 degree-of-freedom (DOF) rigid hand tracking as an example application, this work harnesses consumer-grade GPUs to achieve real-time, 3-D model-based, markerless object tracking in monocular video.

Coding visual features extracted from video sequences.

Science.gov (United States)

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

Effectiveness of an Automatic Tracking Software in Underwater Motion Analysis

Directory of Open Access Journals (Sweden)

Fabrício A. Magalhaes

2013-12-01

Full Text Available Tracking of markers placed on anatomical landmarks is a common practice in sports science to perform the kinematic analysis that interests both athletes and coaches. Although different software programs have been developed to automatically track markers and/or features, none of them was specifically designed to analyze underwater motion. Hence, this study aimed to evaluate the effectiveness of a software developed for automatic tracking of underwater movements (DVP, based on the Kanade-Lucas-Tomasi feature tracker. Twenty-one video recordings of different aquatic exercises (n = 2940 markers’ positions were manually tracked to determine the markers’ center coordinates. Then, the videos were automatically tracked using DVP and a commercially available software (COM. Since tracking techniques may produce false targets, an operator was instructed to stop the automatic procedure and to correct the position of the cursor when the distance between the calculated marker’s coordinate and the reference one was higher than 4 pixels. The proportion of manual interventions required by the software was used as a measure of the degree of automation. Overall, manual interventions were 10.4% lower for DVP (7.4% than for COM (17.8%. Moreover, when examining the different exercise modes separately, the percentage of manual interventions was 5.6% to 29.3% lower for DVP than for COM. Similar results were observed when analyzing the type of marker rather than the type of exercise, with 9.9% less manual interventions for DVP than for COM. In conclusion, based on these results, the developed automatic tracking software presented can be used as a valid and useful tool for underwater motion analysis.

Some Aspects on Filter Design for Target Tracking

Directory of Open Access Journals (Sweden)

Bertil Ekstrand

2012-01-01

Full Text Available Tracking filter design is discussed. It is argued that the basis of the present stochastic paradigm is questionable. White process noise is not adequate as a model for target manoeuvring, stochastic least-square optimality is not relevant or required in practice, the fact that requirements are necessary for design is ignored, and root mean square (RMS errors are insufficient as performance measure. It is argued that there is no process noise and that the covariance of the assumed process noise contains the design parameters. Focus is on the basic tracking filter, the Kalman filter, which is convenient for clarity and simplicity, but the arguments and conclusions are relevant in general. For design the possibility of an observer transfer function approach is pointed out. The issues can also be considered as a consequence of the fact that there is a difference between estimation and design. The - filter is used for illustration.

Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

Directory of Open Access Journals (Sweden)

Bineng Zhong

Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

Understanding Learning Style by Eye Tracking in Slide Video Learning

Science.gov (United States)

Cao, Jianxia; Nishihara, Akinori

2012-01-01

More and more videos are now being used in e-learning context. For improving learning effect, to understand how students view the online video is important. In this research, we investigate how students deploy their attention when they learn through interactive slide video in the aim of better understanding observers' learning style. Felder and…

An Energy-Efficient Sleep Strategy for Target Tracking Sensor Networks

Directory of Open Access Journals (Sweden)

Juan FENG

2014-02-01

Full Text Available Energy efficiency is very important for sensor networks since sensor nodes have limited energy supply from battery. So far, many researches have been focused on this issue, while less emphasis was placed on the optimal sleep time of each node. This paper proposed an adaptive energy conservation strategy for target tracking based on a grid network structure, where each node autonomously determines when and if to sleep. It allows sensor nodes far away from targets to sleep to save energy and guarantee the tracking accuracy. The proposed approach extend network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of sensor nodes. And each node can choose an optimal sleep time so as to make system adaptive and energy-efficient. We show the performance of our approach in terms of energy drop, comparing it to a naive approach, dynamic PM with fixed sleep time and the coordinate PM strategies. From the experimental results, it is readily seen that the efficiency of the proposed approach.

Activity-based exploitation of Full Motion Video (FMV)

Science.gov (United States)

Kant, Shashi

2012-06-01

Video has been a game-changer in how US forces are able to find, track and defeat its adversaries. With millions of minutes of video being generated from an increasing number of sensor platforms, the DOD has stated that the rapid increase in video is overwhelming their analysts. The manpower required to view and garner useable information from the flood of video is unaffordable, especially in light of current fiscal restraints. "Search" within full-motion video has traditionally relied on human tagging of content, and video metadata, to provision filtering and locate segments of interest, in the context of analyst query. Our approach utilizes a novel machine-vision based approach to index FMV, using object recognition & tracking, events and activities detection. This approach enables FMV exploitation in real-time, as well as a forensic look-back within archives. This approach can help get the most information out of video sensor collection, help focus the attention of overburdened analysts form connections in activity over time and conserve national fiscal resources in exploiting FMV.

Target tracking and surveillance by fusing stereo and RFID information

Science.gov (United States)

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.

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

Science.gov (United States)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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.

Clustering and fault tolerance for target tracking using wireless sensor networks

International Nuclear Information System (INIS)

Bhatti, S.; Khanzada, S.; Memon, S.

2012-01-01

Over the last few years, the deployment of WSNs (Wireless Sensor Networks) has been fostered in diverse applications. WSN has great potential for a variety of domains ranging from scientific experiments to commercial applications. Due to the deployment of WSNs in dynamic and unpredictable environments. They have potential to cope with variety of faults. This paper proposes an energy-aware fault-tolerant clustering protocol for target tracking applications termed as the FITf (Fault Tolerant Target Tracking) protocol The identification of RNs (Redundant Nodes) makes SN (Sensor Node) fault tolerance plausible and the clustering endorsed recovery of sensors supervised by a faulty CH (Cluster Head). The FfTT protocol intends two steps of reducing energy consumption: first, by identifying RNs in the network; secondly, by restricting the numbers of SNs sending data to the CH. Simulations validate the scalability and low power consumption of the FITf protocol in comparison with LEACH protocol. (author)

Light-reflection random-target method for measurement of the modulation transfer function of a digital video-camera

Czech Academy of Sciences Publication Activity Database

Pospíšil, Jaroslav; Jakubík, P.; Machala, L.

2005-01-01

Roč. 116, - (2005), s. 573-585 ISSN 0030-4026 Institutional research plan: CEZ:AV0Z10100522 Keywords : random-target measuring method * light-reflection white - noise target * digital video camera * modulation transfer function * power spectral density Subject RIV: BH - Optics, Masers, Lasers Impact factor: 0.395, year: 2005

DMPDS: A Fast Motion Estimation Algorithm Targeting High Resolution Videos and Its FPGA Implementation

Directory of Open Access Journals (Sweden)

Gustavo Sanchez

2012-01-01

Full Text Available This paper presents a new fast motion estimation (ME algorithm targeting high resolution digital videos and its efficient hardware architecture design. The new Dynamic Multipoint Diamond Search (DMPDS algorithm is a fast algorithm which increases the ME quality when compared with other fast ME algorithms. The DMPDS achieves a better digital video quality reducing the occurrence of local minima falls, especially in high definition videos. The quality results show that the DMPDS is able to reach an average PSNR gain of 1.85 dB when compared with the well-known Diamond Search (DS algorithm. When compared to the optimum results generated by the Full Search (FS algorithm the DMPDS shows a lose of only 1.03 dB in the PSNR. On the other hand, the DMPDS reached a complexity reduction higher than 45 times when compared to FS. The quality gains related to DS caused an expected increase in the DMPDS complexity which uses 6.4-times more calculations than DS. The DMPDS architecture was designed focused on high performance and low cost, targeting to process Quad Full High Definition (QFHD videos in real time (30 frames per second. The architecture was described in VHDL and synthesized to Altera Stratix 4 and Xilinx Virtex 5 FPGAs. The synthesis results show that the architecture is able to achieve processing rates higher than 53 QFHD fps, reaching the real-time requirements. The DMPDS architecture achieved the highest processing rate when compared to related works in the literature. This high processing rate was obtained designing an architecture with a high operation frequency and low numbers of cycles necessary to process each block.

Use of a track and vertex processor in a fixed-target charm experiment

International Nuclear Information System (INIS)

Schub, M.H.; Carey, T.A.; Hsiung, Y.B.; Kaplan, D.M.; Lee, C.; Miller, G.; Sa, J.; Teng, P.K.

1996-01-01

We have constructed and operated a high-speed parallel-pipelined track and vertex processor and used it to trigger data acquisition in a high-rate charm and beauty experiment at Fermilab. The processor uses information from hodoscopes and wire chambers to reconstruct tracks in the bend view of a magnetic spectrometer, and uses these tracks to find the corresponding tracks in a set of silicon-strip detectors. The processor then forms vertices and triggers the experiment if at least one vertex is downstream of the target. Under typical charm running conditions, with an interaction rate of ∼5 MHz, the processor rejects 80-90% of lower-level triggers while maintaining efficiency of ∼70% for two-prong D-meson decays. (orig.)

