WorldWideScience

Sample records for video object tracking

  1. 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.

  2. 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),

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Lerouge Sam

    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 .

  12. 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%.

  13. 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.

  14. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Science.gov (United States)

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

    2014-01-01

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

  15. 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.

  16. 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.

  17. Statistical motion vector analysis for object tracking in compressed video streams

    Science.gov (United States)

    Leny, Marc; Prêteux, Françoise; Nicholson, Didier

    2008-02-01

    Compressed video is the digital raw material provided by video-surveillance systems and used for archiving and indexing purposes. Multimedia standards have therefore a direct impact on such systems. If MPEG-2 used to be the coding standard, MPEG-4 (part 2) has now replaced it in most installations, and MPEG-4 AVC/H.264 solutions are now being released. Finely analysing the complex and rich MPEG-4 streams is a challenging issue addressed in that paper. The system we designed is based on five modules: low-resolution decoder, motion estimation generator, object motion filtering, low-resolution object segmentation, and cooperative decision. Our contributions refer to as the statistical analysis of the spatial distribution of the motion vectors, the computation of DCT-based confidence maps, the automatic motion activity detection in the compressed file and a rough indexation by dedicated descriptors. The robustness and accuracy of the system are evaluated on a large corpus (hundreds of hours of in-and outdoor videos with pedestrians and vehicles). The objective benchmarking of the performances is achieved with respect to five metrics allowing to estimate the error part due to each module and for different implementations. This evaluation establishes that our system analyses up to 200 frames (720x288) per second (2.66 GHz CPU).

  18. 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.

  19. 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%).

  20. Gamifying Video Object Segmentation.

    Science.gov (United States)

    Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

    2017-10-01

    Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

  1. Enumeration versus Multiple Object Tracking: The Case of Action Video Game Players

    Science.gov (United States)

    Green, C. S.; Bavelier, D.

    2006-01-01

    Here, we demonstrate that action video game play enhances subjects' ability in two tasks thought to indicate the number of items that can be apprehended. Using an enumeration task, in which participants have to determine the number of quickly flashed squares, accuracy measures showed a near ceiling performance for low numerosities and a sharp drop…

  2. 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.

  3. 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

  4. 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.

  5. Robust video object cosegmentation.

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih

    2015-10-01

    With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

  6. GPS-Aided Video Tracking

    Directory of Open Access Journals (Sweden)

    Udo Feuerhake

    2015-08-01

    Full Text Available Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS- and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

  7. 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.

  8. 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.

  9. 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.

  10. Optimization of object tracking based on enhanced imperialist ...

    African Journals Online (AJOL)

    . Tracking moving object(s) in video/image frame sequences in cluttered scenes usually results in complications and hence performance degradation. This is attributable to complexity in partial and full object occlusions and scene illumination ...

  11. Tracking in Object Action Space

    DEFF Research Database (Denmark)

    Krüger, Volker; Herzog, Dennis

    2013-01-01

    the space of the object affordances, i.e., the space of possible actions that are applied on a given object. This way, 3D body tracking reduces to action tracking in the object (and context) primed parameter space of the object affordances. This reduces the high-dimensional joint-space to a low...

  12. Visual object recognition and tracking

    Science.gov (United States)

    Chang, Chu-Yin (Inventor); English, James D. (Inventor); Tardella, Neil M. (Inventor)

    2010-01-01

    This invention describes a method for identifying and tracking an object from two-dimensional data pictorially representing said object by an object-tracking system through processing said two-dimensional data using at least one tracker-identifier belonging to the object-tracking system for providing an output signal containing: a) a type of the object, and/or b) a position or an orientation of the object in three-dimensions, and/or c) an articulation or a shape change of said object in said three dimensions.

  13. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

    Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

  14. 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.

  15. Robust feedback zoom tracking for digital video surveillance.

    Science.gov (United States)

    Zou, Tengyue; Tang, Xiaoqi; Song, Bao; Wang, Jin; Chen, Jihong

    2012-01-01

    Zoom tracking is an important function in video surveillance, particularly in traffic management and security monitoring. It involves keeping an object of interest in focus during the zoom operation. Zoom tracking is typically achieved by moving the zoom and focus motors in lenses following the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. The main task of a zoom tracking approach is to accurately estimate the trace curve for the specified object. Because a proportional integral derivative (PID) controller has historically been considered to be the best controller in the absence of knowledge of the underlying process and its high-quality performance in motor control, in this paper, we propose a novel feedback zoom tracking (FZT) approach based on the geometric trace curve estimation and PID feedback controller. The performance of this approach is compared with existing zoom tracking methods in digital video surveillance. The real-time implementation results obtained on an actual digital video platform indicate that the developed FZT approach not only solves the traditional one-to-many mapping problem without pre-training but also improves the robustness for tracking moving or switching objects which is the key challenge in video surveillance.

  16. Technology survey on video face tracking

    Science.gov (United States)

    Zhang, Tong; Gomes, Herman Martins

    2014-03-01

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

  17. Fast-track video-assisted thoracoscopic surgery

    DEFF Research Database (Denmark)

    Holbek, Bo Laksafoss; Petersen, René Horsleben; Kehlet, Henrik

    2016-01-01

    Objectives To provide a short overview of fast-track video-assisted thoracoscopic surgery (VATS) and to identify areas requiring further research. Design A literature search was made using key words including: fast-track, enhanced recovery, video-assisted thoracoscopic surgery, robot......-assisted thoracoscopic surgery (RATS), robotic, thoracotomy, single-incision, uniportal, natural orifice transluminal endoscopic surgery (NOTES), chest tube, air-leak, digital drainage, pain management, analgesia, perioperative management, anaesthesia and non-intubated. References from articles were screened for further...

  18. Visualization of ground truth tracks for the video 'Tracking a "facer's" behavior in a public plaza'

    DEFF Research Database (Denmark)

    2015-01-01

    The video shows the ground truth tracks in GIS of all pedestrians in the video 'Tracking a 'facer's" behavior in a public plaza'. The visualization was made using QGIS TimeManager.......The video shows the ground truth tracks in GIS of all pedestrians in the video 'Tracking a 'facer's" behavior in a public plaza'. The visualization was made using QGIS TimeManager....

  19. 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.

  20. 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.

  1. 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.

  2. 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).

  3. Manifold Regularized Correlation Object Tracking.

    Science.gov (United States)

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2018-05-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

  4. 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.

  5. 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

  6. Automatic video segmentation employing object/camera modeling techniques

    NARCIS (Netherlands)

    Farin, D.S.

    2005-01-01

    Practically established video compression and storage techniques still process video sequences as rectangular images without further semantic structure. However, humans watching a video sequence immediately recognize acting objects as semantic units. This semantic object separation is currently not

  7. Coding Transparency in Object-Based Video

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2006-01-01

    A novel algorithm for coding gray level alpha planes in object-based video is presented. The scheme is based on segmentation in multiple layers. Different coders are specifically designed for each layer. In order to reduce the bit rate, cross-layer redundancies as well as temporal correlation are...

  8. Multiple objects tracking in fluorescence microscopy.

    Science.gov (United States)

    Kalaidzidis, Yannis

    2009-01-01

    Many processes in cell biology are connected to the movement of compact entities: intracellular vesicles and even single molecules. The tracking of individual objects is important for understanding cellular dynamics. Here we describe the tracking algorithms which have been developed in the non-biological fields and successfully applied to object detection and tracking in biological applications. The characteristics features of the different algorithms are compared.

  9. Manifold Regularized Correlation Object Tracking

    OpenAIRE

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2017-01-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

  10. Object tracking using active appearance models

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2001-01-01

    This paper demonstrates that (near) real-time object tracking can be accomplished by the deformable template model; the Active Appearance Model (AAM) using only low-cost consumer electronics such as a PC and a web-camera. Successful object tracking of perspective, rotational and translational...

  11. Compressed multi-block local binary pattern for object tracking

    Science.gov (United States)

    Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

    2018-04-01

    Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

  12. Object detection and tracking system

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Tian J.

    2017-05-30

    Methods and apparatuses for analyzing a sequence of images for an object are disclosed herein. In a general embodiment, the method identifies a region of interest in the sequence of images. The object is likely to move within the region of interest. The method divides the region of interest in the sequence of images into sections and calculates signal-to-noise ratios for a section in the sections. A signal-to-noise ratio for the section is calculated using the section in the image, a prior section in a prior image to the image, and a subsequent section in a subsequent image to the image. The signal-to-noise ratios are for potential velocities of the object in the section. The method also selects a velocity from the potential velocities for the object in the section using a potential velocity in the potential velocities having a highest signal-to-noise ratio in the signal-to-noise ratios.

  13. Robust Object Tracking Using Valid Fragments Selection.

    Science.gov (United States)

    Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

  14. Objective assessment of IP video calls with Asterisk

    OpenAIRE

    Kapičák, Lukáš; Nevlud, Pavel; Mikulec, Martin; Zdrálek, Jaroslav

    2012-01-01

    The paper deals with an objective assessment of IP video calls transmission over GSM and UMTS networks. Video transmission is affected by many factors in mobile network. Among these factors belong packet loss, latency and transmission rate of the mobile network. Network properties were simulated by Simena network simulator. Our team have developed a unique technique for finding defects in video appearing in video calls. This technique is built on modified Asterisk SW PBX with enabled video re...

  15. Segmentation of object-based video of gaze communication

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Stegmann, Mikkel Bille; Forchhammer, Søren

    2005-01-01

    Aspects of video communication based on gaze interaction are considered. The overall idea is to use gaze interaction to control video, e.g. for video conferencing. Towards this goal, animation of a facial mask is demonstrated. The animation is based on images using Active Appearance Models (AAM......). Good quality reproduction of (low-resolution) coded video of an animated facial mask as low as 10-20 kbit/s using MPEG-4 object based video is demonstated....

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Riad I. Hammoud

    2014-10-01

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

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

    Science.gov (United States)

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

    2014-10-22

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

  19. 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...

  20. 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.

  1. 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.

  2. Reallocating attention during multiple object tracking.

    Science.gov (United States)

    Ericson, Justin M; Christensen, James C

    2012-07-01

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

  3. 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...

  4. IMPLEMENTATION OF OBJECT TRACKING ALGORITHMS ON THE BASIS OF CUDA TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    B. A. Zalesky

    2014-01-01

    Full Text Available A fast version of correlation algorithm to track objects on video-sequences made by a nonstabilized camcorder is presented. The algorithm is based on comparison of local correlations of the object image and regions of video-frames. The algorithm is implemented in programming technology CUDA. Application of CUDA allowed to attain real time execution of the algorithm. To improve its precision and stability, a robust version of the Kalman filter has been incorporated into the flowchart. Tests showed applicability of the algorithm to practical object tracking.

  5. 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...

  6. Tracking Objects with Networked Scattered Directional Sensors

    Science.gov (United States)

    Plarre, Kurt; Kumar, P. R.

    2007-12-01

    We study the problem of object tracking using highly directional sensors—sensors whose field of vision is a line or a line segment. A network of such sensors monitors a certain region of the plane. Sporadically, objects moving in straight lines and at a constant speed cross the region. A sensor detects an object when it crosses its line of sight, and records the time of the detection. No distance or angle measurements are available. The task of the sensors is to estimate the directions and speeds of the objects, and the sensor lines, which are unknown a priori. This estimation problem involves the minimization of a highly nonconvex cost function. To overcome this difficulty, we introduce an algorithm, which we call "adaptive basis algorithm." This algorithm is divided into three phases: in the first phase, the algorithm is initialized using data from six sensors and four objects; in the second phase, the estimates are updated as data from more sensors and objects are incorporated. The third phase is an optional coordinated transformation. The estimation is done in an "ad-hoc" coordinate system, which we call "adaptive coordinate system." When more information is available, for example, the location of six sensors, the estimates can be transformed to the "real-world" coordinate system. This constitutes the third phase.

  7. 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.

  8. Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

    Directory of Open Access Journals (Sweden)

    Gil-beom Lee

    2017-03-01

    Full Text Available Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

  9. Self-Motion Impairs Multiple-Object Tracking

    Science.gov (United States)

    Thomas, Laura E.; Seiffert, Adriane E.

    2010-01-01

    Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement…

  10. Real-Time Video Stylization Using Object Flows.

    Science.gov (United States)

    Lu, Cewu; Xiao, Yao; Tang, Chi-Keung

    2017-05-05

    We present a real-time video stylization system and demonstrate a variety of painterly styles rendered on real video inputs. The key technical contribution lies on the object flow, which is robust to inaccurate optical flow, unknown object transformation and partial occlusion as well. Since object flows relate regions of the same object across frames, shower-door effect can be effectively reduced where painterly strokes and textures are rendered on video objects. The construction of object flows is performed in real time and automatically after applying metric learning. To reduce temporal flickering, we extend the bilateral filtering into motion bilateral filtering. We propose quantitative metrics to measure the temporal coherence on structures and textures of our stylized videos, and perform extensive experiments to compare our stylized results with baseline systems and prior works specializing in watercolor and abstraction.

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

    Directory of Open Access Journals (Sweden)

    Lei Qin

    2014-05-01

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

  12. Real-time object detection, tracking and occlusion reasoning

    Science.gov (United States)

    Divakaran, Ajay; Yu, Qian; Tamrakar, Amir; Sawhney, Harpreet Singh; Zhu, Jiejie; Javed, Omar; Liu, Jingen; Cheng, Hui; Eledath, Jayakrishnan

    2018-02-27

    A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.

  13. 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.

  14. Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

    Directory of Open Access Journals (Sweden)

    Jaehoon Jung

    2016-06-01

    Full Text Available This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i automatic camera calibration using both moving objects and a background structure; (ii object depth estimation; and (iii detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems.

  15. Visual attention is required for multiple object tracking.

    Science.gov (United States)

    Tran, Annie; Hoffman, James E

    2016-12-01

    In the multiple object tracking task, participants attempt to keep track of a moving set of target objects embedded in an identical set of moving distractors. Depending on several display parameters, observers are usually only able to accurately track 3 to 4 objects. Various proposals attribute this limit to a fixed number of discrete indexes (Pylyshyn, 1989), limits in visual attention (Cavanagh & Alvarez, 2005), or "architectural limits" in visual cortical areas (Franconeri, 2013). The present set of experiments examined the specific role of visual attention in tracking using a dual-task methodology in which participants tracked objects while identifying letter probes appearing on the tracked objects and distractors. As predicted by the visual attention model, probe identification was faster and/or more accurate when probes appeared on tracked objects. This was the case even when probes were more than twice as likely to appear on distractors suggesting that some minimum amount of attention is required to maintain accurate tracking performance. When the need to protect tracking accuracy was relaxed, participants were able to allocate more attention to distractors when probes were likely to appear there but only at the expense of large reductions in tracking accuracy. A final experiment showed that people attend to tracked objects even when letters appearing on them are task-irrelevant, suggesting that allocation of attention to tracked objects is an obligatory process. These results support the claim that visual attention is required for tracking objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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)

  1. 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.

  2. Tracking multiple objects is limited only by object spacing, not by speed, time, or capacity.

    Science.gov (United States)

    Franconeri, S L; Jonathan, S V; Scimeca, J M

    2010-07-01

    In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors-the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the root cause of all performance constraints in multiple-object tracking. In two experiments, we found that as long as the distribution of object spacing is held constant, tracking performance is unaffected by large changes in object speed and tracking time. These results suggest that barring object-spacing constraints, people could reliably track an unlimited number of objects as fast as they could track a single object.

  3. 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.

  4. 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...

  5. 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...

  6. Automated Mulitple Object Optical Tracking and Recognition System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  7. 3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

    Science.gov (United States)

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

    2017-10-01

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

  8. VIDEO GAMES ARE AN INTERESTING OBJECT TO THE COGNITION STUDIES

    Directory of Open Access Journals (Sweden)

    Cleci Maraschin

    2013-12-01

    Full Text Available Video games create a virtual space that can be inhabited in various ways by the players. Despite the controversies in which they are constantly included, electronic games bear witness to the modus operandi in our contemporary cognition permeated by technical objects. By focusing the know-how instead of a declarative experience the games open questions in the field of new literacies and problematize the use of technology in teaching practices. From the development of a locative game at the Botanical Garden of Porto Alegre, this article discussed some, methodological, political and theoretical implications arising from the research with video games in the field of cognitive studies. We discuss, finally, three theoretical / methodological implications the practice with video games forces us to think: research the video game through the process of its operation, questioning cognitive policies that organize our everyday and map the complex web of practices that supports the use of technical objects.

  9. Objective video quality measure for application to tele-echocardiography.

    Science.gov (United States)

    Moore, Peter Thomas; O'Hare, Neil; Walsh, Kevin P; Ward, Neil; Conlon, Niamh

    2008-08-01

    Real-time tele-echocardiography is widely used to remotely diagnose or exclude congenital heart defects. Cost effective technical implementation is realised using low-bandwidth transmission systems and lossy compression (videoconferencing) schemes. In our study, DICOM video sequences were converted to common multimedia formats, which were then, compressed using three lossy compression algorithms. We then applied a digital (multimedia) video quality metric (VQM) to determine objectively a value for degradation due to compression. Three levels of compression were simulated by varying system bandwidth and compared to a subjective assessment of video clip quality by three paediatric cardiologists with more than 5 years of experience.

  10. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    He Dajun

    2004-01-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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...

  13. Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

    Science.gov (United States)

    Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

    2016-02-01

    Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

  14. GPS Based Tracking of Mobile Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Torp, Kristian

    2006-01-01

    Denne artikel beskriver hvorledes man med eksisterende teknologi, herunder Global Position System og General Packet Radio Service, effektivt kan tracke mobile objekter som f.eks. køretøjer med en garanteret nøjagtighed. Først beskrives den teknologiske platform. Herefter beskrives tre forskellige...... teknikker til at tracke mobile objekter. Teknikkerne bliver gradvis mere avancerede. De tre teknikker evalueres, og omkostningen for at tracke et mobilt objekt med en nøjagtighed på cirka 150 meter estimeres til mindre end 1 kr. pr. døgn baseret på priser fra et forsøg udført i 2004. Udgivelsesdato...

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

    Science.gov (United States)

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

    2016-05-01

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

  16. Context based Coding of Quantized Alpha Planes for Video Objects

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2002-01-01

    In object based video, each frame is a composition of objects that are coded separately. The composition is performed through the alpha plane that represents the transparency of the object. We present an alternative to MPEG-4 for coding of alpha planes that considers their specific properties....... Comparisons in terms of rate and distortion are provided, showing that the proposed coding scheme for still alpha planes is better than the algorithms for I-frames used in MPEG-4....

  17. Perceptual video quality assessment in H.264 video coding standard using objective modeling.

    Science.gov (United States)

    Karthikeyan, Ramasamy; Sainarayanan, Gopalakrishnan; Deepa, Subramaniam Nachimuthu

    2014-01-01

    Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to compute the perceptual video quality metric based on no reference method. Because of the shuttle difference between the original video and the encoded video the quality of the encoded picture gets degraded, this quality difference is introduced by the encoding process like Intra and Inter prediction. The proposed model takes into account of the artifacts introduced by these spatial and temporal activities in the hybrid block based coding methods and an objective modeling of these artifacts into subjective quality estimation is proposed. The proposed model calculates the objective quality metric using subjective impairments; blockiness, blur and jerkiness compared to the existing bitrate only calculation defined in the ITU G 1070 model. The accuracy of the proposed perceptual video quality metrics is compared against popular full reference objective methods as defined by VQEG.

  18. Compressed normalized block difference for object tracking

    Science.gov (United States)

    Gao, Yun; Zhang, Dengzhuo; Cai, Donglan; Zhou, Hao; Lan, Ge

    2018-04-01

    Feature extraction is very important for robust and real-time tracking. Compressive sensing provided a technical support for real-time feature extraction. However, all existing compressive tracking were based on compressed Haar-like feature, and how to compress many more excellent high-dimensional features is worth researching. In this paper, a novel compressed normalized block difference feature (CNBD) was proposed. For resisting noise effectively in a highdimensional normalized pixel difference feature (NPD), a normalized block difference feature extends two pixels in the original formula of NPD to two blocks. A CNBD feature can be obtained by compressing a normalized block difference feature based on compressive sensing theory, with the sparse random Gaussian matrix as the measurement matrix. The comparative experiments of 7 trackers on 20 challenging sequences showed that the tracker based on CNBD feature can perform better than other trackers, especially than FCT tracker based on compressed Haar-like feature, in terms of AUC, SR and Precision.

  19. Using standardized video cases for assessment of medical communication skills: reliability of an objective structured video examination by computer

    NARCIS (Netherlands)

    Hulsman, R. L.; Mollema, E. D.; Oort, F. J.; Hoos, A. M.; de Haes, J. C. J. M.

    2006-01-01

    OBJECTIVE: Using standardized video cases in a computerized objective structured video examination (OSVE) aims to measure cognitive scripts underlying overt communication behavior by questions on knowledge, understanding and performance. In this study the reliability of the OSVE assessment is

  20. A-Track: Detecting Moving Objects in FITS images

    Science.gov (United States)

    Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

    2017-04-01

    A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

  1. Is Seeing Believing? Identifying Aspects of Informative Videos that Indicate Objectivity

    NARCIS (Netherlands)

    H.M. Boots-Blankers (Helen)

    2017-01-01

    textabstractInformation in online videos can be misleading and unreliable. Video users tend to select videos with misleading information (Butler, 2013). To facilitate video users in their selection of videos they need an objectivity measure (Palumbo, 2012). We propose thirteen aspects of video that

  2. OBJECT TRACKING WITH ROTATION-INVARIANT LARGEST DIFFERENCE INDEXED LOCAL TERNARY PATTERN

    Directory of Open Access Journals (Sweden)

    J Shajeena

    2017-02-01

    Full Text Available This paper presents an ideal method for object tracking directly in the compressed domain in video sequences. An enhanced rotation-invariant image operator called Largest Difference Indexed Local Ternary Pattern (LDILTP has been proposed. The Local Ternary Pattern which worked very well in texture classification and face recognition is now extended for rotation invariant object tracking. Histogramming the LTP code makes the descriptor resistant to translation. The histogram intersection is used to find the similarity measure. This method is robust to noise and retain contrast details. The proposed scheme has been verified on various datasets and shows a commendable performance.

  3. Object Detection and Tracking-Based Camera Calibration for Normalized Human Height Estimation

    Directory of Open Access Journals (Sweden)

    Jaehoon Jung

    2016-01-01

    Full Text Available This paper presents a normalized human height estimation algorithm using an uncalibrated camera. To estimate the normalized human height, the proposed algorithm detects a moving object and performs tracking-based automatic camera calibration. The proposed method consists of three steps: (i moving human detection and tracking, (ii automatic camera calibration, and (iii human height estimation and error correction. The proposed method automatically calibrates camera by detecting moving humans and estimates the human height using error correction. The proposed method can be applied to object-based video surveillance systems and digital forensic.

  4. Multiple Object Permanence Tracking: Maintenance, Retrieval and Transformation of Dynamic Object Representations

    OpenAIRE

    Saiki, Jun

    2008-01-01

    Multiple object permanence tracking (MOPT) task revealed that our ability of maintaining and transforming multiple representations of complex feature-bound objects is limited to handle only 1-2 objects. Often reported capacity of 3-5 objects likely reflects memory for partial representations of objects and simple cases such as just color and their locations. Also, performance in multiple object tracking (MOT) task is likely mediated by spatiotemporal indices, not by feature-bound object repre...

  5. Impact of Constant Rate Factor on Objective Video Quality Assessment

    Directory of Open Access Journals (Sweden)

    Juraj Bienik

    2017-01-01

    Full Text Available This paper deals with the impact of constant rate factor value on the objective video quality assessment using PSNR and SSIM metrics. Compression efficiency of H.264 and H.265 codecs defined by different Constant rate factor (CRF values was tested. The assessment was done for eight types of video sequences depending on content for High Definition (HD, Full HD (FHD and Ultra HD (UHD resolution. Finally, performance of both mentioned codecs with emphasis on compression ratio and efficiency of coding was compared.