Automatic radar target recognition of objects falling on railway tracks

International Nuclear Information System (INIS)

Mroué, A; Heddebaut, M; Elbahhar, F; Rivenq, A; Rouvaen, J-M

2012-01-01

This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers

NucliTrack: an integrated nuclei tracking application.

Science.gov (United States)

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.

User-assisted video segmentation system for visual communication

Science.gov (United States)

Wu, Zhengping; Chen, Chun

2002-01-01

Video segmentation plays an important role for efficient storage and transmission in visual communication. In this paper, we introduce a novel video segmentation system using point tracking and contour formation techniques. Inspired by the results from the study of the human visual system, we intend to solve the video segmentation problem into three separate phases: user-assisted feature points selection, feature points' automatic tracking, and contour formation. This splitting relieves the computer of ill-posed automatic segmentation problems, and allows a higher level of flexibility of the method. First, the precise feature points can be found using a combination of user assistance and an eigenvalue-based adjustment. Second, the feature points in the remaining frames are obtained using motion estimation and point refinement. At last, contour formation is used to extract the object, and plus a point insertion process to provide the feature points for next frame's tracking.

Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Dao-Wei Bi

2007-07-01

Full Text Available A primary criterion of wireless sensor network is energy efficiency. Focused onthe energy problem of target tracking in wireless sensor networks, this paper proposes acluster-based dynamic energy management mechanism. Target tracking problem isformulated by the multi-sensor detection model as well as energy consumption model. Adistributed adaptive clustering approach is investigated to form a reasonable routingframework which has uniform cluster head distribution. Dijkstra’s algorithm is utilized toobtain optimal intra-cluster routing. Target position is predicted by particle filter. Thepredicted target position is adopted to estimate the idle interval of sensor nodes. Hence,dynamic awakening approach is exploited to prolong sleep time of sensor nodes so that theoperation energy consumption of wireless sensor network can be reduced. The sensornodes around the target wake up on time and act as sensing candidates. With the candidatesensor nodes and predicted target position, the optimal sensor node selection is considered.Binary particle swarm optimization is proposed to minimize the total energy consumptionduring collaborative sensing and data reporting. Experimental results verify that theproposed clustering approach establishes a low-energy communication structure while theenergy efficiency of wireless sensor networks is enhanced by cluster-based dynamic energymanagement.

Tracking Honey Bees Using LIDAR (Light Detection and Ranging) Technology

Energy Technology Data Exchange (ETDEWEB)

BENDER, SUSAN FAE ANN; RODACY, PHILIP J.; SCHMITT, RANDAL L.; HARGIS JR., PHILIP J.; JOHNSON, MARK S.; KLARKOWSKI, JAMES R.; MAGEE, GLEN I.; BENDER, GARY LEE

2003-01-01

The Defense Advanced Research Projects Agency (DARPA) has recognized that biological and chemical toxins are a real and growing threat to troops, civilians, and the ecosystem. The Explosives Components Facility at Sandia National Laboratories (SNL) has been working with the University of Montana, the Southwest Research Institute, and other agencies to evaluate the feasibility of directing honeybees to specific targets, and for environmental sampling of biological and chemical ''agents of harm''. Recent work has focused on finding and locating buried landmines and unexploded ordnance (UXO). Tests have demonstrated that honeybees can be trained to efficiently and accurately locate explosive signatures in the environment. However, it is difficult to visually track the bees and determine precisely where the targets are located. Video equipment is not practical due to its limited resolution and range. In addition, it is often unsafe to install such equipment in a field. A technology is needed to provide investigators with the standoff capability to track bees and accurately map the location of the suspected targets. This report documents Light Detection and Ranging (LIDAR) tests that were performed by SNL. These tests have shown that a LIDAR system can be used to track honeybees. The LIDAR system can provide both the range and coordinates of the target so that the location of buried munitions can be accurately mapped for subsequent removal.

Trade-Off Exploration for Target Tracking Application in a Customized Multiprocessor Architecture

Directory of Open Access Journals (Sweden)

Yassin El-Hillali

2009-01-01

Full Text Available This paper presents the design of an FPGA-based multiprocessor-system-on-chip (MPSoC architecture optimized for Multiple Target Tracking (MTT in automotive applications. An MTT system uses an automotive radar to track the speed and relative position of all the vehicles (targets within its field of view. As the number of targets increases, the computational needs of the MTT system also increase making it difficult for a single processor to handle it alone. Our implementation distributes the computational load among multiple soft processor cores optimized for executing specific computational tasks. The paper explains how we designed and profiled the MTT application to partition it among different processors. It also explains how we applied different optimizations to customize the individual processor cores to their assigned tasks and to assess their impact on performance and FPGA resource utilization. The result is a complete MTT application running on an optimized MPSoC architecture that fits in a contemporary medium-sized FPGA and that meets the application's real-time constraints.

Greenhouse gas emission trends and projections in Europe 2011. Tracking progress towards Kyoto and 2020 targets

Energy Technology Data Exchange (ETDEWEB)

Busche, J.; Scheffler, M.; Graichen, V. (Umweltbundesamt, Vienna (Austria)) (and others)

2011-10-15

At the end of 2010, the EU-15 was on track to achieve its Kyoto target but three EU-15 Member States (Austria, Italy and Luxembourg) were not on track to meet their burden-sharing targets. These countries must therefore seriously consider further action to ensure compliance, in particular revising their plans on using flexible mechanisms. Among the EEA member countries outside the EU, Liechtenstein and Switzerland were not on track to achieve their Kyoto target at the end of 2009. All other European countries are on track to meet their targets, either based on domestic emissions only or with the assistance of Kyoto mechanisms. The economic recession had a significant impact on the EU's total greenhouse gas (GHG) emission trends but a more limited effect on progress towards Kyoto targets. This is because emissions in the sectors covered by the EU Emissions Trading Scheme (ETS), which were most affected by the crisis, do not affect Kyoto compliance once ETS caps have been set. With existing national measures, Member States do not project enough emission reductions for the EU to meet its unilateral 20 % reduction commitment in 2020. Additional measures currently planned by Member States will help further reduce emissions but will be insufficient to achieve the important emission cuts needed in the longer term. By 2020 Member States must enhance their efforts to reduce emissions in non-EU ETS sectors, such as the residential, transport or agriculture sectors, where legally binding national targets have been set under the EU's 2009 climate and energy package. (Author)

Hybrid markerless tracking of complex articulated motion in golf swings.

Science.gov (United States)

Fung, Sim Kwoh; Sundaraj, Kenneth; Ahamed, Nizam Uddin; Kiang, Lam Chee; Nadarajah, Sivadev; Sahayadhas, Arun; Ali, Md Asraf; Islam, Md Anamul; Palaniappan, Rajkumar

2014-04-01

Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfer's head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

People detection in nuclear plants by video processing for safety purpose

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN), Rio de Janeiro, RJ (Brazil); Seixas, Jose M.; Silva, Eduardo Antonio B., E-mail: seixas@lps.ufrj.b, E-mail: eduardo@lps.ufrj.b [Coordenacao dos Programas de Pos-Graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Eletrica; Cota, Raphael E.; Ramos, Bruno L., E-mail: brunolange@poli.ufrj.b [Universidade Federal do Rio de Janeiro (EP/UFRJ), RJ (Brazil). Dept. de Engenharia Eletronica e de Computacao

2011-07-01

This work describes the development of a surveillance system for safety purposes in nuclear plants. The final objective is to track people online in videos, in order to estimate the dose received by personnel, during the execution of working tasks in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a real nuclear plant at Instituto de Engenharia Nuclear, Argonauta nuclear research reactor. Cameras have been installed within Argonauta's room, supplying the data needed. Both video processing and statistical signal processing techniques may be used for detection, segmentation and tracking people in video. This first paper reports people segmentation in video using background subtraction, by two different approaches, namely frame differences, and blind signal separation based on the independent component analysis method. Results are commented, along with perspectives for further work. (author)

People detection in nuclear plants by video processing for safety purpose

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Seixas, Jose M.; Silva, Eduardo Antonio B.; Cota, Raphael E.; Ramos, Bruno L.

2011-01-01

This work describes the development of a surveillance system for safety purposes in nuclear plants. The final objective is to track people online in videos, in order to estimate the dose received by personnel, during the execution of working tasks in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a real nuclear plant at Instituto de Engenharia Nuclear, Argonauta nuclear research reactor. Cameras have been installed within Argonauta's room, supplying the data needed. Both video processing and statistical signal processing techniques may be used for detection, segmentation and tracking people in video. This first paper reports people segmentation in video using background subtraction, by two different approaches, namely frame differences, and blind signal separation based on the independent component analysis method. Results are commented, along with perspectives for further work. (author)

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Mü ller, Matthias; Bibi, Adel Aamer; Giancola, Silvio; Al-Subaihi, Salman; Ghanem, Bernard

2018-01-01

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Müller, Matthias

2018-03-28

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

Determining nest predators of the Least Bell's Vireo through point counts, tracking stations, and video photography

Science.gov (United States)

Peterson, Bonnie L.; Kus, Barbara E.; Deutschman, Douglas H.

2004-01-01

We compared three methods to determine nest predators of the Least Bell's Vireo (Vireo bellii pusillus) in San Diego County, California, during spring and summer 2000. Point counts and tracking stations were used to identify potential predators and video photography to document actual nest predators. Parental behavior at depredated nests was compared to that at successful nests to determine whether activity (frequency of trips to and from the nest) and singing vs. non-singing on the nest affected nest predation. Yellow-breasted Chats (Icteria virens) were the most abundant potential avian predator, followed by Western Scrub-Jays (Aphelocoma californica). Coyotes (Canis latrans) were abundant, with smaller mammalian predators occurring in low abundance. Cameras documented a 48% predation rate with scrub-jays as the major nest predators (67%), but Virginia opossums (Didelphis virginiana, 17%), gopher snakes (Pituophis melanoleucus, 8%) and Argentine ants (Linepithema humile, 8%) were also confirmed predators. Identification of potential predators from tracking stations and point counts demonstrated only moderate correspondence with actual nest predators. Parental behavior at the nest prior to depredation was not related to nest outcome.

Tracking of TV and video gaming during childhood: Iowa Bone Development Study.

Science.gov (United States)

Francis, Shelby L; Stancel, Matthew J; Sernulka-George, Frances D; Broffitt, Barbara; Levy, Steven M; Janz, Kathleen F

2011-09-24

Tracking studies determine the stability and predictability of specific phenomena. This study examined tracking of TV viewing (TV) and video game use (VG) from middle childhood through early adolescence after adjusting for moderate and vigorous physical activity (MVPA), percentage of body fat (% BF), and maturity. TV viewing and VG use were measured at ages 5, 8, 11, and 13 (n = 434) via parental- and self-report. MVPA was measured using the Actigraph, % BF using dual-energy x-ray absorptiometry, and maturity via Mirwald predictive equations. Generalized Estimating Equations (GEE) were used to assess stability and logistic regression was used to predict children "at risk" for maintaining sedentary behaviors. Additional models examined tracking only in overfat children (boys ≥ 25% BF; girls ≥ 32% BF). Data were collected from 1998 to 2007 and analyzed in 2010. The adjusted stability coefficients (GEE) for TV viewing were 0.35 (95% CI = 0.26, 0.44) for boys, 0.32 (0.23, 0.40) for girls, and 0.45 (0.27, 0.64) for overfat. For VG use, the adjusted stability coefficients were 0.14 (0.05, 0.24) for boys, 0.24 (0.10, 0.38) for girls, and 0.29 (0.08, 0.50) for overfat. The adjusted odds ratios (OR) for TV viewing were 3.2 (2.0, 5.2) for boys, 2.9 (1.9, 4.6) for girls, and 6.2 (2.2, 17.2) for overfat. For VG use, the OR were 1.8 (1.1, 3.1) for boys, 3.5 (2.1, 5.8) for girls, and 1.9 (0.6, 6.1) for overfat. TV viewing and VG use are moderately stable throughout childhood and predictive of later behavior. TV viewing appears to be more stable in younger children than VG use and more predictive of later behavior. Since habitual patterns of sedentarism in young children tend to continue to adolescence, early intervention strategies, particularly to reduce TV viewing, are warranted.

Tracking of TV and video gaming during childhood: Iowa Bone Development Study

Directory of Open Access Journals (Sweden)

Broffitt Barbara

2011-09-01

Full Text Available Abstract Background Tracking studies determine the stability and predictability of specific phenomena. This study examined tracking of TV viewing (TV and video game use (VG from middle childhood through early adolescence after adjusting for moderate and vigorous physical activity (MVPA, percentage of body fat (% BF, and maturity. Methods TV viewing and VG use were measured at ages 5, 8, 11, and 13 (n = 434 via parental- and self-report. MVPA was measured using the Actigraph, % BF using dual-energy x-ray absorptiometry, and maturity via Mirwald predictive equations. Generalized Estimating Equations (GEE were used to assess stability and logistic regression was used to predict children "at risk" for maintaining sedentary behaviors. Additional models examined tracking only in overfat children (boys ≥ 25% BF; girls ≥ 32% BF. Data were collected from 1998 to 2007 and analyzed in 2010. Results The adjusted stability coefficients (GEE for TV viewing were 0.35 (95% CI = 0.26, 0.44 for boys, 0.32 (0.23, 0.40 for girls, and 0.45 (0.27, 0.64 for overfat. For VG use, the adjusted stability coefficients were 0.14 (0.05, 0.24 for boys, 0.24 (0.10, 0.38 for girls, and 0.29 (0.08, 0.50 for overfat. The adjusted odds ratios (OR for TV viewing were 3.2 (2.0, 5.2 for boys, 2.9 (1.9, 4.6 for girls, and 6.2 (2.2, 17.2 for overfat. For VG use, the OR were 1.8 (1.1, 3.1 for boys, 3.5 (2.1, 5.8 for girls, and 1.9 (0.6, 6.1 for overfat. Conclusions TV viewing and VG use are moderately stable throughout childhood and predictive of later behavior. TV viewing appears to be more stable in younger children than VG use and more predictive of later behavior. Since habitual patterns of sedentarism in young children tend to continue to adolescence, early intervention strategies, particularly to reduce TV viewing, are warranted.

Tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

Directory of Open Access Journals (Sweden)

Linhai Gan

2017-01-01

Full Text Available The random matrix (RM method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.

Anesthesia and fast-track in video-assisted thoracic surgery (VATS): from evidence to practice.

Science.gov (United States)

Umari, Marzia; Falini, Stefano; Segat, Matteo; Zuliani, Michele; Crisman, Marco; Comuzzi, Lucia; Pagos, Francesco; Lovadina, Stefano; Lucangelo, Umberto

2018-03-01

In thoracic surgery, the introduction of video-assisted thoracoscopic techniques has allowed the development of fast-track protocols, with shorter hospital lengths of stay and improved outcomes. The perioperative management needs to be optimized accordingly, with the goal of reducing postoperative complications and speeding recovery times. Premedication performed in the operative room should be wisely administered because often linked to late discharge from the post-anesthesia care unit (PACU). Inhalatory anesthesia, when possible, should be preferred based on protective effects on postoperative lung inflammation. Deep neuromuscular blockade should be pursued and carefully monitored, and an appropriate reversal administered before extubation. Management of one-lung ventilation (OLV) needs to be optimized to prevent not only intraoperative hypoxemia but also postoperative acute lung injury (ALI): protective ventilation strategies are therefore to be implemented. Locoregional techniques should be favored over intravenous analgesia: the thoracic epidural, the paravertebral block (PVB), the intercostal nerve block (ICNB), and the serratus anterior plane block (SAPB) are thoroughly reviewed and the most common dosages are reported. Fluid therapy needs to be administered critically, to avoid both overload and cardiovascular compromisation. All these practices are analyzed singularly with the aid of the most recent evidences aimed at the best patient care. Finally, a few notes on some of the latest trends in research are presented, such as non-intubated video-assisted thoracoscopic surgery (VATS) and intravenous lidocaine.

Video Conferencing for a Virtual Seminar Room

DEFF Research Database (Denmark)

Forchhammer, Søren; Fosgerau, A.; Hansen, Peter Søren K.

2002-01-01

A PC-based video conferencing system for a virtual seminar room is presented. The platform is enhanced with DSPs for audio and video coding and processing. A microphone array is used to facilitate audio based speaker tracking, which is used for adaptive beam-forming and automatic camera...

Detection of Visual Events in Underwater Video Using a Neuromorphic Saliency-based Attention System

Science.gov (United States)

Edgington, D. R.; Walther, D.; Cline, D. E.; Sherlock, R.; Salamy, K. A.; Wilson, A.; Koch, C.