  6. Eye-tracking study of inanimate objects

    Directory of Open Access Journals (Sweden)

    Ković Vanja

    2009-01-01

    Full Text Available Unlike the animate objects, where participants were consistent in their looking patterns, for inanimates it was difficult to identify both consistent areas of fixations and a consistent order of fixations. Furthermore, in comparison to animate objects, in animates received significantly shorter total looking time, shorter longest looks and a smaller number of overall fixations. However, as with animates, looking patterns did not systematically differ between the naming and non-naming conditions. These results suggested that animacy, but not labelling, impacts on looking behavior in this paradigm. In the light of feature-based accounts of semantic memory organization, one could interpret these findings as suggesting that processing of the animate objects is based on the saliency/diagnosticity of their visual features (which is then reflected through participants eye-movements towards those features, whereas processing of the inanimate objects is based more on functional features (which cannot be easily captured by looking behavior in such a paradigm.

  7. 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

  8. Enhanced online convolutional neural networks for object tracking

    Science.gov (United States)

    Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

    2018-04-01

    In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

  9. Adaptive Colour Feature Identification in Image for Object Tracking

    Directory of Open Access Journals (Sweden)

    Feng Su

    2012-01-01

    Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

  10. Creation of nanoscale objects by swift heavy ion track manipulations

    International Nuclear Information System (INIS)

    Fink, D.; Petrov, A.; Stolterfoht, N.

    2003-01-01

    In this work we give an overview of the possibilities to create new objects with nanoscale dimensions with ion tracks, for future applications. This can be realized in two ways: by manipulation of latent swift heavy ion (SHI) tracks, or by embedding specific structures within etched SHI tracks. In the first case one can make use of irradiation effects such as phase transitions and chemical or structural changes along the tracks. In the latter case, one can fill etched SHI tracks with metals, semiconductors, insulating and conducting polymers, fullerite, or colloides. Wires and tubules with outer diameters, between about 50 nm and 5 μm and lengths of up to about 100 μm can be obtained. The most important production techniques are galvanic and chemical depositions. Ion Transmission Spectrometry has turned out to be an especially useful tool for the characterisation of the produced objects. Present studies aim at the construction of condensers, magnets, diodes, and sensors in etched tracks. An obstacle for the practical realization of smallest-size polymeric ion track devices is the statistical distribution of the ion tracks on the target areas, which yields some pixels without any track, and other pixels even with overlapping tracks on a given sample. In a first test experiment we demonstrate that one can, in principle, overcome that problem by taking self-ordered porous foils as masks for subsequent high-fluence SHI irradiation. (author)

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

    Science.gov (United States)

    Zelinsky, Gregory J; Todor, Andrei

    2010-12-29

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

  12. 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.

  13. 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.

  14. Efficient Coding of Shape and Transparency for Video Objects

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2007-01-01

    A novel scheme for coding gray-level alpha planes in object-based video is presented. Gray-level alpha planes convey the shape and the transparency information, which are required for smooth composition of video objects. The algorithm proposed is based on the segmentation of the alpha plane...... in three layers: binary shape layer, opaque layer, and intermediate layer. Thus, the latter two layers replace the single transparency layer of MPEG-4 Part 2. Different encoding schemes are specifically designed for each layer, utilizing cross-layer correlations to reduce the bit rate. First, the binary...... demonstrating that the proposed techniques provide substantial bit rate savings coding shape and transparency when compared to the tools adopted in MPEG-4 Part 2....

  15. Tracking of multiple objects with time-adjustable composite correlation filters

    Science.gov (United States)

    Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya

    2017-09-01

    An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.

  16. 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

  17. Object Tracking via 2DPCA and l2-Regularization

    Directory of Open Access Journals (Sweden)

    Haijun Wang

    2016-01-01

    Full Text Available We present a fast and robust object tracking algorithm by using 2DPCA and l2-regularization in a Bayesian inference framework. Firstly, we model the challenging appearance of the tracked object using 2DPCA bases, which exploit the strength of subspace representation. Secondly, we adopt the l2-regularization to solve the proposed presentation model and remove the trivial templates from the sparse tracking method which can provide a more fast tracking performance. Finally, we present a novel likelihood function that considers the reconstruction error, which is concluded from the orthogonal left-projection matrix and the orthogonal right-projection matrix. Experimental results on several challenging image sequences demonstrate that the proposed method can achieve more favorable performance against state-of-the-art tracking algorithms.

  18. Lagrangian 3D tracking of fluorescent microscopic objects in motion

    Science.gov (United States)

    Darnige, T.; Figueroa-Morales, N.; Bohec, P.; Lindner, A.; Clément, E.

    2017-05-01

    We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in microfluidic devices. The system is based on real-time image processing, determining the displacement of a x, y mechanical stage to keep the chosen object at a fixed position in the observation frame. The z displacement is based on the refocusing of the fluorescent object determining the displacement of a piezo mover keeping the moving object in focus. Track coordinates of the object with respect to the microfluidic device as well as images of the object are obtained at a frequency of several tenths of Hertz. This device is particularly well adapted to obtain trajectories of motile micro-organisms in microfluidic devices with or without flow.

  19. TRAX - Real-World Tracking of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Pakalnis, Stardas

    2007-01-01

    accuracy. This paper presents the TRAX tracking system that supports several techniques capable of tracking the current positions of moving objects with guaranteed accuracies at low update and communication costs in real-world settings. The techniques are readily relevant for practical applications......, but they also have implications for continued research. The tracking techniques offer a realistic setting for existing query processing techniques that assume that it is possible to always know the exact positions of moving objects. The techniques enable studies of trade-offs between querying and update...

  20. 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.

  1. 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.

  2. Improving human object recognition performance using video enhancement techniques

    Science.gov (United States)

    Whitman, Lucy S.; Lewis, Colin; Oakley, John P.

    2004-12-01

    Atmospheric scattering causes significant degradation in the quality of video images, particularly when imaging over long distances. The principle problem is the reduction in contrast due to scattered light. It is known that when the scattering particles are not too large compared with the imaging wavelength (i.e. Mie scattering) then high spatial resolution information may be contained within a low-contrast image. Unfortunately this information is not easily perceived by a human observer, particularly when using a standard video monitor. A secondary problem is the difficulty of achieving a sharp focus since automatic focus techniques tend to fail in such conditions. Recently several commercial colour video processing systems have become available. These systems use various techniques to improve image quality in low contrast conditions whilst retaining colour content. These systems produce improvements in subjective image quality in some situations, particularly in conditions of haze and light fog. There is also some evidence that video enhancement leads to improved ATR performance when used as a pre-processing stage. Psychological literature indicates that low contrast levels generally lead to a reduction in the performance of human observers in carrying out simple visual tasks. The aim of this paper is to present the results of an empirical study on object recognition in adverse viewing conditions. The chosen visual task was vehicle number plate recognition at long ranges (500 m and beyond). Two different commercial video enhancement systems are evaluated using the same protocol. The results show an increase in effective range with some differences between the different enhancement systems.

  3. Visual object tracking by correlation filters and online learning

    Science.gov (United States)

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

    2018-06-01

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

  4. Video based object representation and classification using multiple covariance matrices.

    Science.gov (United States)

    Zhang, Yurong; Liu, Quan

    2017-01-01

    Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

  5. 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.

  6. Combining 3D structure of real video and synthetic objects

    Science.gov (United States)

    Kim, Man-Bae; Song, Mun-Sup; Kim, Do-Kyoon

    1998-04-01

    This paper presents a new approach of combining real video and synthetic objects. The purpose of this work is to use the proposed technology in the fields of advanced animation, virtual reality, games, and so forth. Computer graphics has been used in the fields previously mentioned. Recently, some applications have added real video to graphic scenes for the purpose of augmenting the realism that the computer graphics lacks in. This approach called augmented or mixed reality can produce more realistic environment that the entire use of computer graphics. Our approach differs from the virtual reality and augmented reality in the manner that computer- generated graphic objects are combined to 3D structure extracted from monocular image sequences. The extraction of the 3D structure requires the estimation of 3D depth followed by the construction of a height map. Graphic objects are then combined to the height map. The realization of our proposed approach is carried out in the following steps: (1) We derive 3D structure from test image sequences. The extraction of the 3D structure requires the estimation of depth and the construction of a height map. Due to the contents of the test sequence, the height map represents the 3D structure. (2) The height map is modeled by Delaunay triangulation or Bezier surface and each planar surface is texture-mapped. (3) Finally, graphic objects are combined to the height map. Because 3D structure of the height map is already known, Step (3) is easily manipulated. Following this procedure, we produced an animation video demonstrating the combination of the 3D structure and graphic models. Users can navigate the realistic 3D world whose associated image is rendered on the display monitor.

  7. Joint Conditional Random Field Filter for Multi-Object Tracking

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  8. Lagrangian 3D tracking of fluorescent microscopic objects in motion

    OpenAIRE

    Darnige, T.; Figueroa-Morales, N.; Bohec, P.; Lindner, A.; Clément, E.

    2016-01-01

    We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in micro-fluidic devices. The system is based on real-time image processing, determining the displacement of a x,y mechanical stage to keep the chosen object at a fixed position in the observation frame. The z displacement is based on the refocusing of the fluorescent object determining the displ...

  9. Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Apurva Samdurkar

    2018-06-01

    Full Text Available Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS and cross diamond search algorithms (CDS are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.

  10. Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

    Directory of Open Access Journals (Sweden)

    Zhenghao Xi

    2014-01-01

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

  11. Objective analysis of image quality of video image capture systems

    Science.gov (United States)

    Rowberg, Alan H.

    1990-07-01

    As Picture Archiving and Communication System (PACS) technology has matured, video image capture has become a common way of capturing digital images from many modalities. While digital interfaces, such as those which use the ACR/NEMA standard, will become more common in the future, and are preferred because of the accuracy of image transfer, video image capture will be the dominant method in the short term, and may continue to be used for some time because of the low cost and high speed often associated with such devices. Currently, virtually all installed systems use methods of digitizing the video signal that is produced for display on the scanner viewing console itself. A series of digital test images have been developed for display on either a GE CT9800 or a GE Signa MRI scanner. These images have been captured with each of five commercially available image capture systems, and the resultant images digitally transferred on floppy disk to a PC1286 computer containing Optimast' image analysis software. Here the images can be displayed in a comparative manner for visual evaluation, in addition to being analyzed statistically. Each of the images have been designed to support certain tests, including noise, accuracy, linearity, gray scale range, stability, slew rate, and pixel alignment. These image capture systems vary widely in these characteristics, in addition to the presence or absence of other artifacts, such as shading and moire pattern. Other accessories such as video distribution amplifiers and noise filters can also add or modify artifacts seen in the captured images, often giving unusual results. Each image is described, together with the tests which were performed using them. One image contains alternating black and white lines, each one pixel wide, after equilibration strips ten pixels wide. While some systems have a slew rate fast enough to track this correctly, others blur it to an average shade of gray, and do not resolve the lines, or give

  12. Self-Occlusions and Disocclusions in Causal Video Object Segmentation

    KAUST Repository

    Yang, Yanchao

    2016-02-19

    We propose a method to detect disocclusion in video sequences of three-dimensional scenes and to partition the disoccluded regions into objects, defined by coherent deformation corresponding to surfaces in the scene. Our method infers deformation fields that are piecewise smooth by construction without the need for an explicit regularizer and the associated choice of weight. It then partitions the disoccluded region and groups its components with objects by leveraging on the complementarity of motion and appearance cues: Where appearance changes within an object, motion can usually be reliably inferred and used for grouping. Where appearance is close to constant, it can be used for grouping directly. We integrate both cues in an energy minimization framework, incorporate prior assumptions explicitly into the energy, and propose a numerical scheme. © 2015 IEEE.

  13. 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.

  14. 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.

  15. Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm.

    Science.gov (United States)

    Tombu, Michael; Seiffert, Adriane E

    2011-04-01

    People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target-distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking--one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone.

  16. 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.

  17. 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…

  18. Invariant Hough Random Ferns for Object Detection and Tracking

    Directory of Open Access Journals (Sweden)

    Yimin Lin

    2014-01-01

    Full Text Available This paper introduces an invariant Hough random ferns (IHRF incorporating rotation and scale invariance into the local feature description, random ferns classifier training, and Hough voting stages. It is especially suited for object detection under changes in object appearance and scale, partial occlusions, and pose variations. The efficacy of this approach is validated through experiments on a large set of challenging benchmark datasets, and the results demonstrate that the proposed method outperforms state-of-the-art conventional methods such as bounding-box-based and part-based methods. Additionally, we also propose an efficient clustering scheme based on the local patches’ appearance and their geometric relations that can provide pixel-accurate, top-down segmentations from IHRF back-projections. This refined segmentation can be used to improve the quality of online object tracking because it avoids the drifting problem. Thus, an online tracking framework based on IHRF, which is trained and updated in each frame to distinguish and segment the object from the background, is established. Finally, the experimental results on both object segmentation and long-term object tracking show that this method yields accurate and robust tracking performance in a variety of complex scenarios, especially in cases of severe occlusions and nonrigid deformations.

  19. Track-before-detect procedures for detection of extended object

    Science.gov (United States)

    Fan, Ling; Zhang, Xiaoling; Shi, Jun

    2011-12-01

    In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance). Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

  20. Device-free object tracking using passive tags

    CERN Document Server

    Han, Jinsong; Zhao, Kun; Jiang, Zhiping

    2014-01-01

    This SpringerBrief examines the use of cheap commercial passive RFID tags to achieve accurate device-free object-tracking. It presents a sensitive detector, named Twins, which uses a pair of adjacent passive tags to detect uncooperative targets (such as intruders). Twins leverages a newly observed phenomenon called critical state that is caused by interference among passive tags.The author expands on the previous object tracking methods, which are mostly device-based, and reveals a new interference model and their extensive experiments for validation. A prototype implementation of the Twins-ba

  1. Track-before-detect procedures for detection of extended object

    Directory of Open Access Journals (Sweden)

    Fan Ling

    2011-01-01

    Full Text Available Abstract In this article, we present a particle filter (PF-based track-before-detect (PF TBD procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance. Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

  2. Deep Spatial-Temporal Joint Feature Representation for Video Object Detection

    Directory of Open Access Journals (Sweden)

    Baojun Zhao

    2018-03-01

    Full Text Available With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP.

  3. Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

    Science.gov (United States)

    Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

    2018-03-04

    With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

  4. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  5. DEEP-SEE: Joint Object Detection, Tracking and Recognition with Application to Visually Impaired Navigational Assistance

    Directory of Open Access Journals (Sweden)

    Ruxandra Tapu

    2017-10-01

    Full Text Available In this paper, we introduce the so-called DEEP-SEE framework that jointly exploits computer vision algorithms and deep convolutional neural networks (CNNs to detect, track and recognize in real time objects encountered during navigation in the outdoor environment. A first feature concerns an object detection technique designed to localize both static and dynamic objects without any a priori knowledge about their position, type or shape. The methodological core of the proposed approach relies on a novel object tracking method based on two convolutional neural networks trained offline. The key principle consists of alternating between tracking using motion information and predicting the object location in time based on visual similarity. The validation of the tracking technique is performed on standard benchmark VOT datasets, and shows that the proposed approach returns state-of-the-art results while minimizing the computational complexity. Then, the DEEP-SEE framework is integrated into a novel assistive device, designed to improve cognition of VI people and to increase their safety when navigating in crowded urban scenes. The validation of our assistive device is performed on a video dataset with 30 elements acquired with the help of VI users. The proposed system shows high accuracy (>90% and robustness (>90% scores regardless on the scene dynamics.

  6. 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

  7. Automatic feature-based grouping during multiple object tracking.

    Science.gov (United States)

    Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

    2013-12-01

    Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

  8. 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.

  9. Mapping and tracking of moving objects in dynamic environments

    CSIR Research Space (South Africa)

    Pancham, A

    2012-10-01

    Full Text Available In order for mobile robots to operate in dynamic or real world environments they must be able to localise themselves while building a map of the environment, and detect and track moving objects. This work involves the research and implementation...

  10. Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

    Science.gov (United States)

    Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

    2012-12-01

    Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

  11. Object tracking on mobile devices using binary descriptors

    Science.gov (United States)

    Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

    2015-03-01

    With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

  12. 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

  13. Visual recognition and tracking of objects for robot sensing

    International Nuclear Information System (INIS)

    Lowe, D.G.

    1994-01-01

    An overview is presented of a number of techniques used for recognition and motion tracking of articulated 3-D objects. With recent advances in robust methods for model-based vision and improved performance of computer systems, it will soon be possible to build low-cost, high-reliability systems for model-based motion tracking. Such systems can be expected to open up a wide range of applications in robotics by providing machines with real-time information about their environment. This paper describes a number of techniques for efficiently matching parameterized 3-D models to image features. The matching methods are robust with respect to missing and ambiguous features as well as measurement errors. Unlike most previous work on model-based motion tracking, this system provides for the integrated treatment of matching and measurement errors during motion tracking. The initial application is in a system for real-time motion tracking of articulated 3-D objects. With the future addition of an indexing component, these same techniques can also be used for general model-based recognition. The current real-time implementation is based on matching straight line segments, but some preliminary experiments on matching arbitrary curves are also described. (author)

  14. 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.

  15. Tracking Object Existence From an Autonomous Patrol Vehicle

    Science.gov (United States)

    Wolf, Michael; Scharenbroich, Lucas

    2011-01-01

    An autonomous vehicle patrols a large region, during which an algorithm receives measurements of detected potential objects within its sensor range. The goal of the algorithm is to track all objects in the region over time. This problem differs from traditional multi-target tracking scenarios because the region of interest is much larger than the sensor range and relies on the movement of the sensor through this region for coverage. The goal is to know whether anything has changed between visits to the same location. In particular, two kinds of alert conditions must be detected: (1) a previously detected object has disappeared and (2) a new object has appeared in a location already checked. For the time an object is within sensor range, the object can be assumed to remain stationary, changing position only between visits. The problem is difficult because the upstream object detection processing is likely to make many errors, resulting in heavy clutter (false positives) and missed detections (false negatives), and because only noisy, bearings-only measurements are available. This work has three main goals: (1) Associate incoming measurements with known objects or mark them as new objects or false positives, as appropriate. For this, a multiple hypothesis tracker was adapted to this scenario. (2) Localize the objects using multiple bearings-only measurements to provide estimates of global position (e.g., latitude and longitude). A nonlinear Kalman filter extension provides these 2D position estimates using the 1D measurements. (3) Calculate the probability that a suspected object truly exists (in the estimated position), and determine whether alert conditions have been triggered (for new objects or disappeared objects). The concept of a probability of existence was created, and a new Bayesian method for updating this probability at each time step was developed. A probabilistic multiple hypothesis approach is chosen because of its superiority in handling the

  16. Determination of feature generation methods for PTZ camera object tracking

    Science.gov (United States)

    Doyle, Daniel D.; Black, Jonathan T.

    2012-06-01

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

  17. 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...

  18. The Visual Object Tracking VOT2016 Challenge Results

    KAUST Repository

    Kristan, Matej; Leonardis, Aleš; Matas, Jiři; Felsberg, Michael; Pflugfelder, Roman; Čehovin, Luka; Vojí r̃, Tomá š; Hä ger, Gustav; Lukežič, Alan; Ferná ndez, Gustavo; Gupta, Abhinav; Petrosino, Alfredo; Memarmoghadam, Alireza; Garcia-Martin, Alvaro; Solí s Montero, André s; Vedaldi, Andrea; Robinson, Andreas; Ma, Andy J.; Varfolomieiev, Anton; Alatan, Aydin; Erdem, Aykut; Ghanem, Bernard; Liu, Bin; Han, Bohyung; Martinez, Brais; Chang, Chang-Ming; Xu, Changsheng; Sun, Chong; Kim, Daijin; Chen, Dapeng; Du, Dawei; Mishra, Deepak; Yeung, Dit-Yan; Gundogdu, Erhan; Erdem, Erkut; Khan, Fahad; Porikli, Fatih; Zhao, Fei; Bunyak, Filiz; Battistone, Francesco; Zhu, Gao; Roffo, Giorgio; Subrahmanyam, Gorthi R. K. Sai; Bastos, Guilherme; Seetharaman, Guna; Medeiros, Henry; Li, Hongdong; Qi, Honggang; Bischof, Horst; Possegger, Horst; Lu, Huchuan; Lee, Hyemin; Nam, Hyeonseob; Chang, Hyung Jin; Drummond, Isabela; Valmadre, Jack; Jeong, Jae-chan; Cho, Jae-il; Lee, Jae-Yeong; Zhu, Jianke; Feng, Jiayi; Gao, Jin; Choi, Jin Young; Xiao, Jingjing; Kim, Ji-Wan; Jeong, Jiyeoup; Henriques, Joã o F.; Lang, Jochen; Choi, Jongwon; Martinez, Jose M.; Xing, Junliang; Gao, Junyu; Palaniappan, Kannappan; Lebeda, Karel; Gao, Ke; Mikolajczyk, Krystian; Qin, Lei; Wang, Lijun; Wen, Longyin; Bertinetto, Luca; Rapuru, Madan Kumar; Poostchi, Mahdieh; Maresca, Mario; Danelljan, Martin; Mueller, Matthias; Zhang, Mengdan; Arens, Michael; Valstar, Michel; Tang, Ming; Baek, Mooyeol; Khan, Muhammad Haris; Wang, Naiyan; Fan, Nana; Al-Shakarji, Noor; Miksik, Ondrej; Akin, Osman; Moallem, Payman; Senna, Pedro; Torr, Philip H. S.; Yuen, Pong C.; Huang, Qingming; Martin-Nieto, Rafael; Pelapur, Rengarajan; Bowden, Richard; Laganiè re, Robert; Stolkin, Rustam; Walsh, Ryan; Krah, Sebastian B.; Li, Shengkun; Zhang, Shengping; Yao, Shizeng; Hadfield, Simon; Melzi, Simone; Lyu, Siwei; Li, Siyi; Becker, Stefan; Golodetz, Stuart; Kakanuru, Sumithra; Choi, Sunglok; Hu, Tao; Mauthner, Thomas; Zhang, Tianzhu; Pridmore, Tony; Santopietro, Vincenzo; Hu, Weiming; Li, Wenbo; Hü bner, Wolfgang; Lan, Xiangyuan; Wang, Xiaomeng; Li, Xin; Li, Yang; Demiris, Yiannis; Wang, Yifan; Qi, Yuankai; Yuan, Zejian; Cai, Zexiong; Xu, Zhan; He, Zhenyu; Chi, Zhizhen

    2016-01-01

    The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).

  19. The Visual Object Tracking VOT2015 Challenge Results

    KAUST Repository

    Kristan, Matej; Matas, Jiri; Leonardis, Ale; Felsberg, Michael; Cehovin, Luka; Fernandez, Gustavo; Vojir, Toma; Hager, Gustav; Nebehay, Georg; Pflugfelder, Roman; Gupta, Abhinav; Bibi, Adel Aamer; Lukezic, Alan; Garcia-Martin, Alvaro; Saffari, Amir; Petrosino, Alfredo; Montero, Andres Solıs; Varfolomieiev, Anton; Baskurt, Atilla; Zhao, Baojun; Ghanem, Bernard; Martinez, Brais; Lee, ByeongJu; Han, Bohyung; Wang, Chaohui; Garcia, Christophe; Zhang, Chunyuan; Schmid, Cordelia; Tao, Dacheng; Kim, Daijin; Huang, Dafei; Prokhorov, Danil; Du, Dawei; Yeung, Dit-Yan; Ribeiro, Eraldo; Khan, Fahad Shahbaz; Porikli, Fatih; Bunyak, Filiz; Zhu, Gao; Seetharaman, Guna; Kieritz, Hilke; Yau, Hing Tuen; Li, Hongdong; Qi, Honggang; Bischof, Horst; Possegger, Horst; Lee, Hyemin; Nam, Hyeonseob; Bogun, Ivan; Jeong, Jae-chan; Cho, Jae-il; Lee, Jae-Yeong; Zhu, Jianke; Shi, Jianping; Li, Jiatong; Jia, Jiaya; Feng, Jiayi; Gao, Jin; Choi, Jin Young; Kim, Ji-Wan; Lang, Jochen; Martinez, Jose M.; Choi, Jongwon; Xing, Junliang; Xue, Kai; Palaniappan, Kannappan; Lebeda, Karel; Alahari, Karteek; Gao, Ke; Yun, Kimin; Wong, Kin Hong; Luo, Lei; Ma, Liang; Ke, Lipeng; Wen, Longyin; Bertinetto, Luca; Pootschi, Mahdieh; Maresca, Mario; Danelljan, Martin; Wen, Mei; Zhang, Mengdan; Arens, Michael; Valstar, Michel; Tang, Ming; Chang, Ming-Ching; Khan, Muhammad Haris; Fan, Nana; Wang, Naiyan; Miksik, Ondrej; Torr, Philip H S; Wang, Qiang; Martin-Nieto, Rafael; Pelapur, Rengarajan; Bowden, Richard; Laganiere, Robert; Moujtahid, Salma; Hare, Sam; Hadfield, Simon; Lyu, Siwei; Li, Siyi; Zhu, Song-Chun; Becker, Stefan; Duffner, Stefan; Hicks, Stephen L; Golodetz, Stuart; Choi, Sunglok; Wu, Tianfu; Mauthner, Thomas; Pridmore, Tony; Hu, Weiming; Hubner, Wolfgang; Wang, Xiaomeng; Li, Xin; Shi, Xinchu; Zhao, Xu; Mei, Xue; Shizeng, Yao; Hua, Yang; Li, Yang; Lu, Yang; Li, Yuezun; Chen, Zhaoyun; Huang, Zehua; Chen, Zhe; Zhang, Zhe; He, Zhenyu; Hong, Zhibin

    2015-01-01

    The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

  20. The Visual Object Tracking VOT2016 Challenge Results

    KAUST Repository

    Kristan, Matej

    2016-11-02

    The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).