2003-12-01

The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment on remotely operated vehicles (ROV) to obtain quantitative data on the distribution and abundance of oceanic animals. High-quality video data supplants the traditional approach of assessing the kinds and numbers of animals in the oceanic water column through towing collection nets behind ships. Tow nets are limited in spatial resolution, and often destroy abundant gelatinous animals resulting in species undersampling. Video camera-based quantitative video transects (QVT) are taken through the ocean midwater, from 50m to 4000m, and provide high-resolution data at the scale of the individual animals and their natural aggregation patterns. However, the current manual method of analyzing QVT video by trained scientists is labor intensive and poses a serious limitation to the amount of information that can be analyzed from ROV dives. Presented here is an automated system for detecting marine animals (events) visible in the videos. Automated detection is difficult due to the low contrast of many translucent animals and due to debris ("marine snow") cluttering the scene. Video frames are processed with an artificial intelligence attention selection algorithm that has proven a robust means of target detection in a variety of natural terrestrial scenes. The candidate locations identified by the attention selection module are tracked across video frames using linear Kalman filters. Typically, the occurrence of visible animals in the video footage is sparse in space and time. A notion of "boring" video frames is developed by detecting whether or not there is an interesting candidate object for an animal present in a particular sequence of underwater video -- video frames that do not contain any "interesting" events. If objects can be tracked successfully over several frames, they are stored as potentially "interesting" events. Based on low-level properties, interesting events are

A Cubature-Principle-Assisted IMM-Adaptive UKF Algorithm for Maneuvering Target Tracking Caused by Sensor Faults

Directory of Open Access Journals (Sweden)

Huan Zhou

2017-09-01

Full Text Available Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF algorithm. By dividing the IMM-UKF into two links, the algorithm introduces the cubature principle to approximate the probability density of the random variable, after the interaction, by considering the external link of IMM-UKF, which constitutes the cubature-principle-assisted IMM method (CPIMM for solving the non-Gaussian problem, and leads to an adaptive matrix to balance the contribution of the state. The algorithm provides filtering solutions by considering the internal link of IMM-UKF, which is called a new adaptive UKF algorithm (NAUKF to address sensor faults. The proposed CPIMM-NAUKF is evaluated in a numerical simulation and two practical experiments including one navigation experiment and one maneuvering target tracking experiment. The simulation and experiment results show that the proposed CPIMM-NAUKF has greater filtering precision and faster convergence than the existing IMM-UKF. The proposed algorithm achieves a very good tracking performance, and will be effective and applicable in the field of maneuvering target tracking.

Fish4Knowledge collecting and analyzing massive coral reef fish video data

CERN Document Server

Chen-Burger, Yun-Heh; Giordano, Daniela; Hardman, Lynda; Lin, Fang-Pang

2016-01-01

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see ho...

Improved people detection in nuclear plants by video processing for safety purpose

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R., E-mail: calexandre@ien.gov.br, E-mail: mol@ien.gov.br, E-mail: paulov@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Seixas, Jose M.; Silva, Eduardo Antonio B., E-mail: seixas@lps.ufrj.br, E-mail: eduardo@smt.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Eletrica; Waintraub, Fabio, E-mail: fabiowaintraub@hotmail.com [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Escola Politecnica. Departamento de Engenharia Eletronica e de Computacao

2013-07-01

This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

Improved people detection in nuclear plants by video processing for safety purpose

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R.; Seixas, Jose M.; Silva, Eduardo Antonio B.; Waintraub, Fabio

2013-01-01

This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

Nonmyopic Sensor Scheduling and its Efficient Implementation for Target Tracking Applications

Directory of Open Access Journals (Sweden)

Morrell Darryl

2006-01-01

Full Text Available We propose two nonmyopic sensor scheduling algorithms for target tracking applications. We consider a scenario where a bearing-only sensor is constrained to move in a finite number of directions to track a target in a two-dimensional plane. Both algorithms provide the best sensor sequence by minimizing a predicted expected scheduler cost over a finite time-horizon. The first algorithm approximately computes the scheduler costs based on the predicted covariance matrix of the tracker error. The second algorithm uses the unscented transform in conjunction with a particle filter to approximate covariance-based costs or information-theoretic costs. We also propose the use of two branch-and-bound-based optimal pruning algorithms for efficient implementation of the scheduling algorithms. We design the first pruning algorithm by combining branch-and-bound with a breadth-first search and a greedy-search; the second pruning algorithm combines branch-and-bound with a uniform-cost search. Simulation results demonstrate the advantage of nonmyopic scheduling over myopic scheduling and the significant savings in computational and memory resources when using the pruning algorithms.

Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

KAUST Repository

Zhang, Tianzhu

2014-06-19

Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

Robust Individual-Cell/Object Tracking via PCANet Deep Network in Biomedicine and Computer Vision

Directory of Open Access Journals (Sweden)

Bineng Zhong

2016-01-01

Full Text Available Tracking individual-cell/object over time is important in understanding drug treatment effects on cancer cells and video surveillance. A fundamental problem of individual-cell/object tracking is to simultaneously address the cell/object appearance variations caused by intrinsic and extrinsic factors. In this paper, inspired by the architecture of deep learning, we propose a robust feature learning method for constructing discriminative appearance models without large-scale pretraining. Specifically, in the initial frames, an unsupervised method is firstly used to learn the abstract feature of a target by exploiting both classic principal component analysis (PCA algorithms with recent deep learning representation architectures. We use learned PCA eigenvectors as filters and develop a novel algorithm to represent a target by composing of a PCA-based filter bank layer, a nonlinear layer, and a patch-based pooling layer, respectively. Then, based on the feature representation, a neural network with one hidden layer is trained in a supervised mode to construct a discriminative appearance model. Finally, to alleviate the tracker drifting problem, a sample update scheme is carefully designed to keep track of the most representative and diverse samples during tracking. We test the proposed tracking method on two standard individual cell/object tracking benchmarks to show our tracker's state-of-the-art performance.

An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream

Directory of Open Access Journals (Sweden)

Li Yao

2014-01-01

Full Text Available Modeling background and segmenting moving objects are significant techniques for computer vision applications. Mixture-of-Gaussians (MoG background model is commonly used in foreground extraction in video steam. However considering the case that the objects enter the scenery and stay for a while, the foreground extraction would fail as the objects stay still and gradually merge into the background. In this paper, we adopt a blob tracking method to cope with this situation. To construct the MoG model more quickly, we add frame difference method to the foreground extracted from MoG for very crowded situations. What is more, a new shadow removal method based on RGB color space is proposed.

Detection of goal events in soccer videos

Science.gov (United States)

Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

2005-01-01

In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

Brief Report: Broad Autism Phenotype in Adults Is Associated with Performance on an Eye-Tracking Measure of Joint Attention

Science.gov (United States)

Swanson, Meghan R.; Siller, Michael

2014-01-01

The current study takes advantage of modern eye-tracking technology and evaluates how individuals allocate their attention when viewing social videos that display an adult model who is gazing at a series of targets that appear and disappear in the four corners of the screen (congruent condition), or gazing elsewhere (incongruent condition). Data…

Tracking 20 years of compound-to-target output from literature and patents.

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Christopher Southan

Full Text Available 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

Greenhouse gas emission trends and projections in Europe 2012. Tracking progress towards Kyoto and 2020 targets

Energy Technology Data Exchange (ETDEWEB)

Gores, S.; Scheffler, M.; Graichen, V. [Oeko-Institut (Oeko), Freiburg (Germany)] [and others

2012-10-15

At the end of 2011, almost all European countries were on track towards their Kyoto targets for 2008-2012. The EU-15 also remained on track to achieve its Kyoto target. Italy, however, was not on track. Spain plans to acquire a large quantity of Kyoto units through the KP's flexible mechanisms to achieve its target. With emission caps already set for the economic sectors under the EU Emissions Trading Scheme (EU ETS), emissions reductions during 2012 in the sectors outside the EU ETS together with reductions by carbon sinks will set the frame for how many Kyoto units Member States need to acquire to reach their individual targets. Hence, both the development and delivery of adequate plans to acquire enough Kyoto credits is becoming increasingly important. ETS emissions from 2008 to 2011 were on average 5 % below these caps, which results in an oversupply of allowances. The EU ETS is undergoing important changes in view of the third trading phase from 2013 to 2020. Most EU Member States project that in 2020, their emissions outside the EU ETS will be lower than their national targets set under the Climate and Energy Package. However, further efforts will be necessary to achieve longer term reductions. (Author)

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

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

2013-11-01

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

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

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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

Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

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Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

2017-10-01

Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

Automatic video surveillance of outdoor scenes using track before detect

DEFF Research Database (Denmark)

Hansen, Morten; Sørensen, Helge Bjarup Dissing; Birkemark, Christian M.

2005-01-01

This paper concerns automatic video surveillance of outdoor scenes using a single camera. The first step in automatic interpretation of the video stream is activity detection based on background subtraction. Usually, this process will generate a large number of false alarms in outdoor scenes due...

An adaptive approach to human motion tracking from video

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Wu, Lifang; Chen, Chang Wen

2010-07-01

Vision based human motion tracking has drawn considerable interests recently because of its extensive applications. In this paper, we propose an approach to tracking the body motion of human balancing on each foot. The ability to balance properly is an important indication of neurological condition. Comparing with many other human motion tracking, there is much less occlusion in human balancing tracking. This less constrained problem allows us to combine a 2D model of human body with image analysis techniques to develop an efficient motion tracking algorithm. First we define a hierarchical 2D model consisting of six components including head, body and four limbs. Each of the four limbs involves primary component (upper arms and legs) and secondary component (lower arms and legs) respectively. In this model, we assume each of the components can be represented by quadrangles and every component is connected to one of others by a joint. By making use of inherent correlation between different components, we design a top-down updating framework and an adaptive algorithm with constraints of foreground regions for robust and efficient tracking. The approach has been tested using the balancing movement in HumanEva-I/II dataset. The average tracking time is under one second, which is much shorter than most of current schemes.

Inertial fusion energy target injection, tracking, and beam pointing

International Nuclear Information System (INIS)

Petzoldt, R.W.

1995-01-01

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. 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

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

Science.gov (United States)

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

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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

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Hua Liu

2017-06-01

Full Text Available 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.

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

Science.gov (United States)

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).

REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

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M. S. Temiz

2012-07-01

Full Text Available In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.

A framework for multi-object tracking over distributed wireless camera networks

Science.gov (United States)

Gau, Victor; Hwang, Jenq-Neng

2010-07-01

In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

Object tracking mask-based NLUT on GPUs for real-time generation of holographic videos of three-dimensional scenes.

Science.gov (United States)

Kwon, M-W; Kim, S-C; Yoon, S-E; Ho, Y-S; Kim, E-S

2015-02-09

A new object tracking mask-based novel-look-up-table (OTM-NLUT) method is proposed and implemented on graphics-processing-units (GPUs) for real-time generation of holographic videos of three-dimensional (3-D) scenes. Since the proposed method is designed to be matched with software and memory structures of the GPU, the number of compute-unified-device-architecture (CUDA) kernel function calls and the computer-generated hologram (CGH) buffer size of the proposed method have been significantly reduced. It therefore results in a great increase of the computational speed of the proposed method and enables real-time generation of CGH patterns of 3-D scenes. Experimental results show that the proposed method can generate 31.1 frames of Fresnel CGH patterns with 1,920 × 1,080 pixels per second, on average, for three test 3-D video scenarios with 12,666 object points on three GPU boards of NVIDIA GTX TITAN, and confirm the feasibility of the proposed method in the practical application of electro-holographic 3-D displays.

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

Science.gov (United States)

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.

Discriminative object tracking via sparse representation and online dictionary learning.

Science.gov (United States)

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

2014-04-01

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

Person detection, tracking and following using stereo camera

Science.gov (United States)

Wang, Xiaofeng; Zhang, Lilian; Wang, Duo; Hu, Xiaoping

2018-04-01

Person detection, tracking and following is a key enabling technology for mobile robots in many human-robot interaction applications. In this article, we present a system which is composed of visual human detection, video tracking and following. The detection is based on YOLO(You only look once), which applies a single convolution neural network(CNN) to the full image, thus can predict bounding boxes and class probabilities directly in one evaluation. Then the bounding box provides initial person position in image to initialize and train the KCF(Kernelized Correlation Filter), which is a video tracker based on discriminative classifier. At last, by using a stereo 3D sparse reconstruction algorithm, not only the position of the person in the scene is determined, but also it can elegantly solve the problem of scale ambiguity in the video tracker. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

The Habituation/Cross-Habituation Test Revisited: Guidance from Sniffing and Video Tracking

Directory of Open Access Journals (Sweden)

G. Coronas-Samano

2016-01-01

Full Text Available The habituation/cross-habituation test (HaXha is a spontaneous odor discrimination task that has been used for many decades to evaluate olfactory function in animals. Animals are presented repeatedly with the same odorant after which a new odorant is introduced. The time the animal explores the odor object is measured. An animal is considered to cross-habituate during the novel stimulus trial when the exploration time is higher than the prior trial and indicates the degree of olfactory patency. On the other hand, habituation across the repeated trials involves decreased exploration time and is related to memory patency, especially at long intervals. Classically exploration is timed using a stopwatch when the animal is within 2 cm of the object and aimed toward it. These criteria are intuitive, but it is unclear how they relate to olfactory exploration, that is, sniffing. We used video tracking combined with plethysmography to improve accuracy, avoid observer bias, and propose more robust criteria for exploratory scoring when sniff measures are not available. We also demonstrate that sniff rate combined with proximity is the most direct measure of odorant exploration and provide a robust and sensitive criterion.

Video Tracking Protocol to Screen Deterrent Chemistries for Honey Bees.

Science.gov (United States)

Larson, Nicholas R; Anderson, Troy D

2017-06-12

The European honey bee, Apis mellifera L., is an economically and agriculturally important pollinator that generates billions of dollars annually. Honey bee colony numbers have been declining in the United States and many European countries since 1947. A number of factors play a role in this decline, including the unintentional exposure of honey bees to pesticides. The development of new methods and regulations are warranted to reduce pesticide exposures to these pollinators. One approach is the use of repellent chemistries that deter honey bees from a recently pesticide-treated crop. Here, we describe a protocol to discern the deterrence of honey bees exposed to select repellent chemistries. Honey bee foragers are collected and starved overnight in an incubator 15 h prior to testing. Individual honey bees are placed into Petri dishes that have either a sugar-agarose cube (control treatment) or sugar-agarose-compound cube (repellent treatment) placed into the middle of the dish. The Petri dish serves as the arena that is placed under a camera in a light box to record the honey bee locomotor activities using video tracking software. A total of 8 control and 8 repellent treatments were analyzed for a 10 min period with each treatment was duplicated with new honey bees. Here, we demonstrate that honey bees are deterred from the sugar-agarose cubes with a compound treatment whereas honey bees are attracted to the sugar-agarose cubes without an added compound.

Augmenting real-time video with virtual models for enhanced visualization for simulation, teaching, training and guidance

Science.gov (United States)

Potter, Michael; Bensch, Alexander; Dawson-Elli, Alexander; Linte, Cristian A.

2015-03-01

In minimally invasive surgical interventions direct visualization of the target area is often not available. Instead, clinicians rely on images from various sources, along with surgical navigation systems for guidance. These spatial localization and tracking systems function much like the Global Positioning Systems (GPS) that we are all well familiar with. In this work we demonstrate how the video feed from a typical camera, which could mimic a laparoscopic or endoscopic camera used during an interventional procedure, can be used to identify the pose of the camera with respect to the viewed scene and augment the video feed with computer-generated information, such as rendering of internal anatomy not visible beyond the imaged surface, resulting in a simple augmented reality environment. This paper describes the software and hardware environment and methodology for augmenting the real world with virtual models extracted from medical images to provide enhanced visualization beyond the surface view achieved using traditional imaging. Following intrinsic and extrinsic camera calibration, the technique was implemented and demonstrated using a LEGO structure phantom, as well as a 3D-printed patient-specific left atrial phantom. We assessed the quality of the overlay according to fiducial localization, fiducial registration, and target registration errors, as well as the overlay offset error. Using the software extensions we developed in conjunction with common webcams it is possible to achieve tracking accuracy comparable to that seen with significantly more expensive hardware, leading to target registration errors on the order of 2 mm.

The live service of video geo-information

Science.gov (United States)

Xue, Wu; Zhang, Yongsheng; Yu, Ying; Zhao, Ling

2016-03-01

In disaster rescue, emergency response and other occasions, traditional aerial photogrammetry is difficult to meet real-time monitoring and dynamic tracking demands. To achieve the live service of video geo-information, a system is designed and realized—an unmanned helicopter equipped with video sensor, POS, and high-band radio. This paper briefly introduced the concept and design of the system. The workflow of video geo-information live service is listed. Related experiments and some products are shown. In the end, the conclusion and outlook is given.

Simultaneous recordings of human microsaccades and drifts with a contemporary video eye tracker and the search coil technique.

Directory of Open Access Journals (Sweden)

Michael B McCamy

Full Text Available Human eyes move continuously, even during visual fixation. These "fixational eye movements" (FEMs include microsaccades, intersaccadic drift and oculomotor tremor. Research in human FEMs has grown considerably in the last decade, facilitated by the manufacture of noninvasive, high-resolution/speed video-oculography eye trackers. Due to the small magnitude of FEMs, obtaining reliable data can be challenging, however, and depends critically on the sensitivity and precision of the eye tracking system. Yet, no study has conducted an in-depth comparison of human FEM recordings obtained with the search coil (considered the gold standard for measuring microsaccades and drift and with contemporary, state-of-the art video trackers. Here we measured human microsaccades and drift simultaneously with the search coil and a popular state-of-the-art video tracker. We found that 95% of microsaccades detected with the search coil were also detected with the video tracker, and 95% of microsaccades detected with video tracking were also detected with the search coil, indicating substantial agreement between the two systems. Peak/mean velocities and main sequence slopes of microsaccades detected with video tracking were significantly higher than those of the same microsaccades detected with the search coil, however. Ocular drift was significantly correlated between the two systems, but drift speeds were higher with video tracking than with the search coil. Overall, our combined results suggest that contemporary video tracking now approaches the search coil for measuring FEMs.

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

Science.gov (United States)

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

2017-10-01

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

Video Golf

Science.gov (United States)

1995-01-01

George Nauck of ENCORE!!! invented and markets the Advanced Range Performance (ARPM) Video Golf System for measuring the result of a golf swing. After Nauck requested their assistance, Marshall Space Flight Center scientists suggested video and image processing/computing technology, and provided leads on commercial companies that dealt with the pertinent technologies. Nauck contracted with Applied Research Inc. to develop a prototype. The system employs an elevated camera, which sits behind the tee and follows the flight of the ball down range, catching the point of impact and subsequent roll. Instant replay of the video on a PC monitor at the tee allows measurement of the carry and roll. The unit measures distance and deviation from the target line, as well as distance from the target when one is selected. The information serves as an immediate basis for making adjustments or as a record of skill level progress for golfers.