  1. The Visual Object Tracking VOT2015 Challenge Results

    KAUST Repository

    Kristan, Matej

    2015-12-07

    The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

  2. Group of Hexagonal Search Patterns for Motion Estimation and Object Tracking

    International Nuclear Information System (INIS)

    Elazm, A.A.; Mahmoud, I.I; Hashima, S.M.

    2010-01-01

    This paper presents a group of fast block matching algorithms based on the hexagon pattern search .A new predicted one point hexagon (POPHEX) algorithm is proposed and compared with other well known algorithms. The comparison of these algorithms and our proposed one is performed for both motion estimation and object tracking. Test video sequences are used to demonstrate the behavior of studied algorithms. All algorithms are implemented in MATLAB environment .Experimental results showed that the proposed algorithm posses less number of search points however its computational overhead is little increased due to prediction procedure.

  3. 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

  4. Growth in the Number of SSN Tracked Orbital Objects

    Science.gov (United States)

    Stansbery, Eugene G.

    2004-01-01

    The number of objects in earth orbit tracked by the US Space Surveillance Network (SSN) has experienced unprecedented growth since March, 2003. Approximately 2000 orbiting objects have been added to the "Analyst list" of tracked objects. This growth is primarily due to the resumption of full power/full time operation of the AN/FPS-108 Cobra Dane radar located on Shemya Island, AK. Cobra Dane is an L-band (23-cm wavelength) phased array radar which first became operational in 1977. Cobra Dane was a "Collateral Sensor" in the SSN until 1994 when its communication link with the Space Control Center (SCC) was closed. NASA and the Air Force conducted tests in 1999 using Cobra Dane to detect and track small debris. These tests confirmed that the radar was capable of detecting and maintaining orbits on objects as small as 5-cm diameter. Subsequently, Cobra Dane was reconnected to the SSN and resumed full power/full time space surveillance operations on March 4, 2003. This paper will examine the new data and its implications to the understanding of the orbital debris environment and orbital safety.

  5. 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.

  6. 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

  7. INTEGRATION OF VIDEO IMAGES AND CAD WIREFRAMES FOR 3D OBJECT LOCALIZATION

    Directory of Open Access Journals (Sweden)

    R. A. Persad

    2012-07-01

    Full Text Available The tracking of moving objects from single images has received widespread attention in photogrammetric computer vision and considered to be at a state of maturity. This paper presents a model-driven solution for localizing moving objects detected from monocular, rotating and zooming video images in a 3D reference frame. To realize such a system, the recovery of 2D to 3D projection parameters is essential. Automatic estimation of these parameters is critical, particularly for pan-tilt-zoom (PTZ surveillance cameras where parameters change spontaneously upon camera motion. In this work, an algorithm for automated parameter retrieval is proposed. This is achieved by matching linear features between incoming images from video sequences and simple geometric 3D CAD wireframe models of man-made structures. The feature matching schema uses a hypothesis-verify optimization framework referred to as LR-RANSAC. This novel method improves the computational efficiency of the matching process in comparison to the standard RANSAC robust estimator. To demonstrate the applicability and performance of the method, experiments have been performed on indoor and outdoor image sequences under varying conditions with lighting changes and occlusions. Reliability of the matching algorithm has been analyzed by comparing the automatically determined camera parameters with ground truth (GT. Dependability of the retrieved parameters for 3D localization has also been assessed by comparing the difference between 3D positions of moving image objects estimated using the LR-RANSAC-derived parameters and those computed using GT parameters.

  8. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

    Directory of Open Access Journals (Sweden)

    Bernardin Keni

    2008-01-01

    Full Text Available Abstract Simultaneous tracking of multiple persons in real-world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. Recently, there has been a growing interest in organizing systematic evaluations to compare the various techniques. Unfortunately, the lack of common metrics for measuring the performance of multiple object trackers still makes it hard to compare their results. In this work, we introduce two intuitive and general metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently label objects over time. These metrics have been extensively used in two large-scale international evaluations, the 2006 and 2007 CLEAR evaluations, to measure and compare the performance of multiple object trackers for a wide variety of tracking tasks. Selected performance results are presented and the advantages and drawbacks of the presented metrics are discussed based on the experience gained during the evaluations.

  9. Efficient Tracking of Moving Objects with Precision Guarantees

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Nenortaite, Jovita

    2004-01-01

    Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...... an object is moving. Empirical performance studies based on a real road network and GPS logs from cars are reported....

  10. The Role of Visual Working Memory in Attentive Tracking of Unique Objects

    Science.gov (United States)

    Makovski, Tal; Jiang, Yuhong V.

    2009-01-01

    When tracking moving objects in space humans usually attend to the objects' spatial locations and update this information over time. To what extent do surface features assist attentive tracking? In this study we asked participants to track identical or uniquely colored objects. Tracking was enhanced when objects were unique in color. The benefit…

  11. Connection-based and object-based grouping in multiple-object tracking: A developmental study

    OpenAIRE

    Hallen, Ruth; Reusens, J. (Julie); Evers, K. (Kris); de-Wit, Lee; Wagemans, Johan

    2018-01-01

    textabstractDevelopmental research on Gestalt laws has previously revealed that, even as young as infancy, we are bound to group visual elements into unitary structures in accordance with a variety of organizational principles. Here, we focus on the developmental trajectory of both connection-based and object-based grouping, and investigate their impact on object formation in participants, aged 9-21 years old (N = 113), using a multiple-object tracking paradigm. Results reveal a main effect o...

  12. Particle filters for object tracking: enhanced algorithm and efficient implementations

    International Nuclear Information System (INIS)

    Abd El-Halym, H.A.

    2010-01-01

    Object tracking and recognition is a hot research topic. In spite of the extensive research efforts expended, the development of a robust and efficient object tracking algorithm remains unsolved due to the inherent difficulty of the tracking problem. Particle filters (PFs) were recently introduced as a powerful, post-Kalman filter, estimation tool that provides a general framework for estimation of nonlinear/ non-Gaussian dynamic systems. Particle filters were advanced for building robust object trackers capable of operation under severe conditions (small image size, noisy background, occlusions, fast object maneuvers ..etc.). The heavy computational load of the particle filter remains a major obstacle towards its wide use.In this thesis, an Excitation Particle Filter (EPF) is introduced for object tracking. A new likelihood model is proposed. It depends on multiple functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modified the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. This modification is based on re-exciting the particles if their weights fall below a memorized weight value. The proposed enhanced PF is implemented in software and evaluated. Its results are compared with a single likelihood function PF tracker, Particle Swarm Optimization (PSO) tracker, a correlation tracker, as well as, an edge tracker. The experimental results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness, and occlusion compared with other methods Efficient novel hardware architectures of the Sample Important Re sample Filter (SIRF) and the EPF are implemented. Three novel hardware architectures of the SIRF for object tracking are introduced. The first architecture is a two-step sequential PF machine, where particle generation, weight calculation and normalization are carried out in parallel during the first step followed by a sequential re

  13. Object acquisition and tracking for space-based surveillance

    Science.gov (United States)

    1991-11-01

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

  14. 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.

  15. An adaptive approach to human motion tracking from video

    Science.gov (United States)

    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.

  16. Connection-based and object-based grouping in multiple-object tracking: A developmental study.

    Science.gov (United States)

    Van der Hallen, Ruth; Reusens, Julie; Evers, Kris; de-Wit, Lee; Wagemans, Johan

    2018-03-30

    Developmental research on Gestalt laws has previously revealed that, even as young as infancy, we are bound to group visual elements into unitary structures in accordance with a variety of organizational principles. Here, we focus on the developmental trajectory of both connection-based and object-based grouping, and investigate their impact on object formation in participants, aged 9-21 years old (N = 113), using a multiple-object tracking paradigm. Results reveal a main effect of both age and grouping type, indicating that 9- to 21-year-olds are sensitive to both connection-based and object-based grouping interference, and tracking ability increases with age. In addition to its importance for typical development, these results provide an informative baseline to understand clinical aberrations in this regard. Statement of contribution What is already known on this subject? The origin of the Gestalt principles is still an ongoing debate: Are they innate, learned over time, or both? Developmental research has revealed how each Gestalt principle has its own trajectory and unique relationship to visual experience. Both connectedness and object-based grouping play an important role in object formation during childhood. What does this study add? The study identifies how sensitivity to connectedness and object-based grouping evolves in individuals, aged 9-21 years old. Using multiple-object tracking, results reveal that the ability to track multiple objects increases with age. These results provide an informative baseline to understand clinical aberrations in different types of grouping. © 2018 The Authors. British Journal of Developmental Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

  17. Objective video quality assessment method for freeze distortion based on freeze aggregation

    Science.gov (United States)

    Watanabe, Keishiro; Okamoto, Jun; Kurita, Takaaki

    2006-01-01

    With the development of the broadband network, video communications such as videophone, video distribution, and IPTV services are beginning to become common. In order to provide these services appropriately, we must manage them based on subjective video quality, in addition to designing a network system based on it. Currently, subjective quality assessment is the main method used to quantify video quality. However, it is time-consuming and expensive. Therefore, we need an objective quality assessment technology that can estimate video quality from video characteristics effectively. Video degradation can be categorized into two types: spatial and temporal. Objective quality assessment methods for spatial degradation have been studied extensively, but methods for temporal degradation have hardly been examined even though it occurs frequently due to network degradation and has a large impact on subjective quality. In this paper, we propose an objective quality assessment method for temporal degradation. Our approach is to aggregate multiple freeze distortions into an equivalent freeze distortion and then derive the objective video quality from the equivalent freeze distortion. Specifically, our method considers the total length of all freeze distortions in a video sequence as the length of the equivalent single freeze distortion. In addition, we propose a method using the perceptual characteristics of short freeze distortions. We verified that our method can estimate the objective video quality well within the deviation of subjective video quality.

  18. A Fisher Kernel Approach for Multiple Instance Based Object Retrieval in Video Surveillance

    Directory of Open Access Journals (Sweden)

    MIRONICA, I.

    2015-11-01

    Full Text Available This paper presents an automated surveillance system that exploits the Fisher Kernel representation in the context of multiple-instance object retrieval task. The proposed algorithm has the main purpose of tracking a list of persons in several video sources, using only few training examples. In the first step, the Fisher Kernel representation describes a set of features as the derivative with respect to the log-likelihood of the generative probability distribution that models the feature distribution. Then, we learn the generative probability distribution over all features extracted from a reduced set of relevant frames. The proposed approach shows significant improvements and we demonstrate that Fisher kernels are well suited for this task. We demonstrate the generality of our approach in terms of features by conducting an extensive evaluation with a broad range of keypoints features. Also, we evaluate our method on two standard video surveillance datasets attaining superior results comparing to state-of-the-art object recognition algorithms.

  19. Tracking moving objects with megavoltage portal imaging: A feasibility study

    International Nuclear Information System (INIS)

    Meyer, Juergen; Richter, Anne; Baier, Kurt; Wilbert, Juergen; Guckenberger, Matthias; Flentje, Michael

    2006-01-01

    Four different algorithms were investigated with the aim to determine their suitability to track an object in conventional megavoltage portal images. The algorithms considered were the mean of the sum of squared differences (MSSD), mutual information (MI), the correlation ratio (CR), and the correlation coefficient (CC). Simulation studies were carried out with various image series containing a rigid object of interest that was moved along a predefined trajectory. For each of the series the signal-to-noise ratio (SNR) was varied to compare the performance of the algorithms under noisy conditions. For a poor SNR of -6 dB the mean tracking error was 2.4, 6.5, 39.0, and 17.2 pixels for MSSD, CC, CR and MI, respectively, with a standard deviation of 1.9, 12.9, 19.5, and 7.5 pixels, respectively. The size of a pixel was 0.5 mm. These results improved to 1.1, 1.3, 1.3, and 2.0 pixels, respectively, with a standard deviation of 0.6, 0.8, 0.8, and 2.1 pixels, respectively, when a mean filter was applied to the images prior to tracking. The implementation of MSSD into existing in-house software demonstrated that, depending on the search range, it was possible to process between 2 and 15 images/s, making this approach capable of real-time applications. In conclusion, the best geometric tracking accuracy overall was obtained with MSSD, followed by CC, CR, and MI. The simplest and best algorithm, both in terms of geometric accuracy as well as computational cost, was the MSSD algorithm and was therefore the method of choice

  20. 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.

  1. 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...

  2. Tracker: Image-Processing and Object-Tracking System Developed

    Science.gov (United States)

    Klimek, Robert B.; Wright, Theodore W.

    1999-01-01

    Tracker is an object-tracking and image-processing program designed and developed at the NASA Lewis Research Center to help with the analysis of images generated by microgravity combustion and fluid physics experiments. Experiments are often recorded on film or videotape for analysis later. Tracker automates the process of examining each frame of the recorded experiment, performing image-processing operations to bring out the desired detail, and recording the positions of the objects of interest. It can load sequences of images from disk files or acquire images (via a frame grabber) from film transports, videotape, laser disks, or a live camera. Tracker controls the image source to automatically advance to the next frame. It can employ a large array of image-processing operations to enhance the detail of the acquired images and can analyze an arbitrarily large number of objects simultaneously. Several different tracking algorithms are available, including conventional threshold and correlation-based techniques, and more esoteric procedures such as "snake" tracking and automated recognition of character data in the image. The Tracker software was written to be operated by researchers, thus every attempt was made to make the software as user friendly and self-explanatory as possible. Tracker is used by most of the microgravity combustion and fluid physics experiments performed by Lewis, and by visiting researchers. This includes experiments performed on the space shuttles, Mir, sounding rockets, zero-g research airplanes, drop towers, and ground-based laboratories. This software automates the analysis of the flame or liquid s physical parameters such as position, velocity, acceleration, size, shape, intensity characteristics, color, and centroid, as well as a number of other measurements. It can perform these operations on multiple objects simultaneously. Another key feature of Tracker is that it performs optical character recognition (OCR). This feature is useful in

  3. Connected Component Model for Multi-Object Tracking.

    Science.gov (United States)

    He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

    2016-08-01

    In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

  4. 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

  5. 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.

  6. INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING

    Institute of Scientific and Technical Information of China (English)

    Chen Ken; Napolitano; Zhang Yun; Li Dong

    2010-01-01

    The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.

  7. 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.

  8. Applicability of Existing Objective Metrics of Perceptual Quality for Adaptive Video Streaming

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Krasula, Lukás; Shahid, Muhammad

    2016-01-01

    Objective video quality metrics are designed to estimate the quality of experience of the end user. However, these objective metrics are usually validated with video streams degraded under common distortion types. In the presented work, we analyze the performance of published and known full......-reference and noreference quality metrics in estimating the perceived quality of adaptive bit-rate video streams knowingly out of scope. Experimental results indicate not surprisingly that state of the art objective quality metrics overlook the perceived degradations in the adaptive video streams and perform poorly...

  9. Consumer-based technology for distribution of surgical videos for objective evaluation.

    Science.gov (United States)

    Gonzalez, Ray; Martinez, Jose M; Lo Menzo, Emanuele; Iglesias, Alberto R; Ro, Charles Y; Madan, Atul K

    2012-08-01

    The Global Operative Assessment of Laparoscopic Skill (GOALS) is one validated metric utilized to grade laparoscopic skills and has been utilized to score recorded operative videos. To facilitate easier viewing of these recorded videos, we are developing novel techniques to enable surgeons to view these videos. The objective of this study is to determine the feasibility of utilizing widespread current consumer-based technology to assist in distributing appropriate videos for objective evaluation. Videos from residents were recorded via a direct connection from the camera processor via an S-video output via a cable into a hub to connect to a standard laptop computer via a universal serial bus (USB) port. A standard consumer-based video editing program was utilized to capture the video and record in appropriate format. We utilized mp4 format, and depending on the size of the file, the videos were scaled down (compressed), their format changed (using a standard video editing program), or sliced into multiple videos. Standard available consumer-based programs were utilized to convert the video into a more appropriate format for handheld personal digital assistants. In addition, the videos were uploaded to a social networking website and video sharing websites. Recorded cases of laparoscopic cholecystectomy in a porcine model were utilized. Compression was required for all formats. All formats were accessed from home computers, work computers, and iPhones without difficulty. Qualitative analyses by four surgeons demonstrated appropriate quality to grade for these formats. Our preliminary results show promise that, utilizing consumer-based technology, videos can be easily distributed to surgeons to grade via GOALS via various methods. Easy accessibility may help make evaluation of resident videos less complicated and cumbersome.

  10. ‘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.

  11. Scale-adaptive Local Patches for Robust Visual Object Tracking

    Directory of Open Access Journals (Sweden)

    Kang Sun

    2014-04-01

    Full Text Available This paper discusses the problem of robustly tracking objects which undergo rapid and dramatic scale changes. To remove the weakness of global appearance models, we present a novel scheme that combines object’s global and local appearance features. The local feature is a set of local patches that geometrically constrain the changes in the target’s appearance. In order to adapt to the object’s geometric deformation, the local patches could be removed and added online. The addition of these patches is constrained by the global features such as color, texture and motion. The global visual features are updated via the stable local patches during tracking. To deal with scale changes, we adapt the scale of patches in addition to adapting the object bound box. We evaluate our method by comparing it to several state-of-the-art trackers on publicly available datasets. The experimental results on challenging sequences confirm that, by using this scale-adaptive local patches and global properties, our tracker outperforms the related trackers in many cases by having smaller failure rate as well as better accuracy.

  12. Subjective Analysis and Objective Characterization of Adaptive Bitrate Videos

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Tavakoli, Samira; Brunnström, Kjell

    2016-01-01

    The HTTP Adaptive Streaming (HAS) technology allows video service providers to improve the network utilization and thereby increasing the end-users’ Quality of Experience (QoE).This has made HAS a widely used approach for audiovisual delivery. There are several previous studies aiming to identify...... the factors influencing on subjective QoE of adaptation events.However, adapting the video quality typically lasts in a time scale much longer than what current standardized subjective testing methods are designed for, thus making the full matrix design of the experiment on an event level hard to achieve....... In this study, we investigated the overall subjective QoE of 6 minutes long video sequences containing different sequential adaptation events. This was compared to a data set from our previous work performed to evaluate the individual adaptation events. We could then derive a relationship between the overall...

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

    Science.gov (United States)

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

    2016-04-01

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

  14. Video Cases in Teacher Education: A review study on intended and achieved learning objectives by video cases

    NARCIS (Netherlands)

    Geerts, Walter; Van der Werff, Anne; Hummel, Hans; Van Geert, Paul

    2014-01-01

    This literature review focuses on the use of video cases in the education of preservice teachers as a means of achieving higher order learning objectives that are necessary for gaining situated knowledge. An overview of both intended and achieved learning objectives in relevant studies involving

  15. 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.

  16. 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.

  17. Object recognition with video-theodolites and without targeting the object

    International Nuclear Information System (INIS)

    Kahmen, H.; Seixas, A. de

    1999-01-01

    At the Department of Applied Geodesy and Engineering Geodesy (TU Vienna) an new kind of theodolite measurement system is under development, enabling measurements with an accuracy of 1:30.000 with and without targeting the object. The main goal is, to develop an intelligent multi-sensor system. Thus an operator is only needed to supervise the system. Results are gained on-sine and can be stored in a CAD system. If no artificial targets are used identification of points has to be performed by the Master-Theodolite. The method, used in our project, is based on interest operators. The Slave-Theodolite has to track the master by searching for homologous regions. The before described method can only be used, if there is some texture on the surface of the object. If that is not fulfilled, a 'grid-line-method' can be used, to get informations about the surface of the object. In the case of a cartesian co-ordinate system, for instance, the grid-lines can be chosen by the operator before the measurement process is started. The theodolite-measurement system is then able to detect the grid-lines and to find the positions where the grid-lines intersect the surface of the object. This system could be used for positioning the different components of a particle accelerator. (author)

  18. Object recognition with video-theodolites and without targeting the object

    Energy Technology Data Exchange (ETDEWEB)

    Kahmen, H.; Seixas, A. de [University of Technology Vienna, Institute of Geodesy and Geophysics, Vienna (Austria)

    1999-07-01

    At the Department of Applied Geodesy and Engineering Geodesy (TU Vienna) an new kind of theodolite measurement system is under development, enabling measurements with an accuracy of 1:30.000 with and without targeting the object. The main goal is, to develop an intelligent multi-sensor system. Thus an operator is only needed to supervise the system. Results are gained on-sine and can be stored in a CAD system. If no artificial targets are used identification of points has to be performed by the Master-Theodolite. The method, used in our project, is based on interest operators. The Slave-Theodolite has to track the master by searching for homologous regions. The before described method can only be used, if there is some texture on the surface of the object. If that is not fulfilled, a 'grid-line-method' can be used, to get informations about the surface of the object. In the case of a cartesian co-ordinate system, for instance, the grid-lines can be chosen by the operator before the measurement process is started. The theodolite-measurement system is then able to detect the grid-lines and to find the positions where the grid-lines intersect the surface of the object. This system could be used for positioning the different components of a particle accelerator. (author)

  19. 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.

  20. Track-to-track association for object matching in an inter-vehicle communication system

    Science.gov (United States)

    Yuan, Ting; Roth, Tobias; Chen, Qi; Breu, Jakob; Bogdanovic, Miro; Weiss, Christian A.

    2015-09-01

    Autonomous driving poses unique challenges for vehicle environment perception due to the complex driving environment the autonomous vehicle finds itself in and differentiates from remote vehicles. Due to inherent uncertainty of the traffic environments and incomplete knowledge due to sensor limitation, an autonomous driving system using only local onboard sensor information is generally not sufficiently enough for conducting a reliable intelligent driving with guaranteed safety. In order to overcome limitations of the local (host) vehicle sensing system and to increase the likelihood of correct detections and classifications, collaborative information from cooperative remote vehicles could substantially facilitate effectiveness of vehicle decision making process. Dedicated Short Range Communication (DSRC) system provides a powerful inter-vehicle wireless communication channel to enhance host vehicle environment perceiving capability with the aid of transmitted information from remote vehicles. However, there is a major challenge before one can fuse the DSRC-transmitted remote information and host vehicle Radar-observed information (in the present case): the remote DRSC data must be correctly associated with the corresponding onboard Radar data; namely, an object matching problem. Direct raw data association (i.e., measurement-to-measurement association - M2MA) is straightforward but error-prone, due to inherent uncertain nature of the observation data. The uncertainties could lead to serious difficulty in matching decision, especially, using non-stationary data. In this study, we present an object matching algorithm based on track-to-track association (T2TA) and evaluate the proposed approach with prototype vehicles in real traffic scenarios. To fully exploit potential of the DSRC system, only GPS position data from remote vehicle are used in fusion center (at host vehicle), i.e., we try to get what we need from the least amount of information; additional feature

  1. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  2. 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.

  3. Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

    Science.gov (United States)

    Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

    2016-09-01

    We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Self Occlusion and Disocclusion in Causal Video Object Segmentation

    Science.gov (United States)

    2015-12-18

    22, 37, 13, 17], since an explicit 3D reconstruction of the scene produces as a side effect a partition of the video into regions. However, it...83.4 79.3 82.8 84.4 34.7 Soldier 84.0 81.1 83.8 66.6 66.5 Monkey 85.1 86.0 84.8 79.0 61.9 Bird of Paradise 96.1 93.0 94.0 92.2 86.8 BMXPerson 92.8 88.9

  6. Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions (Open Access)

    Science.gov (United States)

    2013-10-03

    fol- low the setup in the literature ([13, 14]), and use 5 (birdfall, cheetah , girl, monkeydog and parachute) of the videos for evaluation (since the...segmentation labeling results of the method, GT is the ground-truth labeling of the video, and F is the (a) Birdfall (b) Cheetah (c) Girl (d) Monkeydog...Video Ours [14] [13] [20] [6] birdfall 155 189 288 252 454 cheetah 633 806 905 1142 1217 girl 1488 1698 1785 1304 1755 monkeydog 365 472 521 563 683

  7. Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

    Science.gov (United States)

    Alsadik, B.; Gerke, M.; Vosselman, G.

    2015-03-01

    Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

  8. EFFICIENT USE OF VIDEO FOR 3D MODELLING OF CULTURAL HERITAGE OBJECTS

    Directory of Open Access Journals (Sweden)

    B. Alsadik

    2015-03-01

    Full Text Available Currently, there is a rapid development in the techniques of the automated image based modelling (IBM, especially in advanced structure-from-motion (SFM and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 – 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

  9. optimization of object tracking based on enhanced imperialist ...

    African Journals Online (AJOL)

    Damuut and Dogara

    A typical example is the Roman Empire which had influence or control over ... the Enhance Imperialist Competitive Algorithm (EICA) in optimizing the generated ... segment the video frame into a number of regions based on visual features like ...

  10. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2014-01-01

    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

  11. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2013-01-01

    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

  12. A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

    Science.gov (United States)

    Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

    2014-01-01

    This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

  13. 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.

  14. An Innovative SIFT-Based Method for Rigid Video Object Recognition

    Directory of Open Access Journals (Sweden)

    Jie Yu

    2014-01-01

    Full Text Available This paper presents an innovative SIFT-based method for rigid video object recognition (hereafter called RVO-SIFT. Just like what happens in the vision system of human being, this method makes the object recognition and feature updating process organically unify together, using both trajectory and feature matching, and thereby it can learn new features not only in the training stage but also in the recognition stage, which can improve greatly the completeness of the video object’s features automatically and, in turn, increases the ratio of correct recognition drastically. The experimental results on real video sequences demonstrate its surprising robustness and efficiency.

  15. 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

  16. 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.

  17. Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

    Science.gov (United States)

    2017-09-01

    past research related to the tasks of ego-motion estimation and object tracking from the viewpoint of their role in continuous object learning...in visual object tracking, competitions are held each year to identify the most accurate and robust tracking implementations. Over recent competitions...information should they share) or vice versa? These are just some of the questions that must be addressed in future research toward continuous object

  18. Multiple-object permanence tracking: limitation in maintenance and transformation of perceptual objects.

    Science.gov (United States)

    Saiki, Jun

    2002-01-01

    Research on change blindness and transsaccadic memory revealed that a limited amount of information is retained across visual disruptions in visual working memory. It has been proposed that visual working memory can hold four to five coherent object representations. To investigate their maintenance and transformation in dynamic situations, I devised an experimental paradigm called multiple-object permanence tracking (MOPT) that measures memory for multiple feature-location bindings in dynamic situations. Observers were asked to detect any color switch in the middle of a regular rotation of a pattern with multiple colored disks behind an occluder. The color-switch detection performance dramatically declined as the pattern rotation velocity increased, and this effect of object motion was independent of the number of targets. The MOPT task with various shapes and colors showed that color-shape conjunctions are not available in the MOPT task. These results suggest that even completely predictable motion severely reduces our capacity of object representations, from four to only one or two.

  19. 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.

  20. Subjective rating and objective evaluation of the acoustic and indoor climate conditions in video conferencing rooms

    DEFF Research Database (Denmark)

    Hauervig-Jørgensen, Charlotte; Jeong, Cheol-Ho; Toftum, Jørn

    2017-01-01

    Today, face-to-face meetings are frequently replaced by video conferences in order to reduce costs and carbon footprint related to travels and to increase the company efficiency. Yet, complaints about the difficulty of understanding the speech of the participants in both rooms of the video...... conference occur. The aim of this study is to find out the main causes of difficulties in speech communication. Correlation studies between subjective perceptions were conducted through questionnaires and objective acoustic and indoor climate parameters related to video conferencing. Based on four single...

  1. Human-like object tracking and gaze estimation with PKD android.

    Science.gov (United States)

    Wijayasinghe, Indika B; Miller, Haylie L; Das, Sumit K; Bugnariu, Nicoleta L; Popa, Dan O

    2016-05-01

    As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold : to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.

  2. Human-like object tracking and gaze estimation with PKD android

    Science.gov (United States)

    Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K.; Bugnariu, Nicoleta L.; Popa, Dan O.

    2016-05-01

    As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold: to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.

  3. Topical video object discovery from key frames by modeling word co-occurrence prior.

    Science.gov (United States)

    Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

    2015-12-01

    A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

  4. The effects of scene characteristics, resolution, and compression on the ability to recognize objects in video

    Science.gov (United States)

    Dumke, Joel; Ford, Carolyn G.; Stange, Irena W.

    2011-03-01

    Public safety practitioners increasingly use video for object recognition tasks. These end users need guidance regarding how to identify the level of video quality necessary for their application. The quality of video used in public safety applications must be evaluated in terms of its usability for specific tasks performed by the end user. The Public Safety Communication Research (PSCR) project performed a subjective test as one of the first in a series to explore visual intelligibility in video-a user's ability to recognize an object in a video stream given various conditions. The test sought to measure the effects on visual intelligibility of three scene parameters (target size, scene motion, scene lighting), several compression rates, and two resolutions (VGA (640x480) and CIF (352x288)). Seven similarly sized objects were used as targets in nine sets of near-identical source scenes, where each set was created using a different combination of the parameters under study. Viewers were asked to identify the objects via multiple choice questions. Objective measurements were performed on each of the scenes, and the ability of the measurement to predict visual intelligibility was studied.

  5. 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.

  6. 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.

  7. A Flexible Object-of-Interest Annotation Framework for Online Video Portals

    Directory of Open Access Journals (Sweden)

    Robert Sorschag

    2012-02-01

    Full Text Available In this work, we address the use of object recognition techniques to annotate what is shown where in online video collections. These annotations are suitable to retrieve specific video scenes for object related text queries which is not possible with the manually generated metadata that is used by current portals. We are not the first to present object annotations that are generated with content-based analysis methods. However, the proposed framework possesses some outstanding features that offer good prospects for its application in real video portals. Firstly, it can be easily used as background module in any video environment. Secondly, it is not based on a fixed analysis chain but on an extensive recognition infrastructure that can be used with all kinds of visual features, matching and machine learning techniques. New recognition approaches can be integrated into this infrastructure with low development costs and a configuration of the used recognition approaches can be performed even on a running system. Thus, this framework might also benefit from future advances in computer vision. Thirdly, we present an automatic selection approach to support the use of different recognition strategies for different objects. Last but not least, visual analysis can be performed efficiently on distributed, multi-processor environments and a database schema is presented to store the resulting video annotations as well as the off-line generated low-level features in a compact form. We achieve promising results in an annotation case study and the instance search task of the TRECVID 2011 challenge.

  8. 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.

  9. Deep Learning for Detection of Object-Based Forgery in Advanced Video

    Directory of Open Access Journals (Sweden)

    Ye Yao

    2017-12-01

    Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

  10. 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.

  11. 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.

  12. Image and video based remote target localization and tracking on smartphones

    Science.gov (United States)

    Wang, Qia; Lobzhanidze, Alex; Jang, Hyun; Zeng, Wenjun; Shang, Yi; Yang, Jingyu

    2012-06-01

    Smartphones are becoming popular nowadays not only because of its communication functionality but also, more importantly, its powerful sensing and computing capability. In this paper, we describe a novel and accurate image and video based remote target localization and tracking system using the Android smartphones, by leveraging its built-in sensors such as camera, digital compass, GPS, etc. Even though many other distance estimation or localization devices are available, our all-in-one, easy-to-use localization and tracking system on low cost and commodity smartphones is first of its kind. Furthermore, smartphones' exclusive user-friendly interface has been effectively taken advantage of by our system to facilitate low complexity and high accuracy. Our experimental results show that our system works accurately and efficiently.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

    2018-01-01

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

  15. Studying visual attention using the multiple object tracking paradigm: A tutorial review.

    Science.gov (United States)

    Meyerhoff, Hauke S; Papenmeier, Frank; Huff, Markus

    2017-07-01

    Human observers are capable of tracking multiple objects among identical distractors based only on their spatiotemporal information. Since the first report of this ability in the seminal work of Pylyshyn and Storm (1988, Spatial Vision, 3, 179-197), multiple object tracking has attracted many researchers. A reason for this is that it is commonly argued that the attentional processes studied with the multiple object paradigm apparently match the attentional processing during real-world tasks such as driving or team sports. We argue that multiple object tracking provides a good mean to study the broader topic of continuous and dynamic visual attention. Indeed, several (partially contradicting) theories of attentive tracking have been proposed within the almost 30 years since its first report, and a large body of research has been conducted to test these theories. With regard to the richness and diversity of this literature, the aim of this tutorial review is to provide researchers who are new in the field of multiple object tracking with an overview over the multiple object tracking paradigm, its basic manipulations, as well as links to other paradigms investigating visual attention and working memory. Further, we aim at reviewing current theories of tracking as well as their empirical evidence. Finally, we review the state of the art in the most prominent research fields of multiple object tracking and how this research has helped to understand visual attention in dynamic settings.

  16. 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.

  17. Tracking Non-stellar Objects on Ground and in Space

    DEFF Research Database (Denmark)

    Riis, Troels; Jørgensen, John Leif

    1999-01-01

    Many space exploration missions require a fast, early and accurate detection of a specific target. E.g. missions to asteroids, x-ray source missions or interplanetary missions.A second generation star tracker may be used for accurate detection of non-stellar objects of interest for such missions......, simply by listing all objects detected in an image not being identified as a star. Of course a lot of deep space objects will be listed too, especially if the detection threshold is set to let faint object pass through. Assuming a detection threshold of, say mv 7 (the Hipparcos catalogue is complete...... objects that do not move. For stationary objects no straightforward procedure exists to reduce the size of the list, but in the case the user has an approximate knowledge of which area to search the amount of data may be reduced substantially. In the case of a mission to an asteroid, the above described...

  18. Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

    International Nuclear Information System (INIS)

    Kadouf, Hani Hunud A; Mustafah, Yasir Mohd

    2013-01-01

    With robotics becoming a fundamental aspect of modern society, further research and consequent application is ever increasing. Aerial robotics, in particular, covers applications such as surveillance in hostile military zones or search and rescue operations in disaster stricken areas, where ground navigation is impossible. The increased visual capacity of UAV's (Unmanned Air Vehicles) is also applicable in the support of ground vehicles to provide supplies for emergency assistance, for scouting purposes or to extend communication beyond insurmountable land or water barriers. The Quadrotor, which is a small UAV has its lift generated by four rotors and can be controlled by altering the speeds of its motors relative to each other. The four rotors allow for a higher payload than single or dual rotor UAVs, which makes it safer and more suitable to carry camera and transmitter equipment. An onboard camera is used to capture and transmit images of the Quadrotor's First Person View (FPV) while in flight, in real time, wirelessly to a base station. The aim of this research is to develop an autonomous quadrotor platform capable of transmitting real time video signals to a base station for processing. The result from the image analysis will be used as a feedback in the quadrotor positioning control. To validate the system, the algorithm should have the capacity to make the quadrotor identify, track or hover above stationary or moving objects

  19. Infants Track Word Forms in Early Word-Object Associations

    Science.gov (United States)

    Zamuner, Tania S.; Fais, Laurel; Werker, Janet F.

    2014-01-01

    A central component of language development is word learning. One characterization of this process is that language learners discover objects and then look for word forms to associate with these objects (Mcnamara, 1984; Smith, 2000). Another possibility is that word forms themselves are also important, such that once learned, hearing a familiar…

  20. 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

  1. Quantitative Analysis of the Usage of a Pedagogical Tool Combining Questions Listed as Learning Objectives and Answers Provided as Online Videos

    Directory of Open Access Journals (Sweden)

    Odette Laneuville

    2015-05-01

    Full Text Available To improve the learning of basic concepts in molecular biology of an undergraduate science class, a pedagogical tool was developed, consisting of learning objectives listed at the end of each lecture and answers to those objectives made available as videos online. The aim of this study was to determine if the pedagogical tool was used by students as instructed, and to explore students’ perception of its usefulness. A combination of quantitative survey data and measures of online viewing was used to evaluate the usage of the pedagogical practice. A total of 77 short videos linked to 11 lectures were made available to 71 students, and 64 completed the survey. Using online tracking tools, a total of 7046 views were recorded. Survey data indicated that most students (73.4% accessed all videos, and the majority (98.4% found the videos to be useful in assisting their learning. Interestingly, approximately half of the students (53.1% always or most of the time used the pedagogical tool as recommended, and consistently answered the learning objectives before watching the videos. While the proposed pedagogical tool was used by the majority of students outside the classroom, only half used it as recommended limiting the impact on students’ involvement in the learning of the material presented in class.

  2. Tracking Location and Features of Objects within Visual Working Memory

    Directory of Open Access Journals (Sweden)

    Michael Patterson

    2012-10-01

    Full Text Available Four studies examined how color or shape features can be accessed to retrieve the memory of an object's location. In each trial, 6 colored dots (Experiments 1 and 2 or 6 black shapes (Experiments 3 and 4 were displayed in randomly selected locations for 1.5 s. An auditory cue for either the shape or the color to-be-remembered was presented either simultaneously, immediately, or 2 s later. Non-informative cues appeared in some trials to serve as a control condition. After a 4 s delay, 5/6 objects were re-presented, and participants indicated the location of the missing object either by moving the mouse (Experiments 1 and 3, or by typing coordinates using a grid (Experiments 2 and 4. Compared to the control condition, cues presented simultaneously or immediately after stimuli improved location accuracy in all experiments. However, cues presented after 2 s only improved accuracy in Experiment 1. These results suggest that location information may not be addressable within visual working memory using shape features. In Experiment 1, but not Experiments 2–4, cues significantly improved accuracy when they indicated the missing object could be any of the three identical objects. In Experiments 2–4, location accuracy was highly impaired when the missing object came from a group of identical rather than uniquely identifiable objects. This indicates that when items with similar features are presented, location accuracy may be reduced. In summary, both feature type and response mode can influence the accuracy and accessibility of visual working memory for object location.

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

    Science.gov (United States)

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

    2016-01-01

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

  4. Object tracking system using a VSW algorithm based on color and point features

    Directory of Open Access Journals (Sweden)

    Lim Hye-Youn

    2011-01-01

    Full Text Available Abstract An object tracking system using a variable search window (VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI, and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.

  5. Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

    Science.gov (United States)

    2014-09-01

    any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a...tracking 10 cm2 cross section targets in LEO as well as tracking near Earth objects (NEOs) such as meteoroids, and asteroids may well be possible...using short pulsewidth doublet pulse coherent ladar technique offers a means for precision tracking. The technique offers best of both worlds ; precise

  6. A software-based tool for video motion tracking in the surgical skills assessment landscape

    NARCIS (Netherlands)

    Ganni, S.; Botden, Sanne M.B.I.; Chmarra, M.K.; Goossens, R.H.M.; Jakimowicz, J.J.

    2018-01-01

    Background: The use of motion tracking has been proved to provide an objective assessment in surgical skills training. Current systems, however, require the use of additional equipment or specialised laparoscopic instruments and cameras to extract the data. The aim of this study was to determine

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

    Directory of Open Access Journals (Sweden)

    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.

  8. Efficient Tracking, Logging, and Blocking of Accesses to Digital Objects

    Science.gov (United States)

    2015-09-01

    suggestions for reducing this burden, to Department of Defense, Washington Headquarters Services , Directorate for Information Operations and Reports...4.3.1 Initial User Feedback ................................................................................... 33 4.4 Objective Benchmarks of the System...used and, that we can trap guest OS page faults. Shadow paging is a technique that creates a copy of guest page tables, sanitizes and propagates the

  9. A novel no-reference objective stereoscopic video quality assessment method based on visual saliency analysis

    Science.gov (United States)

    Yang, Xinyan; Zhao, Wei; Ye, Long; Zhang, Qin

    2017-07-01

    This paper proposes a no-reference objective stereoscopic video quality assessment method with the motivation that making the effect of objective experiments close to that of subjective way. We believe that the image regions with different visual salient degree should not have the same weights when designing an assessment metric. Therefore, we firstly use GBVS algorithm to each frame pairs and separate both the left and right viewing images into the regions with strong, general and week saliency. Besides, local feature information like blockiness, zero-crossing and depth are extracted and combined with a mathematical model to calculate a quality assessment score. Regions with different salient degree are assigned with different weights in the mathematical model. Experiment results demonstrate the superiority of our method compared with the existed state-of-the-art no-reference objective Stereoscopic video quality assessment methods.

  10. Object detection via eye tracking and fringe restraint

    Science.gov (United States)

    Pan, Fei; Zhang, Hanming; Zeng, Ying; Tong, Li; Yan, Bin

    2017-07-01

    Object detection is a computer vision problem which caught a large amount of attention. But the candidate boundingboxes extracted from only image features may end up with false-detection due to the semantic gap between the top-down and the bottom up information. In this paper, we propose a novel method for generating object bounding-boxes proposals using the combination of eye fixation point, saliency detection and edges. The new method obtains a fixation orientated Gaussian map, optimizes the map through single-layer cellular automata, and derives bounding-boxes from the optimized map on three levels. Then we score the boxes by combining all the information above, and choose the box with the highest score to be the final box. We perform an evaluation of our method by comparing with previous state-ofthe art approaches on the challenging POET datasets, the images of which are chosen from PASCAL VOC 2012. Our method outperforms them on small scale objects while comparable to them in general.

  11. T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos

    OpenAIRE

    Kang, Kai; Li, Hongsheng; Yan, Junjie; Zeng, Xingyu; Yang, Bin; Xiao, Tong; Zhang, Cong; Wang, Zhe; Wang, Ruohui; Wang, Xiaogang; Ouyang, Wanli

    2016-01-01

    The state-of-the-art performance for object detection has been significantly improved over the past two years. Besides the introduction of powerful deep neural networks such as GoogleNet and VGG, novel object detection frameworks such as R-CNN and its successors, Fast R-CNN and Faster R-CNN, play an essential role in improving the state-of-the-art. Despite their effectiveness on still images, those frameworks are not specifically designed for object detection from videos. Temporal and context...

  12. Moving object detection in top-view aerial videos improved by image stacking

    Science.gov (United States)

    Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

    2017-08-01

    Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

  13. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

    OpenAIRE

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

  14. 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.

  15. 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.

  16. 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.

  17. Nurse-surgeon object transfer: video analysis of communication and situation awareness in the operating theatre.

    Science.gov (United States)

    Korkiakangas, Terhi; Weldon, Sharon-Marie; Bezemer, Jeff; Kneebone, Roger

    2014-09-01

    One of the most central collaborative tasks during surgical operations is the passing of objects, including instruments. Little is known about how nurses and surgeons achieve this. The aim of the present study was to explore what factors affect this routine-like task, resulting in fast or slow transfer of objects. A qualitative video study, informed by an observational ethnographic approach, was conducted in a major teaching hospital in the UK. A total of 20 general surgical operations were observed. In total, approximately 68 h of video data have been reviewed. A subsample of 225 min has been analysed in detail using interactional video-analysis developed within the social sciences. Two factors affecting object transfer were observed: (1) relative instrument trolley position and (2) alignment. The scrub nurse's instrument trolley position (close to vs. further back from the surgeon) and alignment (gaze direction) impacts on the communication with the surgeon, and consequently, on the speed of object transfer. When the scrub nurse was standing close to the surgeon, and "converged" to follow the surgeon's movements, the transfer occurred more seamlessly and faster (1.0 s). The smoothness of object transfer can be improved by adjusting the scrub nurse's instrument trolley position, enabling a better monitoring of surgeon's bodily conduct and affording early orientation (awareness) to an upcoming request (changing situation). Object transfer is facilitated by the surgeon's embodied practices, which can elicit the nurse's attention to the request and, as a response, maximise a faster object transfer. A simple intervention to highlight the significance of these factors could improve communication in the operating theatre. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. 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.

  19. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  20. 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.

  1. A software-based tool for video motion tracking in the surgical skills assessment landscape

    OpenAIRE

    Ganni, S.; Botden, Sanne M.B.I.; Chmarra, M.K.; Goossens, R.H.M.; Jakimowicz, J.J.

    2018-01-01

    Background: The use of motion tracking has been proved to provide an objective assessment in surgical skills training. Current systems, however, require the use of additional equipment or specialised laparoscopic instruments and cameras to extract the data. The aim of this study was to determine the possibility of using a software-based solution to extract the data. Methods: 6 expert and 23 novice participants performed a basic laparoscopic cholecystectomy procedure in the operating room. The...

  2. Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

    Directory of Open Access Journals (Sweden)

    Andrea Cavallaro

    2004-06-01

    Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to

  3. Shifting Weights: Adapting Object Detectors from Image to Video (Author’s Manuscript)

    Science.gov (United States)

    2012-12-08

    Skateboard Sewing Machine Sandwich Figure 1: Images of the “ Skateboard ”, “Sewing machine”, and “Sandwich” classes taken from (top row) ImageNet [7...InitialBL VideoPosBL Our method(nt) Our method(full) Gopalan et al. [18] (PLS) Gopalan et al. [18] (SVM) Skateboard 4.29% 2.89% 10.44% 10.44% 0.04% 0.94...belongs to no event class. We select 6 object classes to learn object detectors for because they are commonly present in selected events: “ Skateboard

  4. Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain

    Directory of Open Access Journals (Sweden)

    Boris Mansencal

    2007-11-01

    Full Text Available Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream, different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects, their number, their shape, and their appearance can constitute a good mean for content description. For this reason, we propose to combine both motion information and region-based color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach, which we refer to as “rough indexing,” consists in processing P-frame motion information first, and then in performing I-frame color segmentation. Next, since many details can be lost due to the low-resolution data, to improve the object detection results, a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort.

  5. Efficient Dynamic Adaptation Strategies for Object Tracking Tree in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    CHEN, M.

    2012-12-01

    Full Text Available Most object tracking trees are established using the predefined mobility profile. However, when the real object's movement behaviors and query rates are different from the predefined mobility profile and query rates, the update cost and query cost of object tracking tree may increase. To upgrade the object tracking tree, the sink needs to send very large messages to collect the real movement information from the network, introducing a very large message overhead, which is referred to as adaptation cost. The Sub Root Message-Tree Adaptive procedure was proposed to dynamically collect the real movement information under the sub-tree and reconstruct the sub-tree to provide good performance based on the collected information. The simulation results indicates that the Sub Root Message-Tree Adaptive procedure is sufficient to achieve good total cost and lower adaptation cost.

  6. Multi Camera Multi Object Tracking using Block Search over Epipolar Geometry

    Directory of Open Access Journals (Sweden)

    Saman Sargolzaei

    2000-01-01

    Full Text Available We present strategy for multi-objects tracking in multi camera environment for the surveillance and security application where tracking multitude subjects are of utmost importance in a crowded scene. Our technique assumes partially overlapped multi-camera setup where cameras share common view from different angle to assess positions and activities of subjects under suspicion. To establish spatial correspondence between camera views we employ an epipolar geometry technique. We propose an overlapped block search method to find the interested pattern (target in new frames. Color pattern update scheme has been considered to further optimize the efficiency of the object tracking when object pattern changes due to object motion in the field of views of the cameras. Evaluation of our approach is presented with the results on PETS2007 dataset..

  7. A Novel Object Tracking Algorithm Based on Compressed Sensing and Entropy of Information

    Directory of Open Access Journals (Sweden)

    Ding Ma

    2015-01-01

    Full Text Available Object tracking has always been a hot research topic in the field of computer vision; its purpose is to track objects with specific characteristics or representation and estimate the information of objects such as their locations, sizes, and rotation angles in the current frame. Object tracking in complex scenes will usually encounter various sorts of challenges, such as location change, dimension change, illumination change, perception change, and occlusion. This paper proposed a novel object tracking algorithm based on compressed sensing and information entropy to address these challenges. First, objects are characterized by the Haar (Haar-like and ORB features. Second, the dimensions of computation space of the Haar and ORB features are effectively reduced through compressed sensing. Then the above-mentioned features are fused based on information entropy. Finally, in the particle filter framework, an object location was obtained by selecting candidate object locations in the current frame from the local context neighboring the optimal locations in the last frame. Our extensive experimental results demonstrated that this method was able to effectively address the challenges of perception change, illumination change, and large area occlusion, which made it achieve better performance than existing approaches such as MIL and CT.