Can fractal methods applied to video tracking detect the effects of deltamethrin pesticide or mercury on the locomotion behavior of shrimps?

Science.gov (United States)

Tenorio, Bruno Mendes; da Silva Filho, Eurípedes Alves; Neiva, Gentileza Santos Martins; da Silva, Valdemiro Amaro; Tenorio, Fernanda das Chagas Angelo Mendes; da Silva, Themis de Jesus; Silva, Emerson Carlos Soares E; Nogueira, Romildo de Albuquerque

2017-08-01

Shrimps can accumulate environmental toxicants and suffer behavioral changes. However, methods to quantitatively detect changes in the behavior of these shrimps are still needed. The present study aims to verify whether mathematical and fractal methods applied to video tracking can adequately describe changes in the locomotion behavior of shrimps exposed to low concentrations of toxic chemicals, such as 0.15µgL -1 deltamethrin pesticide or 10µgL -1 mercuric chloride. Results showed no change after 1min, 4, 24, and 48h of treatment. However, after 72 and 96h of treatment, both the linear methods describing the track length, mean speed, mean distance from the current to the previous track point, as well as the non-linear methods of fractal dimension (box counting or information entropy) and multifractal analysis were able to detect changes in the locomotion behavior of shrimps exposed to deltamethrin. Analysis of angular parameters of the track points vectors and lacunarity were not sensitive to those changes. None of the methods showed adverse effects to mercury exposure. These mathematical and fractal methods applicable to software represent low cost useful tools in the toxicological analyses of shrimps for quality of food, water and biomonitoring of ecosystems. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

Tescher, Andrew G. (Editor)

1989-01-01

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

Tracking of Range and Azimuth for Continuous Imaging of Marine Target in Monopulse ISAR with Wideband Echoes

Directory of Open Access Journals (Sweden)

Junhao Xie

2016-01-01

Full Text Available Real-time tracking of maneuvering targets is the prerequisite for continuous imaging of moving targets in inverse synthetic aperture radar (ISAR. In this paper, the range and azimuth tracking (RAT method with wideband radar echoes is first presented for a mechanical scanning monopulse ISAR, which is regarded as the simplest phased array unit due to the two antenna feeds. To relieve the estimation fluctuation and poor robustness of the RAT method with a single snapshot, a modified range and azimuth tracking approach based on centroid algorithm (RATCA with forgotten factor and multiple echoes is then proposed. The performances of different forgotten factors are investigated. Both theoretical analysis and experimental results demonstrate that RATCA is superior to RAT method. Particularly, when target echo is missing occasionally, RAT method fails while RATCA still keeps good performance. The potential of continuous imaging with shipborne ISAR is verified by experimental results. With minor modification, the method proposed in this paper can be potentially applied in the phased array radar.

Visual Attention Modeling for Stereoscopic Video: A Benchmark and Computational Model.

Science.gov (United States)

Fang, Yuming; Zhang, Chi; Li, Jing; Lei, Jianjun; Perreira Da Silva, Matthieu; Le Callet, Patrick

2017-10-01

In this paper, we investigate the visual attention modeling for stereoscopic video from the following two aspects. First, we build one large-scale eye tracking database as the benchmark of visual attention modeling for stereoscopic video. The database includes 47 video sequences and their corresponding eye fixation data. Second, we propose a novel computational model of visual attention for stereoscopic video based on Gestalt theory. In the proposed model, we extract the low-level features, including luminance, color, texture, and depth, from discrete cosine transform coefficients, which are used to calculate feature contrast for the spatial saliency computation. The temporal saliency is calculated by the motion contrast from the planar and depth motion features in the stereoscopic video sequences. The final saliency is estimated by fusing the spatial and temporal saliency with uncertainty weighting, which is estimated by the laws of proximity, continuity, and common fate in Gestalt theory. Experimental results show that the proposed method outperforms the state-of-the-art stereoscopic video saliency detection models on our built large-scale eye tracking database and one other database (DML-ITRACK-3D).

Combined kV and MV imaging for real-time tracking of implanted fiducial markers

International Nuclear Information System (INIS)

Wiersma, R. D.; Mao Weihua; Xing, L.

2008-01-01

In the presence of intrafraction organ motion, target localization uncertainty can greatly hamper the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT). To minimize the adverse dosimetric effect caused by tumor motion, a real-time knowledge of the tumor position is required throughout the beam delivery process. The recent integration of onboard kV diagnostic imaging together with MV electronic portal imaging devices on linear accelerators can allow for real-time three-dimensional (3D) tumor position monitoring during a treatment delivery. The aim of this study is to demonstrate a near real-time 3D internal fiducial tracking system based on the combined use of kV and MV imaging. A commercially available radiotherapy system equipped with both kV and MV imaging systems was used in this work. A hardware video frame grabber was used to capture both kV and MV video streams simultaneously through independent video channels at 30 frames per second. The fiducial locations were extracted from the kV and MV images using a software tool. The geometric tracking capabilities of the system were evaluated using a pelvic phantom with embedded fiducials placed on a moveable stage. The maximum tracking speed of the kV/MV system is approximately 9 Hz, which is primarily limited by the frame rate of the MV imager. The geometric accuracy of the system is found to be on the order of less than 1 mm in all three spatial dimensions. The technique requires minimal hardware modification and is potentially useful for image-guided radiation therapy systems

Testing Video and Social Media for Engaging Users of the U.S. Climate Resilience Toolkit

Science.gov (United States)

Green, C. J.; Gardiner, N.; Niepold, F., III; Esposito, C.

2015-12-01

We developed a custom video production stye and a method for analyzing social media behavior so that we may deliberately build and track audience growth for decision-support tools and case studies within the U.S. Climate Resilience Toolkit. The new style of video focuses quickly on decision processes; its 30s format is well-suited for deployment through social media. We measured both traffic and engagement with video using Google Analytics. Each video included an embedded tag, allowing us to measure viewers' behavior: whether or not they entered the toolkit website; the duration of their session on the website; and the number pages they visited in that session. Results showed that video promotion was more effective on Facebook than Twitter. Facebook links generated twice the number of visits to the toolkit. Videos also increased Facebook interaction overall. Because most Facebook users are return visitors, this campaign did not substantially draw new site visitors. We continue to research and apply these methods in a targeted engagement and outreach campaign that utilizes the theory of social diffusion and social influence strategies to grow our audience of "influential" decision-makers and people within their social networks. Our goal is to increase access and use of the U.S. Climate Resilience Toolkit.

Intra-system reliability of SICS: video-tracking system (Digital.Stadium®) for performance analysis in football.

Science.gov (United States)

Beato, Marco; Jamil, Mikael

2017-05-09

The correct evaluation of external load parameters is a key factor in professional football. The instrumentations usually utilised to quantify the external load parameters during official matches are Video-Tracking Systems (VTS). VTS is a technology that records two- dimensional position data (x and y) at high sampling rates (over 25 Hz). The aim of this study was to evaluate the intra-system reliability of Digital.Stadium® VTS. 28 professional male football players taking part in the Italian Serie A (age 24 ± 6 years, body mass 79.5 ± 7.8 kg, stature 1.83 ± 0.05 m) during the 2015/16 season were enrolled in this study (Team A and Team B). Video-analysis was done during an official match and data analysis was performed immediately after the game ended and then replicated a week later. This study reported a near perfect relationship between the initial analysis (analysis 1) and the replicated analysis undertaken a week later (analysis 2). R2 coefficients were highly significant for each of the performance parameters, p power of 9.65 ± 1.64 w kg-1 and 9.58 ± 1.61 w kg-1, in analysis 1 and analysis 2, respectively. The findings reported in this study underlined that all data reported by Digital.Stadium® VTS showed high levels of absolute and relative reliability.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Sustainable Transportation Attitudes and Health Behavior Change: Evaluation of a Brief Stage-Targeted Video Intervention

Directory of Open Access Journals (Sweden)

Norbert Mundorf

2018-01-01

Full Text Available Promoting physical activity and sustainable transportation is essential in the face of rising health care costs, obesity rates, and other public health threats resulting from lack of physical activity. Targeted communications can encourage distinct population segments to adopt active and sustainable transportation modes. Our work is designed to promote the health, social, and environmental benefits of sustainable/active transportation (ST using the Transtheoretical Model of Change (TTM, which has been successfully applied to a range of health, and more recently, sustainability behaviors. Earlier, measurement development confirmed both the structure of ST pros and cons and efficacy measures as well as the relationship between these constructs and ST stages of change, replicating results found for many other behaviors. The present paper discusses a brief pre-post video pilot intervention study designed for precontemplators and contemplators (N = 604 that was well received, effective in moving respondents towards increased readiness for ST behavior change, and improving some ST attitudes, significantly reducing the cons of ST. This research program shows that a brief stage-targeted behavior change video can increase readiness and reduce the cons for healthy transportation choices.