  8. Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

    Science.gov (United States)

    Kim, Han-Ul; Kim, Chang-Su

    2017-08-01

    In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

  9. Tracking of Vehicle Movement on a Parking Lot Based on Video Detection

    Directory of Open Access Journals (Sweden)

    Ján HALGAŠ

    2014-06-01

    Full Text Available This article deals with topic of transport vehicles identification for dynamic and static transport based on video detection. It explains some of the technologies and approaches necessary for processing of specific image information (transport situation. The paper also describes a design of algorithm for vehicle detection on parking lot and consecutive record of trajectory into virtual environment. It shows a new approach to moving object detection (vehicles, people, and handlers on an enclosed area with emphasis on secure parking. The created application enables automatic identification of trajectory of specific objects moving within the parking area. The application was created in program language C++ with using an open source library OpenCV.

  10. Real-time visual tracking of less textured three-dimensional objects on mobile platforms

    Science.gov (United States)

    Seo, Byung-Kuk; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

    2012-12-01

    Natural feature-based approaches are still challenging for mobile applications (e.g., mobile augmented reality), because they are feasible only in limited environments such as highly textured and planar scenes/objects, and they need powerful mobile hardware for fast and reliable tracking. In many cases where conventional approaches are not effective, three-dimensional (3-D) knowledge of target scenes would be beneficial. We present a well-established framework for real-time visual tracking of less textured 3-D objects on mobile platforms. Our framework is based on model-based tracking that efficiently exploits partially known 3-D scene knowledge such as object models and a background's distinctive geometric or photometric knowledge. Moreover, we elaborate on implementation in order to make it suitable for real-time vision processing on mobile hardware. The performance of the framework is tested and evaluated on recent commercially available smartphones, and its feasibility is shown by real-time demonstrations.

  11. Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

    Science.gov (United States)

    Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

    2018-01-01

    Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

  12. A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation

    Directory of Open Access Journals (Sweden)

    Taesik Kim

    2017-02-01

    Full Text Available Tunnel construction workers face many dangers while working under dark conditions, with difficult access and egress, and many potential hazards. To enhance safety at tunnel construction sites, low latency tracking of mobile objects (e.g., heavy-duty equipment and construction workers is critical for managing the dangerous construction environment. Wireless Sensor Networks (WSNs are the basis for a widely used technology for monitoring the environment because of their energy-efficiency and scalability. However, their use involves an inherent point-to-point delay caused by duty cycling mechanisms that can result in a significant rise in the delivery latency for tracking mobile objects. To overcome this issue, we proposed a mobility-aware adaptive duty cycling mechanism for the WSNs based on object mobility. For the evaluation, we tested this mechanism for mobile object tracking at a tunnel excavation site. The evaluation results showed that the proposed mechanism could track mobile objects with low latency while they were moving, and could reduce energy consumption by increasing sleep time while the objects were immobile.

  13. Constraints on Multiple Object Tracking in Williams Syndrome: How Atypical Development Can Inform Theories of Visual Processing

    Science.gov (United States)

    Ferrara, Katrina; Hoffman, James E.; O'Hearn, Kirsten; Landau, Barbara

    2016-01-01

    The ability to track moving objects is a crucial skill for performance in everyday spatial tasks. The tracking mechanism depends on representation of moving items as coherent entities, which follow the spatiotemporal constraints of objects in the world. In the present experiment, participants tracked 1 to 4 targets in a display of 8 identical…

  14. Fast region-based object detection and tracking using correlation of features

    CSIR Research Space (South Africa)

    Senekal, F

    2010-11-01

    Full Text Available and track a target object (or objects) over a series of digital images. Visual target tracking can be accomplished by feature-based or region-based approaches. In feature-based approaches, interest points are calculated in a digital image, and a local...-time performance based on the computational power that is available on a specific platform. To further reduce the computational requirements, process- ing is restricted to the region of interest (ROI). The region of interest is provided as an input parameter...

  15. IMPLEMENTATION OF IMAGE PROCESSING ALGORITHMS AND GLVQ TO TRACK AN OBJECT USING AR.DRONE CAMERA

    Directory of Open Access Journals (Sweden)

    Muhammad Nanda Kurniawan

    2014-08-01

    Full Text Available Abstract In this research, Parrot AR.Drone as an Unmanned Aerial Vehicle (UAV was used to track an object from above. Development of this system utilized some functions from OpenCV library and Robot Operating System (ROS. Techniques that were implemented in the system are image processing al-gorithm (Centroid-Contour Distance (CCD, feature extraction algorithm (Principal Component Analysis (PCA and an artificial neural network algorithm (Generalized Learning Vector Quantization (GLVQ. The final result of this research is a program for AR.Drone to track a moving object on the floor in fast response time that is under 1 second.

  16. Moving Object Tracking and Its Application to an Indoor Dual-Robot Patrol

    Directory of Open Access Journals (Sweden)

    Cheng-Han Shih

    2016-11-01

    Full Text Available This paper presents an application of image tracking using an omnidirectional wheeled mobile robot (WMR. The objective of this study is to integrate image processing of hue, saturation, and lightness (HSL for fuzzy color space, and use mean shift tracking for object detection and a Radio Frequency Identification (RFID reader for confirming destination. Fuzzy control is applied to omnidirectional WMR for indoor patrol and intruder detection. Experimental results show that the proposed control scheme can make the WMRs perform indoor security service.

  17. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

    Science.gov (United States)

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

  18. Techniques for Efficient Tracking of Road-Network-Based Moving Objects

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

  19. Techniques for efficient road-network-based tracking of moving objects

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

  20. Amusement Park Physics in Panggon Lunjak (Trampoline: Analysis of Kinematics and Energy Use Video Tracking

    Directory of Open Access Journals (Sweden)

    Akhmad Yusuf

    2017-12-01

    Full Text Available Panggon Lunjak (trampoline is one of the famous amusement parks among the people that we can use as a recreation to enjoy a pleasant sensation. Without us knowing the amusement park that we often encounter is actually the result of the application of science and technology, especially in the field of physics, because it is amusement park for student of science is a real laboratory or the giant laboratory that we can use as a study of physics concepts and as research materials. Panggon Lunjak (trampoline motion is very close to the harmonic  motion where the resulting graph of the sinus so that on the graph will be in the analysis of  kinematics and energy phenomena, so that research on simple harmonic motion materials is not limited to research using pendulum motion and spring load motion which is often exemplified as research on harmonic motion. The purpose of this study is to analyze the physical aspects of Panggon Lunjak (trampoline motion based on the laws of physics on the concept of kinematics and analyze energy, Where the mechanical energy of addition between potential energy and kinetic energy (Conservation of energy. The analysis is done by using video tracking. Based on the analysis done using people as a mass, the result of the amplitude, the spring constant, angular frequency, and the law of conservation of energy on the Panggon Lunjak (trampoline is true. This analysis activity will be well used as a physics learning for students.

  1. Novel approach to automatically classify rat social behavior using a video tracking system.

    Science.gov (United States)

    Peters, Suzanne M; Pinter, Ilona J; Pothuizen, Helen H J; de Heer, Raymond C; van der Harst, Johanneke E; Spruijt, Berry M

    2016-08-01

    In the past, studies in behavioral neuroscience and drug development have relied on simple and quick readout parameters of animal behavior to assess treatment efficacy or to understand underlying brain mechanisms. The predominant use of classical behavioral tests has been repeatedly criticized during the last decades because of their poor reproducibility, poor translational value and the limited explanatory power in functional terms. We present a new method to monitor social behavior of rats using automated video tracking. The velocity of moving and the distance between two rats were plotted in frequency distributions. In addition, behavior was manually annotated and related to the automatically obtained parameters for a validated interpretation. Inter-individual distance in combination with velocity of movement provided specific behavioral classes, such as moving with high velocity when "in contact" or "in proximity". Human observations showed that these classes coincide with following (chasing) behavior. In addition, when animals are "in contact", but at low velocity, behaviors such as allogrooming and social investigation were observed. Also, low dose treatment with morphine and short isolation increased the time animals spent in contact or in proximity at high velocity. Current methods that involve the investigation of social rat behavior are mostly limited to short and relatively simple manual observations. A new and automated method for analyzing social behavior in a social interaction test is presented here and shows to be sensitive to drug treatment and housing conditions known to influence social behavior in rats. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. 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.

  3. 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.

  4. AUTONOMOUS DETECTION AND TRACKING OF AN OBJECT AUTONOMOUSLY USING AR.DRONE QUADCOPTER

    Directory of Open Access Journals (Sweden)

    Futuhal Arifin

    2014-08-01

    Full Text Available Abstract Nowadays, there are many robotic applications being developed to do tasks autonomously without any interactions or commands from human. Therefore, developing a system which enables a robot to do surveillance such as detection and tracking of a moving object will lead us to more advanced tasks carried out by robots in the future. AR.Drone is a flying robot platform that is able to take role as UAV (Unmanned Aerial Vehicle. Usage of computer vision algorithm such as Hough Transform makes it possible for such system to be implemented on AR.Drone. In this research, the developed algorithm is able to detect and track an object with certain shape and color. Then the algorithm is successfully implemented on AR.Drone quadcopter for detection and tracking.

  5. Multi-Model Estimation Based Moving Object Detection for Aerial Video

    Directory of Open Access Journals (Sweden)

    Yanning Zhang

    2015-04-01

    Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

  6. Object Tracking with LiDAR: Monitoring Taxiing and Landing Aircraft

    Directory of Open Access Journals (Sweden)

    Zoltan Koppanyi

    2018-02-01

    Full Text Available Mobile light detection and ranging (LiDAR sensors used in car navigation and robotics, such as the Velodyne’s VLP-16 and HDL-32E, allow for sensing the surroundings of the platform with high temporal resolution to detect obstacles, tracking objects and support path planning. This study investigates the feasibility of using LiDAR sensors for tracking taxiing or landing aircraft close to the ground to improve airport safety. A prototype system was developed and installed at an airfield to capture point clouds to monitor aircraft operations. One of the challenges of accurate object tracking using the Velodyne sensors is the relatively small vertical field of view (30°, 41.3° and angular resolution (1.33°, 2°, resulting in a small number of points of the tracked object. The point density decreases with the object–sensor distance, and is already sparse at a moderate range of 30–40 m. The paper introduces our model-based tracking algorithms, including volume minimization and cube trajectories, to address the optimal estimation of object motion and tracking based on sparse point clouds. Using a network of sensors, multiple tests were conducted at an airport to assess the performance of the demonstration system and the algorithms developed. The investigation was focused on monitoring small aircraft moving on runways and taxiways, and the results indicate less than 0.7 m/s and 17 cm velocity and positioning accuracy achieved, respectively. Overall, based on our findings, this technology is promising not only for aircraft monitoring but for airport applications.

  7. Spatio-Temporal Video Object Segmentation via Scale-Adaptive 3D Structure Tensor

    Directory of Open Access Journals (Sweden)

    Hai-Yun Wang

    2004-06-01

    Full Text Available To address multiple motions and deformable objects' motions encountered in existing region-based approaches, an automatic video object (VO segmentation methodology is proposed in this paper by exploiting the duality of image segmentation and motion estimation such that spatial and temporal information could assist each other to jointly yield much improved segmentation results. The key novelties of our method are (1 scale-adaptive tensor computation, (2 spatial-constrained motion mask generation without invoking dense motion-field computation, (3 rigidity analysis, (4 motion mask generation and selection, and (5 motion-constrained spatial region merging. Experimental results demonstrate that these novelties jointly contribute much more accurate VO segmentation both in spatial and temporal domains.

  8. Real-time tracking of visually attended objects in virtual environments and its application to LOD.

    Science.gov (United States)

    Lee, Sungkil; Kim, Gerard Jounghyun; Choi, Seungmoon

    2009-01-01

    This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.

  9. Algorithm of search and track of static and moving large-scale objects

    Directory of Open Access Journals (Sweden)

    Kalyaev Anatoly

    2017-01-01

    Full Text Available We suggest an algorithm for processing of a sequence, which contains images of search and track of static and moving large-scale objects. The possible software implementation of the algorithm, based on multithread CUDA processing, is suggested. Experimental analysis of the suggested algorithm implementation is performed.

  10. Development of an FPGA Based Embedded System for High Speed Object Tracking

    Directory of Open Access Journals (Sweden)

    Chandrashekar MATHAM

    2010-01-01

    Full Text Available This paper deals with the development and implementation of system on chip (SOC for object tracking using histograms. To acquire the distance and velocity information of moving vehicles such as military tanks, to identify the type of target within the range from 100 m to 3 km and to estimate the movements of the vehicle. The VHDL code is written for the above objectives and implemented using Xilinx’s VERTEX-4 based PCI card family.

  11. High-performance object tracking and fixation with an online neural estimator.

    Science.gov (United States)

    Kumarawadu, Sisil; Watanabe, Keigo; Lee, Tsu-Tian

    2007-02-01

    Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller-observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller-observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes.

  12. Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera

    Science.gov (United States)

    Dziri, Aziz; Duranton, Marc; Chapuis, Roland

    2016-07-01

    Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.

  13. Visual Tracking of Deformation and Classification of Non-Rigid Objects with Robot Hand Probing

    Directory of Open Access Journals (Sweden)

    Fei Hui

    2017-03-01

    Full Text Available Performing tasks with a robot hand often requires a complete knowledge of the manipulated object, including its properties (shape, rigidity, surface texture and its location in the environment, in order to ensure safe and efficient manipulation. While well-established procedures exist for the manipulation of rigid objects, as well as several approaches for the manipulation of linear or planar deformable objects such as ropes or fabric, research addressing the characterization of deformable objects occupying a volume remains relatively limited. The paper proposes an approach for tracking the deformation of non-rigid objects under robot hand manipulation using RGB-D data. The purpose is to automatically classify deformable objects as rigid, elastic, plastic, or elasto-plastic, based on the material they are made of, and to support recognition of the category of such objects through a robotic probing process in order to enhance manipulation capabilities. The proposed approach combines advantageously classical color and depth image processing techniques and proposes a novel combination of the fast level set method with a log-polar mapping of the visual data to robustly detect and track the contour of a deformable object in a RGB-D data stream. Dynamic time warping is employed to characterize the object properties independently from the varying length of the tracked contour as the object deforms. The proposed solution achieves a classification rate over all categories of material of up to 98.3%. When integrated in the control loop of a robot hand, it can contribute to ensure stable grasp, and safe manipulation capability that will preserve the physical integrity of the object.

  14. Multisensory Tracking of Objects in Darkness: Capture of Positive Afterimages by the Tactile and Proprioceptive Senses.

    Directory of Open Access Journals (Sweden)

    Brian W Stone

    Full Text Available This paper reports on three experiments investigating the contribution of different sensory modalities to the tracking of objects moved in total darkness. Participants sitting in the dark were exposed to a brief, bright flash which reliably induced a positive visual afterimage of the scene so illuminated. If the participants subsequently move their hand in the darkness, the visual afterimage of that hand fades or disappears; this is presumably due to conflict between the illusory visual afterimage (of the hand in its original location and other information (e.g., proprioceptive from a general mechanism for tracking body parts. This afterimage disappearance effect also occurs for held objects which are moved in the dark, and some have argued that this represents a case of body schema extension, i.e. the rapid incorporation of held external objects into the body schema. We demonstrate that the phenomenon is not limited to held objects and occurs in conditions where incorporation into the body schema is unlikely. Instead, we propose that the disappearance of afterimages of objects moved in darkness comes from a general mechanism for object tracking which integrates input from multiple sensory systems. This mechanism need not be limited to tracking body parts, and thus we need not invoke body schema extension to explain the afterimage disappearance. In this series of experiments, we test whether auditory feedback of object movement can induce afterimage disappearance, demonstrate that the disappearance effect scales with the magnitude of proprioceptive feedback, and show that tactile feedback alone is sufficient for the effect. Together, these data demonstrate that the visual percept of a positive afterimage is constructed not just from visual input of the scene when light reaches the eyes, but in conjunction with input from multiple other senses.

  15. Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

    Directory of Open Access Journals (Sweden)

    Zhijun Xie

    2014-10-01

    Full Text Available Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT. In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

  16. Hard Ware Implementation of Diamond Search Algorithm for Motion Estimation and Object Tracking

    International Nuclear Information System (INIS)

    Hashimaa, S.M.; Mahmoud, I.I.; Elazm, A.A.

    2009-01-01

    Object tracking is very important task in computer vision. Fast search algorithms emerged as important search technique to achieve real time tracking results. To enhance the performance of these algorithms, we advocate the hardware implementation of such algorithms. Diamond search block matching motion estimation has been proposed recently to reduce the complexity of motion estimation. In this paper we selected the diamond search algorithm (DS) for implementation using FPGA. This is due to its fundamental role in all fast search patterns. The proposed architecture is simulated and synthesized using Xilinix and modelsim soft wares. The results agree with the algorithm implementation in Matlab environment.

  17. Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

    Science.gov (United States)

    Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

    2015-04-01

    In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

  18. Modified SURF Algorithm Implementation on FPGA For Real-Time Object Tracking

    Directory of Open Access Journals (Sweden)

    Tomyslav Sledevič

    2013-05-01

    Full Text Available The paper describes the FPGA-based implementation of the modified speeded-up robust features (SURF algorithm. FPGA was selected for parallel process implementation using VHDL to ensure features extraction in real-time. A sliding 84×84 size window was used to store integral pixels and accelerate Hessian determinant calculation, orientation assignment and descriptor estimation. The local extreme searching was used to find point of interest in 8 scales. The simplified descriptor and orientation vector were calculated in parallel in 6 scales. The algorithm was investigated by tracking marker and drawing a plane or cube. All parts of algorithm worked on 25 MHz clock. The video stream was generated using 60 fps and 640×480 pixel camera.Article in Lithuanian

  19. Modeling 3D Unknown object by Range Finder and Video Camera ...

    African Journals Online (AJOL)

    real world); proprioceptive and exteroceptive sensors allowing the recreating of the 3D geometric database of an environment (virtual world). The virtual world is projected onto a video display terminal (VDT). Computer-generated and video ...

  20. 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.

  1. Contralateral delay activity tracks object identity information in visual short term memory.

    Science.gov (United States)

    Gao, Zaifeng; Xu, Xiaotian; Chen, Zhibo; Yin, Jun; Shen, Mowei; Shui, Rende

    2011-08-11

    Previous studies suggested that ERP component contralateral delay activity (CDA) tracks the number of objects containing identity information stored in visual short term memory (VSTM). Later MEG and fMRI studies implied that its neural source lays in superior IPS. However, since the memorized stimuli in previous studies were displayed in distinct spatial locations, hence possibly CDA tracks the object-location information instead. Moreover, a recent study implied the activation in superior IPS reflected the location load. The current research thus explored whether CDA tracks the object-location load or the object-identity load, and its neural sources. Participants were asked to remember one color, four identical colors or four distinct colors. The four-identical-color condition was the critical one because it contains the same amount of identity information as that of one color while the same amount of location information as that of four distinct colors. To ensure the participants indeed selected four colors in the four-identical-color condition, we also split the participants into two groups (low- vs. high-capacity), analyzed late positive component (LPC) in the prefrontal area, and collected participant's subjective-report. Our results revealed that most of the participants selected four identical colors. Moreover, regardless of capacity-group, there was no difference on CDA between one color and four identical colors yet both were lower than 4 distinct colors. Besides, the source of CDA was located in the superior parietal lobule, which is very close to the superior IPS. These results support the statement that CDA tracks the object identity information in VSTM. Copyright © 2011 Elsevier B.V. All rights reserved.

  2. Additivity of Feature-based and Symmetry-based Grouping Effects in Multiple Object Tracking

    Directory of Open Access Journals (Sweden)

    Chundi eWang

    2016-05-01

    Full Text Available Multiple object tracking (MOT is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the laws of perceptual organization proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. Additive effect refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The where and what pathways might have played an important role in the additive grouping effect.

  3. Assessment of acute sublethal effects of clothianidin on motor function of honeybee workers using video-tracking analysis.

    Science.gov (United States)

    Alkassab, Abdulrahim T; Kirchner, Wolfgang H

    2018-01-01

    Sublethal impacts of pesticides on the locomotor activity might occur to different degrees and could escape visual observation. Therefore, our objective is the utilization of video-tracking to quantify how the acute oral exposure to different doses (0.1-2ng/bee) of the neonicotinoid "clothianidin" influences the locomotor activity of honeybees in a time course experiment. The total distance moved, resting time as well as the duration and frequency of bouts of laying upside down are measured. Our results show that bees exposed to acute sublethal doses of clothianidin exhibit a significant increase in the total distance moved after 30 and 60min of the treatment at the highest dose (2ng/bee). Nevertheless, a reduction of the total distance is observed at this dose 90min post-treatment compared to the distance of the same group after 30min, where the treated bees show an arched abdomen and start to lose their postural control. The treated bees with 1ng clothianidin show a significant increase in total distance moved over the experimental period. Moreover, a reduction in the resting time and increase of the duration and frequency of bouts of laying upside down at these doses are found. Furthermore, significant effects on the tested parameters are observed at the dose (0.5ng/bee) first at 60min post-treatment compared to untreated bees. The lowest dose (0.1ng/bee) has non-significant effects on the motor activity of honeybees compared to untreated bees over the experimental period. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Development of Adaptive Tilt Tracker that Utilizes QUAD-cell Detector to Track Extended Objects

    Science.gov (United States)

    2014-03-17

    tracked low Earth orbit (LEO) object and atmospheric seeing govern spot characteristics. Unlike static natural or laser guide stars, a LEO object’s...image spot characteristics .......................................................... 101 56. Response for non-adaptive tilt tracker with α equal to...applications toward natural and laser guide stars. The system was innovative and is a relevant forerunner to the tracker proposed in this research. The

  5. Eye movements in Multiple Object Tracking systematically lagging behind the scene content

    Czech Academy of Sciences Publication Activity Database

    Lukavský, Jiří

    2013-01-01

    Roč. 42, Suppl (2013), s. 42-43 ISSN 0301-0066. [36th European Conference on Visual Perception . 25.08.2013.-29.08.2013, Brémy] R&D Projects: GA ČR GA13-28709S Institutional support: RVO:68081740 Keywords : eye movements * attention * multiple object tracking Subject RIV: AN - Psychology http://www. perception web.com/abstract.cgi?id=v130146

  6. Tutorial on Using LISP Object-Oriented Programming for Blackboards: Solving the Radar Tracking Problem

    Science.gov (United States)

    1989-08-01

    1977. Pp. 1-229. 25. V. Lesser and R. Fennell. "Parallelism in Aritificial Intelligence Problem Solving: A Case Study of Hearsay II," IEEE Transactions...artificial intelligence architecture used to solve the radar tracking problem. The research described was performed at Purdue University during long...TION 1 COSA TI CODES 18 SUBJECT TERMS in ,,tnu; . ’ .’ , .., ,’ a-, ,’£ ,i-, ,4’o4,, nun br) ,LD I GROUP SUB.GROu P Artificial intelligence Object

  7. Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

    Directory of Open Access Journals (Sweden)

    Ziho Kang

    2016-01-01

    Full Text Available Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1 participants interrogate dynamic multielement objects that can overlap on the display and (2 visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1 developing dynamic areas of interests (AOIs in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2 introducing the concept of AOI gap tolerance (AGT that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3 finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC operations where air traffic controller specialists (ATCSs interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

  8. Altered defaecatory behaviour and faecal incontinence in a video-tracked animal model of pudendal neuropathy.

    Science.gov (United States)

    Devane, L A; Lucking, E; Evers, J; Buffini, M; Scott, S M; Knowles, C H; O'Connell, P R; Jones, J F X

    2017-05-01

    The aim was to develop a behavioural animal model of faecal continence and assess the effect of retro-uterine balloon inflation (RBI) injury. RBI in the rat causes pudendal neuropathy, a risk factor for obstetric related faecal incontinence in humans. Video-tracking of healthy rats (n = 12) in a cage containing a latrine box was used to monitor their defaecatory behaviour index (DBI) over 2 weeks. The DBI (range 0-1) was devised by dividing the defaecation rate (pellets per hour) outside the latrine by that of the whole cage. A score of 0 indicates all pellets were deposited in the latrine. Subsequently, the effects of RBI (n = 19), sham surgery (n = 4) and colostomy (n = 2) were determined by monitoring the DBI for 2 weeks preoperatively and 3 weeks postoperatively. The DBI for healthy rats was 0.1 ± 0.03 with no significant change over 2 weeks (P = 0.71). In the RBI group, 13 of 19 rats (68%) showed no significant change in DBI postoperatively (0.08 ±  -0.05 vs 0.11 ±  -0.07) while in six rats the DBI increased from 0.16 ±  -0.09 to 0.46 ± 0.23. The negative control, sham surgery, did not significantly affect the DBI (0.09 ± 0.06 vs 0.08 ± 0.04, P = 0.14). The positive control, colostomy, increased the DBI from 0.26 ± 0.03 to 0.86 ± 0.08. This is the first study showing a quantifiable change in defaecatory behaviour following injury in an animal model. This model of pudendal neuropathy affects continence in 32% of rats and provides a basis for research on interventions for incontinence. Colorectal Disease © 2017 The Association of Coloproctology of Great Britain and Ireland.

  9. Low cost, robust and real time system for detecting and tracking moving objects to automate cargo handling in port terminals

    NARCIS (Netherlands)

    Vaquero, V.; Repiso, E.; Sanfeliu, A.; Vissers, J.; Kwakkernaat, M.

    2016-01-01

    The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm

  10. Developmental Profiles for Multiple Object Tracking and Spatial Memory: Typically Developing Preschoolers and People with Williams Syndrome

    Science.gov (United States)

    O'Hearn, Kirsten; Hoffman, James E.; Landau, Barbara

    2010-01-01

    The ability to track moving objects, a crucial skill for mature performance on everyday spatial tasks, has been hypothesized to require a specialized mechanism that may be available in infancy (i.e. indexes). Consistent with the idea of specialization, our previous work showed that object tracking was more impaired than a matched spatial memory…

  11. A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection

    Directory of Open Access Journals (Sweden)

    Stéphanie Jehan-Besson

    2002-06-01

    Full Text Available We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based active contours. First, we introduce a very full general framework for region-based active contours with a new Eulerian method to compute the evolution equation of the active contour from a criterion including both region-based and boundary-based terms. This framework can be easily adapted to various applications, thanks to the introduction of functions named descriptors of the different regions. With this new Eulerian method based on shape optimization principles, we can easily take into account the case of descriptors depending upon features globally attached to the regions. Second, we propose a 3-step algorithm for detection of moving objects, with a static or a mobile camera, using region-based active contours. The basic idea is to hierarchically associate temporal and spatial information. The active contour evolves with successively three sets of descriptors: a temporal one, and then two spatial ones. The third spatial descriptor takes advantage of the segmentation of the image in intensity homogeneous regions. User interaction is reduced to the choice of a few parameters at the beginning of the process. Some experimental results are supplied.

  12. Enhanced object-based tracking algorithm for convective rain storms and cells

    Science.gov (United States)

    Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

    2018-03-01

    This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

  13. Object Tracking Vision System for Mapping the UCN τ Apparatus Volume

    Science.gov (United States)

    Lumb, Rowan; UCNtau Collaboration

    2016-09-01

    The UCN τ collaboration has an immediate goal to measure the lifetime of the free neutron to within 0.1%, i.e. about 1 s. The UCN τ apparatus is a magneto-gravitational ``bottle'' system. This system holds low energy, or ultracold, neutrons in the apparatus with the constraint of gravity, and keeps these low energy neutrons from interacting with the bottle via a strong 1 T surface magnetic field created by a bowl-shaped array of permanent magnets. The apparatus is wrapped with energized coils to supply a magnetic field throughout the ''bottle'' volume to prevent depolarization of the neutrons. An object-tracking stereo-vision system will be presented that precisely tracks a Hall probe and allows a mapping of the magnetic field throughout the volume of the UCN τ bottle. The stereo-vision system utilizes two cameras and open source openCV software to track an object's 3-d position in space in real time. The desired resolution is +/-1 mm resolution along each axis. The vision system is being used as part of an even larger system to map the magnetic field of the UCN τ apparatus and expose any possible systematic effects due to field cancellation or low field points which could allow neutrons to depolarize and possibly escape from the apparatus undetected. Tennessee Technological University.

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

    Science.gov (United States)

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

    2018-04-23

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

  15. 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.

  16. Position Affects Performance in Multiple-Object Tracking in Rugby Union Players

    Directory of Open Access Journals (Sweden)

    Andrés Martín

    2017-09-01

    Full Text Available We report an experiment that examines the performance of rugby union players and a control group composed of graduate student with no sport experience, in a multiple-object tracking task. It compares the ability of 86 high level rugby union players grouped as Backs and Forwards and the control group, to track a subset of randomly moving targets amongst the same number of distractors. Several difficulties were included in the experimental design in order to evaluate possible interactions between the relevant variables. Results show that the performance of the Backs is better than that of the other groups, but the occurrence of interactions precludes an isolated groups analysis. We interpret the results within the framework of visual attention and discuss both, the implications of our results and the practical consequences.

  17. 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

  18. Image-based tracking system for vibration measurement of a rotating object using a laser scanning vibrometer

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dongkyu, E-mail: akein@gist.ac.kr; Khalil, Hossam; Jo, Youngjoon; Park, Kyihwan, E-mail: khpark@gist.ac.kr [School of Mechatronics, Gwangju Institute of Science and Technology, Buk-gu, Gwangju, South Korea, 500-712 (Korea, Republic of)

    2016-06-28

    An image-based tracking system using laser scanning vibrometer is developed for vibration measurement of a rotating object. The proposed system unlike a conventional one can be used where the position or velocity sensor such as an encoder cannot be attached to an object. An image processing algorithm is introduced to detect a landmark and laser beam based on their colors. Then, through using feedback control system, the laser beam can track a rotating object.

  19. A Dynamic Reconfigurable Hardware/Software Architecture for Object Tracking in Video Streams

    Directory of Open Access Journals (Sweden)

    Christophe Bobda

    2006-10-01

    Full Text Available This paper presents the design and implementation of a feature tracker on an embedded reconfigurable hardware system. Contrary to other works, the focus here is on the efficient hardware/software partitioning of the feature tracker algorithm, a viable data flow management, as well as an efficient use of memory and processor features. The implementation is done on a Xilinx Spartan 3 evaluation board and the results provided show the superiority of our implementation compared to the other works.

  20. A Dynamic Reconfigurable Hardware/Software Architecture for Object Tracking in Video Streams

    Directory of Open Access Journals (Sweden)

    Mühlbauer Felix

    2006-01-01

    Full Text Available This paper presents the design and implementation of a feature tracker on an embedded reconfigurable hardware system. Contrary to other works, the focus here is on the efficient hardware/software partitioning of the feature tracker algorithm, a viable data flow management, as well as an efficient use of memory and processor features. The implementation is done on a Xilinx Spartan 3 evaluation board and the results provided show the superiority of our implementation compared to the other works.

  1. More performance results and implementation of an object oriented track reconstruction model in different OO frameworks

    International Nuclear Information System (INIS)

    Gaines, Irwin; Qian Sijin

    2001-01-01

    This is an update of the report about an Object Oriented (OO) track reconstruction model, which was presented in the previous AIHENP'99 at Crete, Greece. The OO model for the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. It has been coded in the C++ programming language and successfully implemented into a few different OO computing environments of the CMS and ATLAS experiments at the future Large Hadron Collider at CERN. We shall report: (1) more performance result: (2) implementing the OO model into the new SW OO framework 'Athena' of ATLAS experiment and some upgrades of the OO model itself

  2. Implementation of an object oriented track reconstruction model into multiple LHC experiments*

    Science.gov (United States)

    Gaines, Irwin; Gonzalez, Saul; Qian, Sijin

    2001-10-01

    An Object Oriented (OO) model (Gaines et al., 1996; 1997; Gaines and Qian, 1998; 1999) for track reconstruction by the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. The model has been coded in the C++ programming language and has been successfully implemented into the OO computing environments of both the CMS (1994) and ATLAS (1994) experiments at the future Large Hadron Collider (LHC) at CERN. We shall report: how the OO model was adapted, with largely the same code, to different scenarios and serves the different reconstruction aims in different experiments (i.e. the level-2 trigger software for ATLAS and the offline software for CMS); how the OO model has been incorporated into different OO environments with a similar integration structure (demonstrating the ease of re-use of OO program); what are the OO model's performance, including execution time, memory usage, track finding efficiency and ghost rate, etc.; and additional physics performance based on use of the OO tracking model. We shall also mention the experience and lessons learned from the implementation of the OO model into the general OO software framework of the experiments. In summary, our practice shows that the OO technology really makes the software development and the integration issues straightforward and convenient; this may be particularly beneficial for the general non-computer-professional physicists.

  3. Object tracking with robotic total stations: Current technologies and improvements based on image data

    Science.gov (United States)

    Ehrhart, Matthias; Lienhart, Werner

    2017-09-01

    The importance of automated prism tracking is increasingly triggered by the rising automation of total station measurements in machine control, monitoring and one-person operation. In this article we summarize and explain the different techniques that are used to coarsely search a prism, to precisely aim at a prism, and to identify whether the correct prism is tracked. Along with the state-of-the-art review, we discuss and experimentally evaluate possible improvements based on the image data of an additional wide-angle camera which is available for many total stations today. In cases in which the total station's fine aiming module loses the prism, the tracked object may still be visible to the wide-angle camera because of its larger field of view. The theodolite angles towards the target can then be derived from its image coordinates which facilitates a fast reacquisition of the prism. In experimental measurements we demonstrate that our image-based approach for the coarse target search is 4 to 10-times faster than conventional approaches.

  4. Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

    Directory of Open Access Journals (Sweden)

    Siavash Hosseinyalamdary

    2015-07-01

    Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

  5. Using cloud computing technologies in IP-video surveillance systems with the function of 3d-object modelling

    Directory of Open Access Journals (Sweden)

    Zhigalov Kirill

    2018-01-01

    Full Text Available This article is devoted to the integration of cloud technology functions into 3D IP video surveil-lance systems in order to conduct further video Analytics, incoming real-time data, as well as stored video materials on the server in the «cloud». The main attention is devoted to «cloud technologies» usage optimizing the process of recognition of the desired object by increasing the criteria of flexibility and scalability of the system. Transferring image load from the client to the cloud server, to the virtual part of the system. The development of the issues considered in the article in terms of data analysis, which will significantly improve the effectiveness of the implementation of special tasks facing special units.

  6. EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

    Full Text Available Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU, which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA, which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05.

  7. Rotation Matrix to Operate a Robot Manipulator for 2D Analog Tracking Objects Using Electrooculography

    Directory of Open Access Journals (Sweden)

    Muhammad Ilhamdi Rusydi

    2014-07-01

    Full Text Available Performing some special tasks using electrooculography (EOG in daily activities is being developed in various areas. In this paper, simple rotation matrixes were introduced to help the operator move a 2-DoF planar robot manipulator. The EOG sensor, NF 5201, has two output channels (Ch1 and Ch2, as well as one ground channel and one reference channel. The robot movement was the indicator that this system could follow gaze motion based on EOG. Operators gazed into five training target points each in the horizontal and vertical line as the preliminary experiments, which were based on directions, distances and the areas of gaze motions. This was done to get the relationships between EOG and gaze motion distance for four directions, which were up, down, right and left. The maximum angle for the horizontal was 46°, while it was 38° for the vertical. Rotation matrixes for the horizontal and vertical signals were combined, so as to diagonally track objects. To verify, the errors between actual and desired target positions were calculated using the Euclidian distance. This test section had 20 random target points. The result indicated that this system could track an object with average angle errors of 3.31° in the x-axis and 3.58° in the y-axis.

  8. RAPTOR-scan: Identifying and Tracking Objects Through Thousands of Sky Images

    International Nuclear Information System (INIS)

    Davidoff, Sherri; Wozniak, Przemyslaw

    2004-01-01

    The RAPTOR-scan system mines data for optical transients associated with gamma-ray bursts and is used to create a catalog for the RAPTOR telescope system. RAPTOR-scan can detect and track individual astronomical objects across data sets containing millions of observed points.Accurately identifying a real object over many optical images (clustering the individual appearances) is necessary in order to analyze object light curves. To achieve this, RAPTOR telescope observations are sent in real time to a database. Each morning, a program based on the DBSCAN algorithm clusters the observations and labels each one with an object identifier. Once clustering is complete, the analysis program may be used to query the database and produce light curves, maps of the sky field, or other informative displays.Although RAPTOR-scan was designed for the RAPTOR optical telescope system, it is a general tool designed to identify objects in a collection of astronomical data and facilitate quick data analysis. RAPTOR-scan will be released as free software under the GNU General Public License

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

    Science.gov (United States)

    Bae, Seung-Hwan; Yoon, Kuk-Jin

    2018-03-01

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

  10. An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

    Science.gov (United States)

    Raihan A. V, Dilshad; Chakravorty, Suman

    2018-03-01

    Optimal and consistent estimation of the state of space objects is pivotal to surveillance and tracking applications. However, probabilistic estimation of space objects is made difficult by the non-Gaussianity and nonlinearity associated with orbital mechanics. In this paper, we present an unscented Kalman-particle hybrid filtering framework for recursive Bayesian estimation of space objects. The hybrid filtering scheme is designed to provide accurate and consistent estimates when measurements are sparse without incurring a large computational cost. It employs an unscented Kalman filter (UKF) for estimation when measurements are available. When the target is outside the field of view (FOV) of the sensor, it updates the state probability density function (PDF) via a sequential Monte Carlo method. The hybrid filter addresses the problem of particle depletion through a suitably designed filter transition scheme. To assess the performance of the hybrid filtering approach, we consider two test cases of space objects that are assumed to undergo full three dimensional orbital motion under the effects of J 2 and atmospheric drag perturbations. It is demonstrated that the hybrid filters can furnish fast, accurate and consistent estimates outperforming standard UKF and particle filter (PF) implementations.

  11. A System to Generate SignWriting for Video Tracks Enhancing Accessibility of Deaf People

    OpenAIRE

    Elena Verdú; Cristina Pelayo G-Bustelo; Ángeles Martínez Sánchez; Rubén Gonzalez-Crespo

    2017-01-01

    Video content has increased much on the Internet during last years. In spite of the efforts of different organizations and governments to increase the accessibility of websites, most multimedia content on the Internet is not accessible. This paper describes a system that contributes to make multimedia content more accessible on the Web, by automatically translating subtitles in oral language to Sign Writing, a way of writing Sign Language. This system extends the functionality of a general we...

  12. A System to Generate SignWriting for Video Tracks Enhancing Accessibility of Deaf People

    Directory of Open Access Journals (Sweden)

    Elena Verdú

    2017-12-01

    Full Text Available Video content has increased much on the Internet during last years. In spite of the efforts of different organizations and governments to increase the accessibility of websites, most multimedia content on the Internet is not accessible. This paper describes a system that contributes to make multimedia content more accessible on the Web, by automatically translating subtitles in oral language to SignWriting, a way of writing Sign Language. This system extends the functionality of a general web platform that can provide accessible web content for different needs. This platform has a core component that automatically converts any web page to a web page compliant with level AA of WAI guidelines. Around this core component, different adapters complete the conversion according to the needs of specific users. One adapter is the Deaf People Accessibility Adapter, which provides accessible web content for the Deaf, based on SignWritting. Functionality of this adapter has been extended with the video subtitle translator system. A first prototype of this system has been tested through different methods including usability and accessibility tests and results show that this tool can enhance the accessibility of video content available on the Web for Deaf people.

  13. Studying the movement behaviour of benthic macroinvertebrates with automated video tracking

    NARCIS (Netherlands)

    Augusiak, J.A.; Brink, van den P.J.

    2015-01-01

    Quantifying and understanding movement is critical for a wide range of questions in basic and applied ecology. Movement ecology is also fostered by technological advances that allow automated tracking for a wide range of animal species. However, for aquatic macroinvertebrates, such detailed methods

  14. X-ray microscopy study of track membranes and biological objects

    International Nuclear Information System (INIS)

    Artioukov, I.A.; Levashov, V.E.; Struk, I.I.; Vinogradov, A.V.; Asadchikov, V.E.; Mchedlishvili, B.V.; Postnov, A.A.; Vilensky, A.I.; Zagorsky, D.L.; Gulimova, V.I.; Saveliev, S.V.; Kurohtin, A.N.; Popov, A.V.

    2000-01-01

    The development of two types of X-ray microscopy applying to the organic objects investigation (biological samples and polymer matrix) is reported. Polymer track membranes were investigated using Schwarzchild X-ray microscope with 20 nm wavelength. Pore diameters down to 0.2 μm were clearly imaged. Contact X-ray microscopy at 0.229 nm wavelength was used to obtain clear images of inner structure of native biological samples. High contrast together with the high resolution (about 2-3 μm) allowed us to use this method for quantitative analysis of demineralization process taking place in the skeleton of amphibious after several weeks of weightlessness on biosputnik board

  15. Robot soccer anywhere: achieving persistent autonomous navigation, mapping, and object vision tracking in dynamic environments

    Science.gov (United States)

    Dragone, Mauro; O'Donoghue, Ruadhan; Leonard, John J.; O'Hare, Gregory; Duffy, Brian; Patrikalakis, Andrew; Leederkerken, Jacques

    2005-06-01

    The paper describes an ongoing effort to enable autonomous mobile robots to play soccer in unstructured, everyday environments. Unlike conventional robot soccer competitions that are usually held on purpose-built robot soccer "fields", in our work we seek to develop the capability for robots to demonstrate aspects of soccer-playing in more diverse environments, such as schools, hospitals, or shopping malls, with static obstacles (furniture) and dynamic natural obstacles (people). This problem of "Soccer Anywhere" presents numerous research challenges including: (1) Simultaneous Localization and Mapping (SLAM) in dynamic, unstructured environments, (2) software control architectures for decentralized, distributed control of mobile agents, (3) integration of vision-based object tracking with dynamic control, and (4) social interaction with human participants. In addition to the intrinsic research merit of these topics, we believe that this capability would prove useful for outreach activities, in demonstrating robotics technology to primary and secondary school students, to motivate them to pursue careers in science and engineering.

  16. Does playing a sports active video game improve object control skills of children with autism spectrum disorder?

    OpenAIRE

    Edwards, Jacqueline; Jeffrey, Sarah; May, Tamara; Rinehart, Nicole J.; Barnett, Lisa M.

    2017-01-01

    Background: Active video games (AVGs) encourage whole body movements to interact or control the gaming system, allowing the opportunity for skill development. Children with autism spectrum disorder (ASD) show decreased fundamental movement skills in comparison with their typically developing (TD) peers and might benefit from this approach. This pilot study investigates whether playing sports AVGs can increase the actual and perceived object control (OC) skills of 11 children with ASD aged 6–1...

  17. Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

    Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

  18. State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

    Directory of Open Access Journals (Sweden)

    Moritz Koplin

    2013-04-01

    Full Text Available Most state-of-the-art driver assistance systems cannot guarantee that real-time images of object states are updated within a given time interval, because the object state observations are typically sampled by uncontrolled sensors and transmitted via an indeterministic bus system such as CAN. To overcome this shortcoming, a paradigm shift toward time-triggered advanced driver assistance systems based on a deterministic bus system, such as FlexRay, is under discussion. In order to prove the feasibility of this paradigm shift, this paper develops different models of a state-of-the-art and a time-triggered advanced driver assistance system based on multi-sensor object tracking and compares them with regard to their mean performance. The results show that while the state-of-the-art model is advantageous in scenarios with low process noise, it is outmatched by the time-triggered model in the case of high process noise, i.e., in complex situations with high dynamic.

  19. 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.

  20. Robust and efficient fiducial tracking for augmented reality in HD-laparoscopic video streams

    Science.gov (United States)

    Mueller, M.; Groch, A.; Baumhauer, M.; Maier-Hein, L.; Teber, D.; Rassweiler, J.; Meinzer, H.-P.; Wegner, In.

    2012-02-01

    Augmented Reality (AR) is a convenient way of porting information from medical images into the surgical field of view and can deliver valuable assistance to the surgeon, especially in laparoscopic procedures. In addition, high definition (HD) laparoscopic video devices are a great improvement over the previously used low resolution equipment. However, in AR applications that rely on real-time detection of fiducials from video streams, the demand for efficient image processing has increased due to the introduction of HD devices. We present an algorithm based on the well-known Conditional Density Propagation (CONDENSATION) algorithm which can satisfy these new demands. By incorporating a prediction around an already existing and robust segmentation algorithm, we can speed up the whole procedure while leaving the robustness of the fiducial segmentation untouched. For evaluation purposes we tested the algorithm on recordings from real interventions, allowing for a meaningful interpretation of the results. Our results show that we can accelerate the segmentation by a factor of 3.5 on average. Moreover, the prediction information can be used to compensate for fiducials that are temporarily occluded or out of scope, providing greater stability.

  1. VISDTA: A video imaging system for detection, tracking, and assessment: Prototype development and concept demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Pritchard, D.A.

    1987-05-01

    It has been demonstrated that thermal imagers are an effective surveillance and assessment tool for security applications because: (1) they work day or night due to their sensitivity to thermal signatures; (2) penetrability through fog, rain, dust, etc., is better than human eyes; (3) short or long range operation is possible with various optics; and (4) they are strictly passive devices providing visible imagery which is readily interpreted by the operator with little training. Unfortunately, most thermal imagers also require the setup of a tripod, connection of batteries, cables, display, etc. When this is accomplished, the operator must manually move the camera back and forth searching for signs of aggressor activity. VISDTA is designed to provide automatic panning, and in a sense, ''watch'' the imagery in place of the operator. The idea behind the development of VISDTA is to provide a small, portable, rugged system to automatically scan areas and detect targets by computer processing of images. It would use a thermal imager and possibly an intensified day/night TV camera, a pan/ tilt mount, and a computer for system control. If mounted on a dedicated vehicle or on a tower, VISDTA will perform video motion detection functions on incoming video imagery, and automatically scan predefined patterns in search of abnormal conditions which may indicate attempted intrusions into the field-of-regard. In that respect, VISDTA is capable of improving the ability of security forces to maintain security of a given area of interest by augmenting present techniques and reducing operator fatigue.

  2. Contactless measurement of muscles fatigue by tracking facial feature points in a video

    DEFF Research Database (Denmark)

    Irani, Ramin; Nasrollahi, Kamal; Moeslund, Thomas B.

    2014-01-01

    their exercises when the level of the fatigue might be dangerous for the patients. The current technology for measuring tiredness, like Electromyography (EMG), requires installing some sensors on the body. In some applications, like remote patient monitoring, this however might not be possible. To deal...... with such cases, in this paper we present a contactless method based on computer vision techniques to measure tiredness by detecting, tracking, and analyzing some facial feature points during the exercise. Experimental results on several test subjects and comparing them against ground truth data show...... that the proposed system can properly find the temporal point of tiredness of the muscles when the test subjects are doing physical exercises....

  3. Photostable bipolar fluorescent probe for video tracking plasma membranes related cellular processes.

    Science.gov (United States)

    Zhang, Xinfu; Wang, Chao; Jin, Liji; Han, Zhuo; Xiao, Yi

    2014-08-13

    Plasma membranes can sense the stimulations and transmit the signals from extracellular environment and then make further responses through changes in locations, shapes or morphologies. Common fluorescent membrane markers are not well suited for long time tracking due to their shorter retention time inside plasma membranes and/or their lower photostability. To this end, we develop a new bipolar marker, Mem-SQAC, which can stably insert into plasma membranes of different cells and exhibits a long retention time over 30 min. Mem-SQAC also inherits excellent photostability from the BODIPY dye family. Large two-photon absorption cross sections and long wavelength fluorescence emissions further enhance the competitiveness of Mem-SQAC as a membrane marker. By using Mem-SQAC, significant morphological changes of plasma membranes have been monitored during heavy metal poisoning and drug induced apoptosis of MCF-7 cells; the change tendencies are so distinctly different from each other that they can be used as indicators to distinguish different cell injuries. Further on, the complete processes of endocytosis toward Staphylococcus aureus and Escherichia coli by RAW 264.7 cells have been dynamically tracked. It is discovered that plasma membranes take quite different actions in response to the two bacteria, information unavailable in previous research reports.