Sustainable Transportation Attitudes and Health Behavior Change: Evaluation of a Brief Stage-Targeted Video Intervention.

Science.gov (United States)

Mundorf, Norbert; Redding, Colleen A; Paiva, Andrea L

2018-01-18

Promoting physical activity and sustainable transportation is essential in the face of rising health care costs, obesity rates, and other public health threats resulting from lack of physical activity. Targeted communications can encourage distinct population segments to adopt active and sustainable transportation modes. Our work is designed to promote the health, social, and environmental benefits of sustainable/active transportation (ST) using the Transtheoretical Model of Change (TTM), which has been successfully applied to a range of health, and more recently, sustainability behaviors. Earlier, measurement development confirmed both the structure of ST pros and cons and efficacy measures as well as the relationship between these constructs and ST stages of change, replicating results found for many other behaviors. The present paper discusses a brief pre-post video pilot intervention study designed for precontemplators and contemplators (N = 604) that was well received, effective in moving respondents towards increased readiness for ST behavior change, and improving some ST attitudes, significantly reducing the cons of ST. This research program shows that a brief stage-targeted behavior change video can increase readiness and reduce the cons for healthy transportation choices.

Sustainable Transportation Attitudes and Health Behavior Change: Evaluation of a Brief Stage-Targeted Video Intervention

Science.gov (United States)

Mundorf, Norbert; Redding, Colleen A.; Paiva, Andrea L.

2018-01-01

Promoting physical activity and sustainable transportation is essential in the face of rising health care costs, obesity rates, and other public health threats resulting from lack of physical activity. Targeted communications can encourage distinct population segments to adopt active and sustainable transportation modes. Our work is designed to promote the health, social, and environmental benefits of sustainable/active transportation (ST) using the Transtheoretical Model of Change (TTM), which has been successfully applied to a range of health, and more recently, sustainability behaviors. Earlier, measurement development confirmed both the structure of ST pros and cons and efficacy measures as well as the relationship between these constructs and ST stages of change, replicating results found for many other behaviors. The present paper discusses a brief pre-post video pilot intervention study designed for precontemplators and contemplators (N = 604) that was well received, effective in moving respondents towards increased readiness for ST behavior change, and improving some ST attitudes, significantly reducing the cons of ST. This research program shows that a brief stage-targeted behavior change video can increase readiness and reduce the cons for healthy transportation choices. PMID:29346314

Data association approaches in bearings-only multi-target tracking

Science.gov (United States)

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.

Video Surveillance of Epilepsy Patients using Color Image Processing

DEFF Research Database (Denmark)

Bager, Gitte; Vilic, Kenan; Alving, Jørgen

2007-01-01

This report introduces a method for tracking of patients under video surveillance based on a marker system. The patients are not restricted in their movements, which requires a tracking system that can overcome non-ideal scenes e.g. occlusions, very fast movements, lightning issues and other movi...

Video surveillance of epilepsy patients using color image processing

DEFF Research Database (Denmark)

Bager, Gitte; Vilic, Kenan; Vilic, Adnan

2014-01-01

This paper introduces a method for tracking patients under video surveillance based on a color marker system. The patients are not restricted in their movements, which requires a tracking system that can overcome non-ideal scenes e.g. occlusions, very fast movements, lighting issues and other mov...

Playing violent video games increases intergroup bias.

Science.gov (United States)

Greitemeyer, Tobias

2014-01-01

Previous research has shown how, why, and for whom violent video game play is related to aggression and aggression-related variables. In contrast, less is known about whether some individuals are more likely than others to be the target of increased aggression after violent video game play. The present research examined the idea that the effects of violent video game play are stronger when the target is a member of an outgroup rather than an ingroup. In fact, a correlational study revealed that violent video game exposure was positively related to ethnocentrism. This relation remained significant when controlling for trait aggression. Providing causal evidence, an experimental study showed that playing a violent video game increased aggressive behavior, and that this effect was more pronounced when the target was an outgroup rather than an ingroup member. Possible mediating mechanisms are discussed.

Methods and Algorithms for Detecting Objects in Video Files

Directory of Open Access Journals (Sweden)

Nguyen The Cuong

2018-01-01

Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

Multiple-camera tracking: UK government requirements

Science.gov (United States)

Hosmer, Paul

2007-10-01

The Imagery Library for Intelligent Detection Systems (i-LIDS) is the UK government's new standard for Video Based Detection Systems (VBDS). The standard was launched in November 2006 and evaluations against it began in July 2007. With the first four i-LIDS scenarios completed, the Home Office Scientific development Branch (HOSDB) are looking toward the future of intelligent vision in the security surveillance market by adding a fifth scenario to the standard. The fifth i-LIDS scenario will concentrate on the development, testing and evaluation of systems for the tracking of people across multiple cameras. HOSDB and the Centre for the Protection of National Infrastructure (CPNI) identified a requirement to track targets across a network of CCTV cameras using both live and post event imagery. The Detection and Vision Systems group at HOSDB were asked to determine the current state of the market and develop an in-depth Operational Requirement (OR) based on government end user requirements. Using this OR the i-LIDS team will develop a full i-LIDS scenario to aid the machine vision community in its development of multi-camera tracking systems. By defining a requirement for multi-camera tracking and building this into the i-LIDS standard the UK government will provide a widely available tool that developers can use to help them turn theory and conceptual demonstrators into front line application. This paper will briefly describe the i-LIDS project and then detail the work conducted in building the new tracking aspect of the standard.

Video game use and cognitive performance: does it vary with the presence of problematic video game use?

Science.gov (United States)

Collins, Emily; Freeman, Jonathan

2014-03-01

Action video game players have been found to outperform nonplayers on a variety of cognitive tasks. However, several failures to replicate these video game player advantages have indicated that this relationship may not be straightforward. Moreover, despite the discovery that problematic video game players do not appear to demonstrate the same superior performance as nonproblematic video game players in relation to multiple object tracking paradigms, this has not been investigated for other tasks. Consequently, this study compared gamers and nongamers in task switching ability, visual short-term memory, mental rotation, enumeration, and flanker interference, as well as investigated the influence of self-reported problematic video game use. A total of 66 participants completed the experiment, 26 of whom played action video games, including 20 problematic players. The results revealed no significant effect of playing action video games, nor any influence of problematic video game play. This indicates that the previously reported cognitive advantages in video game players may be restricted to specific task features or samples. Furthermore, problematic video game play may not have a detrimental effect on cognitive performance, although this is difficult to ascertain considering the lack of video game player advantage. More research is therefore sorely needed.

Occlusion detection via structured sparse learning for robust object tracking

KAUST Repository

Zhang, Tianzhu

2014-01-01

Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.

Online multi-modal robust non-negative dictionary learning for visual tracking.

Science.gov (United States)

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Robust object tracking combining color and scale invariant features

Science.gov (United States)

Zhang, Shengping; Yao, Hongxun; Gao, Peipei

2010-07-01

Object tracking plays a very important role in many computer vision applications. However its performance will significantly deteriorate due to some challenges in complex scene, such as pose and illumination changes, clustering background and so on. In this paper, we propose a robust object tracking algorithm which exploits both global color and local scale invariant (SIFT) features in a particle filter framework. Due to the expensive computation cost of SIFT features, the proposed tracker adopts a speed-up variation of SIFT, SURF, to extract local features. Specially, the proposed method first finds matching points between the target model and target candidate, than the weight of the corresponding particle based on scale invariant features is computed as the the proportion of matching points of that particle to matching points of all particles, finally the weight of the particle is obtained by combining weights of color and SURF features with a probabilistic way. The experimental results on a variety of challenging videos verify that the proposed method is robust to pose and illumination changes and is significantly superior to the standard particle filter tracker and the mean shift tracker.

OLIVE: Speech-Based Video Retrieval

NARCIS (Netherlands)

de Jong, Franciska M.G.; Gauvain, Jean-Luc; den Hartog, Jurgen; den Hartog, Jeremy; Netter, Klaus

1999-01-01

This paper describes the Olive project which aims to support automated indexing of video material by use of human language technologies. Olive is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which serve as the

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

Science.gov (United States)

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

2017-07-26

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

Theory and practice of perceptual video processing in broadcast encoders for cable, IPTV, satellite, and internet distribution

Science.gov (United States)

McCarthy, S.

2014-02-01

This paper describes the theory and application of a perceptually-inspired video processing technology that was recently incorporated into professional video encoders now being used by major cable, IPTV, satellite, and internet video service providers. We will present data that show that this perceptual video processing (PVP) technology can improve video compression efficiency by up to 50% for MPEG-2, H.264, and High Efficiency Video Coding (HEVC). The PVP technology described in this paper works by forming predicted eye-tracking attractor maps that indicate how likely it might be that a free viewing person would look at particular area of an image or video. We will introduce in this paper the novel model and supporting theory used to calculate the eye-tracking attractor maps. We will show how the underlying perceptual model was inspired by electrophysiological studies of the vertebrate retina, and will explain how the model incorporates statistical expectations about natural scenes as well as a novel method for predicting error in signal estimation tasks. Finally, we will describe how the eye-tracking attractor maps are created in real time and used to modify video prior to encoding so that it is more compressible but not noticeably different than the original unmodified video.