  4. A C++ object-oriented toolkit for track finding with k-dimensional hits

    International Nuclear Information System (INIS)

    Uiterwijk, J.W.E.; Panman, J.; Vyver, B. van de

    2006-01-01

    A library is described for the recognition of tracks in a set of hits. The hits are assumed to be k-dimensional points (k-d), with k>=1, of which a subset can be grouped into tracks by using short-range correlations. A connection graph between the hits is created by sorting the hits first in k-d space using one of the developed, fast, k-space containers. The track-finding algorithm considers any connection between two hits as a possible track seed and grows these seeds into longer track segments using a modified depth-first search of the connection graph. All hit-acceptance decisions are called via abstract methods of an acceptance criterion class which isolates the library from the application's hit and track model. An application is tuned for a particular tracking environment by creating a concrete implementation for the hit and track acceptance calculations. The implementer is free to trade tracking time for acceptance complexity (influencing efficiency) depending on the requirements of the particular application. Results for simulated data show that the track finding is both efficient and fast even for high noise environments

  5. Objective assessment of the contribution of dental esthetics and facial attractiveness in men via eye tracking.

    Science.gov (United States)

    Baker, Robin S; Fields, Henry W; Beck, F Michael; Firestone, Allen R; Rosenstiel, Stephen F

    2018-04-01

    Recently, greater emphasis has been placed on smile esthetics in dentistry. Eye tracking has been used to objectively evaluate attention to the dentition (mouth) in female models with different levels of dental esthetics quantified by the aesthetic component of the Index of Orthodontic Treatment Need (IOTN). This has not been accomplished in men. Our objective was to determine the visual attention to the mouth in men with different levels of dental esthetics (IOTN levels) and background facial attractiveness, for both male and female raters, using eye tracking. Facial images of men rated as unattractive, average, and attractive were digitally manipulated and paired with validated oral images, IOTN levels 1 (no treatment need), 7 (borderline treatment need), and 10 (definite treatment need). Sixty-four raters meeting the inclusion criteria were included in the data analysis. Each rater was calibrated in the eye tracker and randomly viewed the composite images for 3 seconds, twice for reliability. Reliability was good or excellent (intraclass correlation coefficients, 0.6-0.9). Significant interactions were observed with factorial repeated-measures analysis of variance and the Tukey-Kramer method for density and duration of fixations in the interactions of model facial attractiveness by area of the face (P models was eye, mouth, and nose, but for men of average attractiveness, it was mouth, eye, and nose. For dental esthetics by area, at IOTN 7, the mouth had significantly more visual attention than it did at IOTN 1 and significantly more than the nose. At IOTN 10, the mouth received significantly more attention than at IOTN 7 and surpassed the nose and eye. These findings were irrespective of facial attractiveness levels. For rater sex by area in visual density, women showed significantly more attention to the eyes than did men, and only men showed significantly more attention to the mouth over the nose. Visual attention to the mouth was the greatest in men of

  6. Real-time object tracking system based on field-programmable gate array and convolution neural network

    Directory of Open Access Journals (Sweden)

    Congyi Lyu

    2016-12-01

    Full Text Available Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

  7. Objectively Determining the Educational Potential of Computer and Video-Based Courseware; or, Producing Reliable Evaluations Despite the Dog and Pony Show.

    Science.gov (United States)

    Barrett, Andrew J.; And Others

    The Center for Interactive Technology, Applications, and Research at the College of Engineering of the University of South Florida (Tampa) has developed objective and descriptive evaluation models to assist in determining the educational potential of computer and video courseware. The computer-based courseware evaluation model and the video-based…

  8. 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...

  9. Utilization of DICOM multi-frame objects for integrating kinetic and kinematic data with raw videos in movement analysis of wheel-chair users to minimize shoulder pain

    Science.gov (United States)

    Deshpande, Ruchi R.; Li, Han; Requejo, Philip; McNitt-Gray, Sarah; Ruparel, Puja; Liu, Brent J.

    2012-02-01

    Wheelchair users are at an increased risk of developing shoulder pain. The key to formulating correct wheelchair operating practices is to analyze the movement patterns of a sample set of subjects. Data collected for movement analysis includes videos and force/ motion readings. Our goal is to combine the kinetic/ kinematic data with the trial video by overlaying force vector graphics on the raw video. Furthermore, conversion of the video to a DICOM multiframe object annotated with the force vector could provide a standardized way of encoding and analyzing data across multiple studies and provide a useful tool for data mining.

  10. Tracking Systems for Virtual Rehabilitation: Objective Performance vs. Subjective Experience. A Practical Scenario

    Directory of Open Access Journals (Sweden)

    Roberto Lloréns

    2015-03-01

    Full Text Available Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 ± 0.417 cm while the electromagnetic device provided the most inaccurate results (11.027 ± 2.364 cm. However, this tracking solution provided the best jitter values (0.324 ± 0.093 cm, in contrast to the skeleton tracking, which had the worst results (1.522 ± 0.858 cm. Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order. Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system.

  11. Fast-track rehabilitation following video-assisted pulmonary sublobar wedge resection: A prospective randomized study

    Directory of Open Access Journals (Sweden)

    Christos Asteriou

    2016-01-01

    Full Text Available Background: Postoperative morbidity and inhospital length of stay are considered major determinants of total health care expenditure associated with thoracic operations. The aim of this study was to prospectively evaluate the role of video-assisted thoracic surgery (VATS compared to mini-muscle-sparing thoracotomy in facilitating early recovery and hospital discharge after pulmonary sublobar wedge resections. Patients and Methods: A total number of 120 patients undergoing elective pulmonary sublobar wedge resection were randomly assigned to VATS (n = 60 or mini-muscle-sparing thoracotomy (n = 60. The primary endpoint was time to hospital discharge. Postoperative complications, cardiopulmonary morbidity and 30-day mortality served as secondary endpoints. Results: Patients' baseline demographic and clinical data did not differ among study arms as well as the number of pulmonary segments resected and the morphology of the nodular lesions. Total hospital stay was significantly shorter in patients assigned to the thoracoscopic technique as opposed to those who were operated using the mini-muscle-sparing thoracotomy approach (4 ± 0.6 versus 4.4 ± 0.6 days respectively, P = 0.006. Multivariate analysis revealed that VATS approach was inversely associated with longer inhospital stay whereas the number of resected segments was positively associated with an increased duration of hospitalization. Patients in the VATS group were less likely to develop atelectasis (≥1 lobe compared to those who underwent thoracotomy (0% versus 6.7% respectively, P = 0.042. Kaplan-Meier analysis revealed similar 30-day mortality rates in both study arms (Log-rank P = 0.560. Conclusion: VATS was associated with shorter duration of hospitalization positively affecting the patients' quality of life and satisfaction. Significant suppression of the total cost of recovery after thoracoscopic pulmonary resections is expected.

  12. Real-Time Vehicle Speed Estimation Based on License Plate Tracking in Monocular Video Sequences

    Directory of Open Access Journals (Sweden)

    Aleksej MAKAROV

    2016-02-01

    Full Text Available A method of estimating the vehicle speed from images obtained by a fixed over-the-road monocular camera is presented. The method is based on detecting and tracking vehicle license plates. The contrast between the license plate and its surroundings is enhanced using infrared light emitting diodes and infrared camera filters. A range of the license plate height values is assumed a priori. The camera vertical angle of view is measured prior to installation. The camera tilt is continuously measured by a micro-electromechanical sensor. The distance of the license plate from the camera is theoretically derived in terms of its pixel coordinates. Inaccuracies due to the frame rate drift, to the tilt and the angle of view measurement errors, to edge pixel detection and to a coarse assumption of the vehicle license plate height are analyzed and theoretically formulated. The resulting system is computationally efficient, inexpensive and easy to install and maintain along with the existing ALPR cameras.

  13. Apocalypse postponed. Discourses on video games from noxious objects to redemptive devices

    Directory of Open Access Journals (Sweden)

    Marco Benoit Carbone

    2012-05-01

    Full Text Available Over the last decade, a new narrative has emerged in favour of the medium of the video game. Games are now being described as a series of practices which improve our mental and physical skills (see Johnson, 2005, or the marketing and reception of Nintendo’s 2007 game Wii Fit; they are targeted to a mature audience, and are no more associated with antisocial teenagers (see Prensky, 2006; they are capable of unprecedented aesthetic achievements (see the reception of games like Rockstar Games’ 2011 L.A. Noire; and their consumption allegedly reveals a seemingly never-ending user growth, making them a globalized, pivotal media for the solution of social and political issues on the scale of the whole planet (McGonigal, 2011.

  14. On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

    Science.gov (United States)

    LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

    2017-12-01

    The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

  15. Fast generation of video holograms of three-dimensional moving objects using a motion compensation-based novel look-up table.

    Science.gov (United States)

    Kim, Seung-Cheol; Dong, Xiao-Bin; Kwon, Min-Woo; Kim, Eun-Soo

    2013-05-06

    A novel approach for fast generation of video holograms of three-dimensional (3-D) moving objects using a motion compensation-based novel-look-up-table (MC-N-LUT) method is proposed. Motion compensation has been widely employed in compression of conventional 2-D video data because of its ability to exploit high temporal correlation between successive video frames. Here, this concept of motion-compensation is firstly applied to the N-LUT based on its inherent property of shift-invariance. That is, motion vectors of 3-D moving objects are extracted between the two consecutive video frames, and with them motions of the 3-D objects at each frame are compensated. Then, through this process, 3-D object data to be calculated for its video holograms are massively reduced, which results in a dramatic increase of the computational speed of the proposed method. Experimental results with three kinds of 3-D video scenarios reveal that the average number of calculated object points and the average calculation time for one object point of the proposed method, have found to be reduced down to 86.95%, 86.53% and 34.99%, 32.30%, respectively compared to those of the conventional N-LUT and temporal redundancy-based N-LUT (TR-N-LUT) methods.

  16. Objective Identification of Environmental Patterns Related to Tropical Cyclone Track Forecast Errors

    National Research Council Canada - National Science Library

    Sanabia, Elizabeth R

    2006-01-01

    The increase in skill of numerical model guidance and the use of consensus forecast techniques have led to significant improvements in the accuracy of tropical cyclone track forecasts at ranges beyond 72 hours...

  17. A study on software-based sensing technology for multiple object control in AR video.

    Science.gov (United States)

    Jung, Sungmo; Song, Jae-Gu; Hwang, Dae-Joon; Ahn, Jae Young; Kim, Seoksoo

    2010-01-01

    Researches on Augmented Reality (AR) have recently received attention. With these, the Machine-to-Machine (M2M) market has started to be active and there are numerous efforts to apply this to real life in all sectors of society. To date, the M2M market has applied the existing marker-based AR technology in entertainment, business and other industries. With the existing marker-based AR technology, a designated object can only be loaded on the screen from one marker and a marker has to be added to load on the screen the same object again. This situation creates a problem where the relevant marker'should be extracted and printed in screen so that loading of the multiple objects is enabled. However, since the distance between markers will not be measured in the process of detecting and copying markers, the markers can be overlapped and thus the objects would not be augmented. To solve this problem, a circle having the longest radius needs to be created from a focal point of a marker to be copied, so that no object is copied within the confines of the circle. In this paper, software-based sensing technology for multiple object detection and loading using PPHT has been developed and overlapping marker control according to multiple object control has been studied using the Bresenham and Mean Shift algorithms.

  18. A Study on Software-based Sensing Technology for Multiple Object Control in AR Video

    Directory of Open Access Journals (Sweden)

    Seoksoo Kim

    2010-11-01

    Full Text Available Researches on Augmented Reality (AR have recently received attention. With these, the Machine-to-Machine (M2M market has started to be active and there are numerous efforts to apply this to real life in all sectors of society. To date, the M2M market has applied the existing marker-based AR technology in entertainment, business and other industries. With the existing marker-based AR technology, a designated object can only be loaded on the screen from one marker and a marker has to be added to load on the screen the same object again. This situation creates a problem where the relevant marker should be extracted and printed in screen so that loading of the multiple objects is enabled. However, since the distance between markers will not be measured in the process of detecting and copying markers, the markers can be overlapped and thus the objects would not be augmented. To solve this problem, a circle having the longest radius needs to be created from a focal point of a marker to be copied, so that no object is copied within the confines of the circle. In this paper, software-based sensing technology for multiple object detection and loading using PPHT has been developed and overlapping marker control according to multiple object control has been studied using the Bresenham and Mean Shift algorithms.

  19. High Dynamics and Precision Optical Measurement Using a Position Sensitive Detector (PSD in Reflection-Mode: Application to 2D Object Tracking over a Smart Surface

    Directory of Open Access Journals (Sweden)

    Ioan Alexandru Ivan

    2012-12-01

    Full Text Available When related to a single and good contrast object or a laser spot, position sensing, or sensitive, detectors (PSDs have a series of advantages over the classical camera sensors, including a good positioning accuracy for a fast response time and very simple signal conditioning circuits. To test the performance of this kind of sensor for microrobotics, we have made a comparative analysis between a precise but slow video camera and a custom-made fast PSD system applied to the tracking of a diffuse-reflectivity object transported by a pneumatic microconveyor called Smart-Surface. Until now, the fast system dynamics prevented the full control of the smart surface by visual servoing, unless using a very expensive high frame rate camera. We have built and tested a custom and low cost PSD-based embedded circuit, optically connected with a camera to a single objective by means of a beam splitter. A stroboscopic light source enhanced the resolution. The obtained results showed a good linearity and a fast (over 500 frames per second response time which will enable future closed-loop control by using PSD.

  20. 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...

  1. Detection of patient movement during CBCT examination using video observation compared with an accelerometer-gyroscope tracking system.

    Science.gov (United States)

    Spin-Neto, Rubens; Matzen, Louise H; Schropp, Lars; Gotfredsen, Erik; Wenzel, Ann

    2017-02-01

    To compare video observation (VO) with a novel three-dimensional registration method, based on an accelerometer-gyroscope (AG) system, to detect patient movement during CBCT examination. The movements were further analyzed according to complexity and patient age. In 181 patients (118 females/63 males; age average 30 years, range: 9-84 years), 206 CBCT examinations were performed, which were video-recorded during examination. An AG was, at the same time, attached to the patient head to track head position in three dimensions. Three observers scored patient movement (yes/no) by VO. AG provided movement data on the x-, y- and z-axes. Thresholds for AG-based registration were defined at 0.5, 1, 2, 3 and 4 mm (movement distance). Movement detected by VO was compared with that registered by AG, according to movement complexity (uniplanar vs multiplanar, as defined by AG) and patient age (≤15, 16-30 and ≥31 years). According to AG, movement ≥0.5 mm was present in 160 (77.7%) examinations. According to VO, movement was present in 46 (22.3%) examinations. One VO-detected movement was not registered by AG. Overall, VO did not detect 71.9% of the movements registered by AG at the 0.5-mm threshold. At a movement distance ≥4 mm, 20% of the AG-registered movements were not detected by VO. Multiplanar movements such as lateral head rotation (72.1%) and nodding/swallowing (52.6%) were more often detected by VO in comparison with uniplanar movements, such as head lifting (33.6%) and anteroposterior translation (35.6%), at the 0.5-mm threshold. The prevalence of patients who move was highest in patients younger than 16 years (64.3% for VO and 92.3% for AG-based registration at the 0.5-mm threshold). AG-based movement registration resulted in a higher prevalence of patient movement during CBCT examination than VO-based registration. Also, AG-registered multiplanar movements were more frequently detected by VO than uniplanar movements. The prevalence of patients who move

  2. 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.

  3. Objective assessment of the impact of frame rate on video quality

    DEFF Research Database (Denmark)

    Ukhanova, Ann; Korhonen, Jari; Forchhammer, Søren

    2012-01-01

    In this paper, we present a novel objective quality metric that takes the impact of frame rate into account. The proposed metric uses PSNR, frame rate and a content dependent parameter that can easily be obtained from spatial and temporal activity indices. The results have been validated on data ...

  4. Tracking on non-active collaborative objects from San Fernando Laser station

    Science.gov (United States)

    Catalán, Manuel; Quijano, Manuel; Cortina, Luis M.; Pazos, Antonio A.; Martín-Davila, José

    2016-04-01

    The Royal Observatory of the Spanish Navy (ROA) works on satellite geodesy from the early days of the space age, when the first artificial satellite tracking telescope was installed in 1958: the Baker-Nunn camera. In 1975 a French satellite Laser ranging (SLR) station was installed and operated at ROA . Since 1980, ROA has been operating this instrument which was upgraded to a third generation and it is still keep into a continuous update to reach the highest level of operability. Since then ROA has participated in different space geodesy campaigns through the International Laser Service Stations (ILRS) or its European regional organization (EUROLAS), tracking a number of artificial satellites types : ERS, ENVISAT, LAGEOS, TOPEX- POSEIDON to name but a few. Recently we opened a new field of research: space debris tracking, which is receiving increasing importance and attention from international space agencies. The main problem is the relatively low accuracy of common used methods. It is clear that improving the predicted orbit accuracy is necessary to fulfill our aims (avoiding unnecessary anti-collision maneuvers,..). Following results obtained by other colleagues (Austria, China, USA,...) we proposed to share our time-schedule using our satellite ranging station to obtain data which will make orbital elements predictions far more accurate (sub-meter accuracy), while we still keep our tracking routines over active satellites. In this communication we report the actions fulfill until nowadays.

  5. Nested Multi- and Many-Objective Optimisation of Team Track Pursuit Cycling

    Directory of Open Access Journals (Sweden)

    Markus Wagner

    2016-10-01

    Full Text Available Team pursuit track cycling is an elite sport that is part of the Summer Olympics. Teams race against each other on special tracks called velodromes. In this article, we create racing strategies that allow the team to complete the race in as little time as possible. In addition to the traditional minimisation of the race times, we consider the amount of energy that the riders have left at the end of the race. For the team coach this extension can have the benefit that a diverse set of trade-off strategies can be considered. For the optimisation approach, the added diversity can help to get over local optima.To solve this problem, we apply different state-of-the-art algorithms with problem-specific variation operators. It turns out that nesting algorithms is beneficial for achieving fast strategies reliably.

  6. 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.

  7. Automated cell tracking and analysis in phase-contrast videos (iTrack4U): development of Java software based on combined mean-shift processes.

    Science.gov (United States)

    Cordelières, Fabrice P; Petit, Valérie; Kumasaka, Mayuko; Debeir, Olivier; Letort, Véronique; Gallagher, Stuart J; Larue, Lionel

    2013-01-01

    Cell migration is a key biological process with a role in both physiological and pathological conditions. Locomotion of cells during embryonic development is essential for their correct positioning in the organism; immune cells have to migrate and circulate in response to injury. Failure of cells to migrate or an inappropriate acquisition of migratory capacities can result in severe defects such as altered pigmentation, skull and limb abnormalities during development, and defective wound repair, immunosuppression or tumor dissemination. The ability to accurately analyze and quantify cell migration is important for our understanding of development, homeostasis and disease. In vitro cell tracking experiments, using primary or established cell cultures, are often used to study migration as cells can quickly and easily be genetically or chemically manipulated. Images of the cells are acquired at regular time intervals over several hours using microscopes equipped with CCD camera. The locations (x,y,t) of each cell on the recorded sequence of frames then need to be tracked. Manual computer-assisted tracking is the traditional method for analyzing the migratory behavior of cells. However, this processing is extremely tedious and time-consuming. Most existing tracking algorithms require experience in programming languages that are unfamiliar to most biologists. We therefore developed an automated cell tracking program, written in Java, which uses a mean-shift algorithm and ImageJ as a library. iTrack4U is a user-friendly software. Compared to manual tracking, it saves considerable amount of time to generate and analyze the variables characterizing cell migration, since they are automatically computed with iTrack4U. Another major interest of iTrack4U is the standardization and the lack of inter-experimenter differences. Finally, iTrack4U is adapted for phase contrast and fluorescent cells.

  8. Automated cell tracking and analysis in phase-contrast videos (iTrack4U: development of Java software based on combined mean-shift processes.

    Directory of Open Access Journals (Sweden)

    Fabrice P Cordelières

    Full Text Available Cell migration is a key biological process with a role in both physiological and pathological conditions. Locomotion of cells during embryonic development is essential for their correct positioning in the organism; immune cells have to migrate and circulate in response to injury. Failure of cells to migrate or an inappropriate acquisition of migratory capacities can result in severe defects such as altered pigmentation, skull and limb abnormalities during development, and defective wound repair, immunosuppression or tumor dissemination. The ability to accurately analyze and quantify cell migration is important for our understanding of development, homeostasis and disease. In vitro cell tracking experiments, using primary or established cell cultures, are often used to study migration as cells can quickly and easily be genetically or chemically manipulated. Images of the cells are acquired at regular time intervals over several hours using microscopes equipped with CCD camera. The locations (x,y,t of each cell on the recorded sequence of frames then need to be tracked. Manual computer-assisted tracking is the traditional method for analyzing the migratory behavior of cells. However, this processing is extremely tedious and time-consuming. Most existing tracking algorithms require experience in programming languages that are unfamiliar to most biologists. We therefore developed an automated cell tracking program, written in Java, which uses a mean-shift algorithm and ImageJ as a library. iTrack4U is a user-friendly software. Compared to manual tracking, it saves considerable amount of time to generate and analyze the variables characterizing cell migration, since they are automatically computed with iTrack4U. Another major interest of iTrack4U is the standardization and the lack of inter-experimenter differences. Finally, iTrack4U is adapted for phase contrast and fluorescent cells.

  9. No Evidence for Phase-Specific Effects of 40 Hz HD–tACS on Multiple Object Tracking

    Directory of Open Access Journals (Sweden)

    Nicholas S. Bland

    2018-03-01

    Full Text Available Phase synchronization drives connectivity between neural oscillators, providing a flexible mechanism through which information can be effectively and selectively routed between task-relevant cortical areas. The ability to keep track of objects moving between the left and right visual hemifields, for example, requires the integration of information between the two cerebral hemispheres. Both animal and human studies have suggested that coherent (or phase-locked gamma oscillations (30–80 Hz might underlie this ability. While most human evidence has been strictly correlational, high-density transcranial alternating current stimulation (HD-tACS has been used to manipulate ongoing interhemispheric gamma phase relationships. Previous research showed that 40 Hz tACS delivered bilaterally over human motion complex could bias the perception of a bistable ambiguous motion stimulus (Helfrich et al., 2014. Specifically, this work showed that in-phase (0° offset stimulation boosted endogenous interhemispheric gamma coherence and biased perception toward the horizontal (whereby visual tokens moved between visual hemifields—requiring interhemispheric integration. By contrast, anti-phase (180° offset stimulation decreased interhemispheric gamma coherence and biased perception toward the vertical (whereby tokens moved within separate visual hemifields. Here we devised a multiple object tracking arena comprised of four quadrants whereby discrete objects moved either entirely within the left and right visual hemifields, or could cross freely between visual hemifields, thus requiring interhemispheric integration. Using the same HD-tACS montages as Helfrich et al. (2014, we found no phase-specific effect of 40 Hz stimulation on overall tracking performance. While tracking performance was generally lower during between-hemifield trials (presumably reflecting a cost of integration, this difference was unchanged by in- vs. anti-phase stimulation. Our null results

  10. Is Content Really King? An Objective Analysis of the Public's Response to Medical Videos on YouTube

    Science.gov (United States)

    Desai, Tejas; Shariff, Afreen; Dhingra, Vibhu; Minhas, Deeba; Eure, Megan; Kats, Mark

    2013-01-01

    Medical educators and patients are turning to YouTube to teach and learn about medical conditions. These videos are from authors whose credibility cannot be verified & are not peer reviewed. As a result, studies that have analyzed the educational content of YouTube have reported dismal results. These studies have been unable to exclude videos created by questionable sources and for non-educational purposes. We hypothesize that medical education YouTube videos, authored by credible sources, are of high educational value and appropriately suited to educate the public. Credible videos about cardiovascular diseases were identified using the Mayo Clinic's Center for Social Media Health network. Content in each video was assessed by the presence/absence of 7 factors. Each video was also evaluated for understandability using the Suitability Assessment of Materials (SAM). User engagement measurements were obtained for each video. A total of 607 videos (35 hours) were analyzed. Half of all videos contained 3 educational factors: treatment, screening, or prevention. There was no difference between the number of educational factors present & any user engagement measurement (p NS). SAM scores were higher in videos whose content discussed more educational factors (pYouTube. PMID:24367517

  11. Optical derotator alignment using image-processing algorithm for tracking laser vibrometer measurements of rotating objects.