MPEG-2 Compressed-Domain Algorithms for Video Analysis

Directory of Open Access Journals (Sweden)

Hesseler Wolfgang

2006-01-01

Full Text Available This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yielding an efficient algorithm to track objects inside video sequences. The third algorithm performs a cut detection using macroblock types and motion vectors.

Extending Track Analysis from Animals in the Lab to Moving Objects Anywhere

NARCIS (Netherlands)

Dommelen, W. van; Laar, P.J.L.J. van de; Noldus, L.P.J.J.

2013-01-01

In this chapter we compare two application domains in which the tracking of objects and the analysis of their movements are core activities, viz. animal tracking and vessel tracking. More specifically, we investigate whether EthoVision XT, a research tool for video tracking and analysis of the

Memory-cenric video processing

NARCIS (Netherlands)

Beric, A.; Meerbergen, van J.; Haan, de G.; Sethuraman, R.

2008-01-01

This work presents a domain-specific memory subsystem based on a two-level memory hierarchy. It targets the application domain of video post-processing applications including video enhancement and format conversion. These applications are based on motion compensation and/or broad class of content

Commercial vehicle route tracking using video detection.

Science.gov (United States)

2010-10-31

Interstate commercial vehicle traffic is a major factor in the life of any road surface. The ability to track : these vehicles and their routes through the state can provide valuable information to planning : activities. We propose a method using vid...

Search and Tracking of an Unknown Number of Targets by a Team of Autonomous Agents Utilizing Time-evolving Partition Classification

OpenAIRE

Wood, Jared Gregory

2011-01-01

The advancement of computing technology has enabled the practical development of intelligent autonomous systems. Intelligent autonomous systems can be used to perform difficult sensing tasks. One such sensing task is to search for and track targets over large geographic areas. Searching for and tracking targets over geographic areas has important applications. These applications include search and rescue, boarder patrol, and reconnaissance. Inherent in applications such as these is the need ...

Automated interactive video playback for studies of animal communication.

Science.gov (United States)

Butkowski, Trisha; Yan, Wei; Gray, Aaron M; Cui, Rongfeng; Verzijden, Machteld N; Rosenthal, Gil G

2011-02-09

Video playback is a widely-used technique for the controlled manipulation and presentation of visual signals in animal communication. In particular, parameter-based computer animation offers the opportunity to independently manipulate any number of behavioral, morphological, or spectral characteristics in the context of realistic, moving images of animals on screen. A major limitation of conventional playback, however, is that the visual stimulus lacks the ability to interact with the live animal. Borrowing from video-game technology, we have created an automated, interactive system for video playback that controls animations in response to real-time signals from a video tracking system. We demonstrated this method by conducting mate-choice trials on female swordtail fish, Xiphophorus birchmanni. Females were given a simultaneous choice between a courting male conspecific and a courting male heterospecific (X. malinche) on opposite sides of an aquarium. The virtual male stimulus was programmed to track the horizontal position of the female, as courting males do in the wild. Mate-choice trials on wild-caught X. birchmanni females were used to validate the prototype's ability to effectively generate a realistic visual stimulus.

Manual versus Automated Rodent Behavioral Assessment: Comparing Efficacy and Ease of Bederson and Garcia Neurological Deficit Scores to an Open Field Video-Tracking System

OpenAIRE

Fiona A. Desland; Aqeela Afzal; Zuha Warraich; J Mocco

2014-01-01

Animal models of stroke have been crucial in advancing our understanding of the pathophysiology of cerebral ischemia. Currently, the standards for determining neurological deficit in rodents are the Bederson and Garcia scales, manual assessments scoring animals based on parameters ranked on a narrow scale of severity. Automated open field analysis of a live-video tracking system that analyzes animal behavior may provide a more sensitive test. Results obtained from the manual Bederson and Garc...

Object tracking by occlusion detection via structured sparse learning

KAUST Repository

Zhang, Tianzhu

2013-06-01

Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.

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

Energy Technology Data Exchange (ETDEWEB)

Berbeco, R. [Brigham and Women’s Hospital and Dana-Farber Cancer Institute (United States)

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 techniques 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.

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

Energy Technology Data Exchange (ETDEWEB)

Low, D. [University of California Los Angeles: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking (United States)

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 techniques 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.

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

Energy Technology Data Exchange (ETDEWEB)

Keall, P. [University of Sydney (Australia)

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 techniques 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.

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

International Nuclear Information System (INIS)

Low, D.

2015-01-01

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 techniques 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

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

International Nuclear Information System (INIS)

Keall, P.

2015-01-01

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 techniques 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

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

International Nuclear Information System (INIS)

Berbeco, R.

2015-01-01

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 techniques 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

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Light-reflection random-target method for measurement of the modulation transfer function of a digital video-camera

Science.gov (United States)

Pospisil, J.; Jakubik, P.; Machala, L.

2005-11-01

This article reports the suggestion, realization and verification of the newly developed measuring means of the noiseless and locally shift-invariant modulation transfer function (MTF) of a digital video camera in a usual incoherent visible region of optical intensity, especially of its combined imaging, detection, sampling and digitizing steps which are influenced by the additive and spatially discrete photodetector, aliasing and quantization noises. Such means relates to the still camera automatic working regime and static two-dimensional spatially continuous light-reflection random target of white-noise property. The introduced theoretical reason for such a random-target method is also performed under exploitation of the proposed simulation model of the linear optical intensity response and possibility to express the resultant MTF by a normalized and smoothed rate of the ascertainable output and input power spectral densities. The random-target and resultant image-data were obtained and processed by means of a processing and evaluational PC with computation programs developed on the basis of MATLAB 6.5E The present examples of results and other obtained results of the performed measurements demonstrate the sufficient repeatability and acceptability of the described method for comparative evaluations of the performance of digital video cameras under various conditions.

Light Video Game Play is Associated with Enhanced Visual Processing of Rapid Serial Visual Presentation Targets.

Science.gov (United States)

Howard, Christina J; Wilding, Robert; Guest, Duncan

2017-02-01

There is mixed evidence that video game players (VGPs) may demonstrate better performance in perceptual and attentional tasks than non-VGPs (NVGPs). The rapid serial visual presentation task is one such case, where observers respond to two successive targets embedded within a stream of serially presented items. We tested light VGPs (LVGPs) and NVGPs on this task. LVGPs were better at correct identification of second targets whether they were also attempting to respond to the first target. This performance benefit seen for LVGPs suggests enhanced visual processing for briefly presented stimuli even with only very moderate game play. Observers were less accurate at discriminating the orientation of a second target within the stream if it occurred shortly after presentation of the first target, that is to say, they were subject to the attentional blink (AB). We find no evidence for any reduction in AB in LVGPs compared with NVGPs.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

International Nuclear Information System (INIS)

Chebrolu, V.V.; Chebrolu, V.V.; Saenz, D.; Tewatia, D.; Paliwal, B.R.; Chebrolu, V.V.; Saenz, D.; Paliwal, B.R.; Sethares, W.A.; Cannon, G.

2014-01-01

To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving auto segmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix © and MIMV ista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ±11.1 seconds per phase ( 512 ×512 resolution) as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

Directory of Open Access Journals (Sweden)

Venkata V. Chebrolu

2014-01-01

Full Text Available Purpose. To achieve rapid automated delineation of gross target volume (GTV and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D CT. Methods and Materials. Novel morphological processing and successive localization (MPSL algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software. Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0±11.1 seconds per phase (512×512 resolution as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth were 0.865±0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours.

Science.gov (United States)

Chebrolu, Venkata V; Saenz, Daniel; Tewatia, Dinesh; Sethares, William A; Cannon, George; Paliwal, Bhudatt R

2014-01-01

Purpose. To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ± 11.1 seconds per phase (512 × 512 resolution) as compared to 142.3 ± 11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

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

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jai-Woong; Sawant, Amit; Suh, Yelin; Cho, Byung-Chul; Suh, Tae-Suk; Keall, Paul [Department of Biomedical Engineering, College of Medicine, Catholic University of Korea, Seoul, Korea 131-700 and Research Institute of Biomedical Engineering, Catholic University of Korea, Seoul, 131-700 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States) and Department of Radiation Oncology, Asan Medical Center, Seoul, 138-736 (Korea, Republic of); Department of Biomedical Engineering, College of Medicine, Catholic University of Korea, Seoul, 131-700 and Research Institute of Biomedical Engineering, Catholic University of Korea, Seoul, 131-700 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States) and Radiation Physics Laboratory, Sydney Medical School, University of Sydney, 2006 (Australia)

2011-07-15

Purpose: 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. Methods: 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 {gamma}-test with a 3%/3 mm criterion. Results: 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