    Science.gov (United States)

    Khalil, Hossam; Kim, Dongkyu; Jo, Youngjoon; Park, Kyihwan

    2017-06-01

    An optical component called a Dove prism is used to rotate the laser beam of a laser-scanning vibrometer (LSV). This is called a derotator and is used for measuring the vibration of rotating objects. The main advantage of a derotator is that it works independently from an LSV. However, this device requires very specific alignment, in which the axis of the Dove prism must coincide with the rotational axis of the object. If the derotator is misaligned with the rotating object, the results of the vibration measurement are imprecise, owing to the alteration of the laser beam on the surface of the rotating object. In this study, a method is proposed for aligning a derotator with a rotating object through an image-processing algorithm that obtains the trajectory of a landmark attached to the object. After the trajectory of the landmark is mathematically modeled, the amount of derotator misalignment with respect to the object is calculated. The accuracy of the proposed method for aligning the derotator with the rotating object is experimentally tested.

  12. Objective Tracking of Tropical Cyclones in the North-West Pacific Basin Based on Wind Field Information only

    Science.gov (United States)

    Leckebusch, G. C.; Befort, D. J.; Kruschke, T.

    2016-12-01

    Although only ca. 12% of the global insured losses of natural disasters occurred in Asia, there are two major reasons to be concerned about risks in Asia: a) The fraction of loss events was substantial higher with 39% of which 94% were due to atmospheric processes; b) Asia and especially China, is undergoing quick transitions and especially the insurance market is rapidly growing. In order to allow for the estimation of potential future (loss) impacts in East-Asia, in this study we further developed and applied a feature tracking system based on extreme wind speed occurrences to tropical cyclones, which was originally developed for extra-tropical cyclones (Leckebusch et al., 2008). In principle, wind fields will be identified and tracked once a coherent exceedance of local percentile thresholds is identified. The focus on severe wind impact will allow an objective link between the strength of a cyclone and its potential damages over land. The wind tracking is developed in such a way to be applicable also to course-gridded AOGCM simulation. In the presented configuration the wind tracking algorithm is applied to the Japanese reanalysis (JRA55) and TC Identification is based on 850hPa wind speeds (6h resolution) from 1979 to 2014 over the Western North Pacific region. For validation the IBTrACS Best Track archive version v03r8 is used. Out of all 904 observed tracks, about 62% can be matched to at least one windstorm event identified in JRA55. It is found that the relative amount of matched best tracks increases with the maximum intensity. Thus, a positive matching (hit rate) of above 98% for Violent Typhoons (VTY), above 90% for Very Strong Typhoons (VSTY), about 75% for Typhoons (TY), and still some 50% for less intense TCs (TD, TS, STS) is found. This result is extremely encouraging to apply this technique to AOGCM outputs and to derive information about affected regions and intensity-frequency distributions potentially changed under future climate conditions.

  13. Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

    Science.gov (United States)

    Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

    2017-08-01

    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

  14. Effects of the pyrethroid insecticide Cypermethrin on the locomotor activity of the wolf spider Pardosa amentata: quantitative analysis employing computer-automated video tracking

    DEFF Research Database (Denmark)

    Baatrup, E; Bayley, M

    1993-01-01

    Pardosa amentata was quantified in an open field setup, using computer-automated video tracking. Each spider was recorded for 24 hr prior to pesticide exposure. After topical application of 4.6 ng of Cypermethrin, the animal was recorded for a further 48 hr. Finally, after 9 days of recovery, the spider...... paresis, the effects of Cypermethrin were evident in reduced path length, average velocity, and maximum velocity and an increase in the time spent in quiescence. Also, the pyrethroid disrupted the consistent distributions of walking velocity and periods of quiescence seen prior to pesticide application...

  15. 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

  16. 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

  17. Post-Newtonian equations of motion for LEO debris objects and space-based acquisition, pointing and tracking laser systems

    Science.gov (United States)

    Gambi, J. M.; García del Pino, M. L.; Gschwindl, J.; Weinmüller, E. B.

    2017-12-01

    This paper deals with the problem of throwing middle-sized low Earth orbit debris objects into the atmosphere via laser ablation. The post-Newtonian equations here provided allow (hypothetical) space-based acquisition, pointing and tracking systems endowed with very narrow laser beams to reach the pointing accuracy presently prescribed. In fact, whatever the orbital elements of these objects may be, these equations will allow the operators to account for the corrections needed to balance the deviations of the line of sight directions due to the curvature of the paths the laser beams are to travel along. To minimize the respective corrections, the systems will have to perform initial positioning manoeuvres, and the shooting point-ahead angles will have to be adapted in real time. The enclosed numerical experiments suggest that neglecting these measures will cause fatal errors, due to differences in the actual locations of the objects comparable to their size.

  18. Comparative Analysis of Several Real-Time Systems for Tracking People and/or Moving Objects using GPS

    OpenAIRE

    Radinski, Gligorcho; Mileva, Aleksandra

    2015-01-01

    When we talk about real-time systems for tracking people and/or moving objects using a Global Positioning System (GPS), there are several categories of such systems and the ways in which they work. Some uses additional hardware to extend the functionality of the offered opportunities, some are free, some are too complex and cost too much money. This paper aims to provide a clearer picture of several such systems and to show results from a comparative analysis of some popular systems for trac...

  19. 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.

  20. Keeping up with video game technology: objective analysis of Xbox Kinect™ and PlayStation 3 Move™ for use in burn rehabilitation.

    Science.gov (United States)

    Parry, Ingrid; Carbullido, Clarissa; Kawada, Jason; Bagley, Anita; Sen, Soman; Greenhalgh, David; Palmieri, Tina

    2014-08-01

    Commercially available interactive video games are commonly used in rehabilitation to aide in physical recovery from a variety of conditions and injuries, including burns. Most video games were not originally designed for rehabilitation purposes and although some games have shown therapeutic potential in burn rehabilitation, the physical demands of more recently released video games, such as Microsoft Xbox Kinect™ (Kinect) and Sony PlayStation 3 Move™ (PS Move), have not been objectively evaluated. Video game technology is constantly evolving and demonstrating different immersive qualities and interactive demands that may or may not have therapeutic potential for patients recovering from burns. This study analyzed the upper extremity motion demands of Kinect and PS Move using three-dimensional motion analysis to determine their applicability in burn rehabilitation. Thirty normal children played each video game while real-time movement of their upper extremities was measured to determine maximal excursion and amount of elevation time. Maximal shoulder flexion, shoulder abduction and elbow flexion range of motion were significantly greater while playing Kinect than the PS Move (p≤0.01). Elevation time of the arms above 120° was also significantly longer with Kinect (p<0.05). The physical demands for shoulder and elbow range of motion while playing the Kinect, and to a lesser extent PS Move, are comparable to functional motion needed for daily tasks such as eating with a utensil and hair combing. Therefore, these more recently released commercially available video games show therapeutic potential in burn rehabilitation. Objectively quantifying the physical demands of video games commonly used in rehabilitation aides clinicians in the integration of them into practice and lays the framework for further research on their efficacy. Copyright © 2013 Elsevier Ltd and ISBI. All rights reserved.

  1. A Multidimensional Scaling Approach to Developmental Dimensions in Object Permanence and Tracking Stimuli.

    Science.gov (United States)

    Townes-Rosenwein, Linda

    This paper discusses a longitudinal, exploratory study of developmental dimensions related to object permanence theory and explains how multidimensional scaling techniques can be used to identify developmental dimensions. Eighty infants, randomly assigned to one of four experimental groups and one of four counterbalanced orders of stimuli, were…

  2. Klet Observatory – European Contribution to Detecting and Tracking of Near Earth Objects

    Directory of Open Access Journals (Sweden)

    Milos Tichy

    2012-03-01

    Full Text Available Near Earth Object (NEO research is an expanding field of astronomy. Is is important for solar system science and also for protecting human society from asteroid and comet hazard.  A near-Earth object (NEO can be defined as an asteroid or comet that has a possibility of making an approach to the Earth, or possibly even collide with it. The discovery rate of current NEO surveys reflects progressive improvement in a number of technical areas. An integral part of NEO discovery is astrometric follow-up fundamental for precise orbit computation and for the reasonable judging of future close encounters with the Earth including possible impact solutions. A wide international cooperation is fundamental for NEO research.  The Klet Observatory (South Bohemia, Czech Republic is aimed especially at the confirmation, early follow-up, long-arc follow-up and recovery of Near Earth Objects. It ranks among the world´s most prolific professional NEO follow-up programmes.  The first NEO follow-up programme started at Klet in 1993 using 0.57-reflector equipped with a small CCD camera. A fundamental upgrade was made in 2002 when the 1.06-m KLENOT telescope was put into regular operation. The KLENOT Telescope is the largest telescope in Europe used exclusively for observations of minor planets (asteroids and comets and full observing time is dedicated to the KLENOT team.  Equipment, technology, software, observing strategy and results of both the Klet Observatory NEO Project between 1993-2010 and the first phase of the KLENOT Project from March 2002 to September 2008 are presented. They consist of thousands of precise astrometric measurements of Near Earth Objects and also three newly discovered Near Earth Asteroids.  Klet Observatory NEO activities as well as our future plans fully reflect international strategies and cooperation in the field of NEO studies.

  3. REAL-TIME OBJECT DETECTION IN PARALLEL THROUGH ATOMIC TRANSACTIONS

    Directory of Open Access Journals (Sweden)

    K Sivakumar

    2016-11-01

    Full Text Available Object detection and tracking is important operation involved in embedded systems like video surveillance, Traffic monitoring, campus security system, machine vision applications and other areas. Detecting and tracking multiple objects in a video or image is challenging problem in machine vision and computer vision based embedded systems. Implementation of such a object detection and tracking systems are done in sequential way of processing and also it was implemented using hardware synthesize tools like verilog HDL with FPGA, achieves considerably lesser performance in speed and it does support lesser atomic transactions. There are many object detection and tracking algorithm were proposed and implemented, among them background subtraction is one of them. This paper proposes a implementation of detecting and tracking multiple objects based on background subtraction algorithm using java and .NET and also discuss about the architecture concept for object detection through atomic transactional, modern hardware synthesizes language called Bluespec.

  4. Objectivity

    CERN Document Server

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  5. Three-directional motion compensation-based novel-look-up-table for video hologram generation of three-dimensional objects freely maneuvering in space.

    Science.gov (United States)

    Dong, Xiao-Bin; Kim, Seung-Cheol; Kim, Eun-Soo

    2014-07-14

    A new three-directional motion compensation-based novel-look-up-table (3DMC-NLUT) based on its shift-invariance and thin-lens properties, is proposed for video hologram generation of three-dimensional (3-D) objects moving with large depth variations in space. The input 3-D video frames are grouped into a set of eight in sequence, where the first and remaining seven frames in each set become the reference frame (RF) and general frames (GFs), respectively. Hence, each 3-D video frame is segmented into a set of depth-sliced object images (DOIs). Then x, y, and z-directional motion vectors are estimated from blocks and DOIs between the RF and each of the GFs, respectively. With these motion vectors, object motions in space are compensated. Then, only the difference images between the 3-directionally motion-compensated RF and each of the GFs are applied to the NLUT for hologram calculation. Experimental results reveal that the average number of calculated object points and the average calculation time of the proposed method have been reduced compared to those of the conventional NLUT, TR-NLUT and MPEG-NLUT by 38.14%, 69.48%, and 67.41% and 35.30%, 66.39%, and 64.46%, respectively.

  6. A Synthetic Algorithm for Tracking a Moving Object in a Multiple-Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

    Directory of Open Access Journals (Sweden)

    Hongzhe Jin

    2017-01-01

    Full Text Available This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

  7. Intelligent keyframe extraction for video printing

    Science.gov (United States)

    Zhang, Tong

    2004-10-01

    Nowadays most digital cameras have the functionality of taking short video clips, with the length of video ranging from several seconds to a couple of minutes. The purpose of this research is to develop an algorithm which extracts an optimal set of keyframes from each short video clip so that the user could obtain proper video frames to print out. In current video printing systems, keyframes are normally obtained by evenly sampling the video clip over time. Such an approach, however, may not reflect highlights or regions of interest in the video. Keyframes derived in this way may also be improper for video printing in terms of either content or image quality. In this paper, we present an intelligent keyframe extraction approach to derive an improved keyframe set by performing semantic analysis of the video content. For a video clip, a number of video and audio features are analyzed to first generate a candidate keyframe set. These features include accumulative color histogram and color layout differences, camera motion estimation, moving object tracking, face detection and audio event detection. Then, the candidate keyframes are clustered and evaluated to obtain a final keyframe set. The objective is to automatically generate a limited number of keyframes to show different views of the scene; to show different people and their actions in the scene; and to tell the story in the video shot. Moreover, frame extraction for video printing, which is a rather subjective problem, is considered in this work for the first time, and a semi-automatic approach is proposed.

  8. Analysis of warm season thunderstorms using an object-oriented tracking method based on radar and total lightning data

    Directory of Open Access Journals (Sweden)

    T. Rigo

    2010-09-01

    Full Text Available Monitoring thunderstorms activity is an essential part of operational weather surveillance given their potential hazards, including lightning, hail, heavy rainfall, strong winds or even tornadoes. This study has two main objectives: firstly, the description of a methodology, based on radar and total lightning data to characterise thunderstorms in real-time; secondly, the application of this methodology to 66 thunderstorms that affected Catalonia (NE Spain in the summer of 2006. An object-oriented tracking procedure is employed, where different observation data types generate four different types of objects (radar 1-km CAPPI reflectivity composites, radar reflectivity volumetric data, cloud-to-ground lightning data and intra-cloud lightning data. In the framework proposed, these objects are the building blocks of a higher level object, the thunderstorm.

    The methodology is demonstrated with a dataset of thunderstorms whose main characteristics, along the complete life cycle of the convective structures (development, maturity and dissipation, are described statistically. The development and dissipation stages present similar durations in most cases examined. On the contrary, the duration of the maturity phase is much more variable and related to the thunderstorm intensity, defined here in terms of lightning flash rate. Most of the activity of IC and CG flashes is registered in the maturity stage. In the development stage little CG flashes are observed (2% to 5%, while for the dissipation phase is possible to observe a few more CG flashes (10% to 15%. Additionally, a selection of thunderstorms is used to examine general life cycle patterns, obtained from the analysis of normalized (with respect to thunderstorm total duration and maximum value of variables considered thunderstorm parameters. Among other findings, the study indicates that the normalized duration of the three stages of thunderstorm life cycle is similar in most thunderstorms

  9. Analysis of warm season thunderstorms using an object-oriented tracking method based on radar and total lightning data

    Science.gov (United States)

    Rigo, T.; Pineda, N.; Bech, J.

    2010-09-01

    Monitoring thunderstorms activity is an essential part of operational weather surveillance given their potential hazards, including lightning, hail, heavy rainfall, strong winds or even tornadoes. This study has two main objectives: firstly, the description of a methodology, based on radar and total lightning data to characterise thunderstorms in real-time; secondly, the application of this methodology to 66 thunderstorms that affected Catalonia (NE Spain) in the summer of 2006. An object-oriented tracking procedure is employed, where different observation data types generate four different types of objects (radar 1-km CAPPI reflectivity composites, radar reflectivity volumetric data, cloud-to-ground lightning data and intra-cloud lightning data). In the framework proposed, these objects are the building blocks of a higher level object, the thunderstorm. The methodology is demonstrated with a dataset of thunderstorms whose main characteristics, along the complete life cycle of the convective structures (development, maturity and dissipation), are described statistically. The development and dissipation stages present similar durations in most cases examined. On the contrary, the duration of the maturity phase is much more variable and related to the thunderstorm intensity, defined here in terms of lightning flash rate. Most of the activity of IC and CG flashes is registered in the maturity stage. In the development stage little CG flashes are observed (2% to 5%), while for the dissipation phase is possible to observe a few more CG flashes (10% to 15%). Additionally, a selection of thunderstorms is used to examine general life cycle patterns, obtained from the analysis of normalized (with respect to thunderstorm total duration and maximum value of variables considered) thunderstorm parameters. Among other findings, the study indicates that the normalized duration of the three stages of thunderstorm life cycle is similar in most thunderstorms, with the longest

  10. 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...

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

    Science.gov (United States)

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

    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 Garcia scales did not show significant differences between pre- and post-stroke animals in a small cohort. When using the same cohort, however, post-stroke data obtained from automated open field analysis showed significant differences in several parameters. Furthermore, large cohort analysis also demonstrated increased sensitivity with automated open field analysis versus the Bederson and Garcia scales. These early data indicate use of automated open field analysis software may provide a more sensitive assessment when compared to traditional Bederson and Garcia scales.

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

    Directory of Open Access Journals (Sweden)

    Fiona A. Desland

    2014-01-01

    Full Text Available 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 Garcia scales did not show significant differences between pre- and post-stroke animals in a small cohort. When using the same cohort, however, post-stroke data obtained from automated open field analysis showed significant differences in several parameters. Furthermore, large cohort analysis also demonstrated increased sensitivity with automated open field analysis versus the Bederson and Garcia scales. These early data indicate use of automated open field analysis software may provide a more sensitive assessment when compared to traditional Bederson and Garcia scales.

  13. Development of radiation hardened robot for nuclear facility - Development of real-time stereo object tracking system using the optical correlator

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Eun Soo; Lee, S. H.; Lee, J. S. [Kwangwoon University, Seoul (Korea)

    2000-03-01

    Object tracking, through Centroide method used in the KAERI-M1 Stereo Robot Vision System developed at Atomic Research Center, is too sensitive to target's light variation and because it has a fragility which can't reflect the surrounding background, the application in the actual condition is very limited. Also the correlation method can constitute a relatively stable object tracker in noise features but the digital calculation amount is too massive in image correlation so real time materialization is limited. So the development of Optical Correlation based on Stereo Object Tracking System using high speed optical information processing technique will put stable the real time stereo object tracking system and substantial atomic industrial stereo robot vision system to practical use. This research is about developing real time stereo object tracking algorithm using optical correlation system through the technique which can be applied to Atomic Research Center's KAERI-M1 Stereo Vision Robot which will be used in atomic facility remote operations. And revise the stereo disparity using real time optical correlation technique, and materializing the application of the stereo object tracking algorithm to KAERI-M1 Stereo Robot. 19 refs., 45 figs., 2 tabs. (Author)

  14. Modeling self-occlusions in dynamic shape and appearance tracking

    KAUST Repository

    Yang, Yanchao; Sundaramoorthi, Ganesh

    2013-01-01

    We present a method to track the precise shape of a dynamic object in video. Joint dynamic shape and appearance models, in which a template of the object is propagated to match the object shape and radiance in the next frame, are advantageous over

  15. Position Based Visual Servoing control of a Wheelchair Mounter Robotic Arm using Parallel Tracking and Mapping of task objects

    Directory of Open Access Journals (Sweden)

    Alessandro Palla

    2017-05-01

    Full Text Available In the last few years power wheelchairs have been becoming the only device able to provide autonomy and independence to people with motor skill impairments. In particular, many power wheelchairs feature robotic arms for gesture emulation, like the interaction with objects. However, complex robotic arms often require a joystic to be controlled; this feature make the arm hard to be controlled by impaired users. Paradoxically, if the user were able to proficiently control such devices, he would not need them. For that reason, this paper presents a highly autonomous robotic arm, designed in order to minimize the effort necessary for the control of the arm. In order to do that, the arm feature an easy to use human - machine interface and is controlled by Computer Vison algorithm, implementing a Position Based Visual Servoing (PBVS control. It was realized by extracting features by the camera and fusing them with the distance from the target, obtained by a proximity sensor. The Parallel Tracking and Mapping (PTAM algorithm was used to find the 3D position of the task object in the camera reference system. The visual servoing algorithm was implemented in an embedded platform, in real time. Each part of the control loop was developed in Robotic Operative System (ROS Environment, which allows to implement the previous algorithms as different nodes. Theoretical analysis, simulations and in system measurements proved the effectiveness of the proposed solution.

  16. 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.

  17. Fighting Depression: Action Video Game Play May Reduce Rumination and Increase Subjective and Objective Cognition in Depressed Patients.

    Science.gov (United States)

    Kühn, Simone; Berna, Fabrice; Lüdtke, Thies; Gallinat, Jürgen; Moritz, Steffen

    2018-01-01

    Cognitive deficits are common in depression and may persist following the resolution of affective symptoms. However, therapeutic strategies that successfully target cognitive impairments are lacking. Recent work has demonstrated that playing action video games leads to improvements in cognition, in particular executive function, in healthy individuals. We therefore set out to test whether playing video games can reduce symptoms associated with depression. We focussed on depressive symptoms and on rumination, since rumination is a good predictor of depression and may contribute to triggering depression. We recruited 68 clinically depressed individuals (mean age: 46 years, 47 females) that were randomized into the training group playing a fast paced action video game for 6 weeks or a waitlist control group. Before and after training participants completed online questionnaires and a neuropsychological test battery. Only participants who actually played the game were included in the analysis. The final sample consisted of n = 21 training group and n = 29 waitlist control group. The training group showed significantly higher subjective cognitive ability, as well as lower self-reported rumination at posttest in contrast to the control group (although these findings do not survive Bonferroni correction). On a subsample with cognitive performance data ( n = 19) we detected an improvement in executive function (Trail Making Task A and B) in the training compared with the control group. The results show that the fast paced action video game employed in the present study improved Trail Making performance and may reduce rumination and enhance subjective cognitive ability. Future research may focus on the investigation of the precise cognitive profile of effects.

  18. Fighting Depression: Action Video Game Play May Reduce Rumination and Increase Subjective and Objective Cognition in Depressed Patients

    Directory of Open Access Journals (Sweden)

    Simone Kühn

    2018-02-01

    Full Text Available Cognitive deficits are common in depression and may persist following the resolution of affective symptoms. However, therapeutic strategies that successfully target cognitive impairments are lacking. Recent work has demonstrated that playing action video games leads to improvements in cognition, in particular executive function, in healthy individuals. We therefore set out to test whether playing video games can reduce symptoms associated with depression. We focussed on depressive symptoms and on rumination, since rumination is a good predictor of depression and may contribute to triggering depression. We recruited 68 clinically depressed individuals (mean age: 46 years, 47 females that were randomized into the training group playing a fast paced action video game for 6 weeks or a waitlist control group. Before and after training participants completed online questionnaires and a neuropsychological test battery. Only participants who actually played the game were included in the analysis. The final sample consisted of n = 21 training group and n = 29 waitlist control group. The training group showed significantly higher subjective cognitive ability, as well as lower self-reported rumination at posttest in contrast to the control group (although these findings do not survive Bonferroni correction. On a subsample with cognitive performance data (n = 19 we detected an improvement in executive function (Trail Making Task A and B in the training compared with the control group. The results show that the fast paced action video game employed in the present study improved Trail Making performance and may reduce rumination and enhance subjective cognitive ability. Future research may focus on the investigation of the precise cognitive profile of effects.

  19. Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

    Science.gov (United States)

    Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

    2012-02-01

    An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p < .05 for both), and when regression was used to partial out shared variance between the two tests, the remaining variance predicted by the OSPAN was minimal (sr ( 2 ) = .029). When measures of spatial memory were included in the regression, the unique variance predicted by the OSPAN became negligible (sr ( 2 ) = .000004). This suggests that the executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

  20. A novel video-tracking system to quantify the behaviour of nocturnal mosquitoes attacking human hosts in the field.

    Science.gov (United States)

    Angarita-Jaimes, N C; Parker, J E A; Abe, M; Mashauri, F; Martine, J; Towers, C E; McCall, P J; Towers, D P

    2016-04-01

    Many vectors of malaria and other infections spend most of their adult life within human homes, the environment where they bloodfeed and rest, and where control has been most successful. Yet, knowledge of peri-domestic mosquito behaviour is limited, particularly how mosquitoes find and attack human hosts or how insecticides impact on behaviour. This is partly because technology for tracking mosquitoes in their natural habitats, traditional dwellings in disease-endemic countries, has never been available. We describe a sensing device that enables observation and recording of nocturnal mosquitoes attacking humans with or without a bed net, in the laboratory and in rural Africa. The device addresses requirements for sub-millimetre resolution over a 2.0 × 1.2 × 2.0 m volume while using minimum irradiance. Data processing strategies to extract individual mosquito trajectories and algorithms to describe behaviour during host/net interactions are introduced. Results from UK laboratory and Tanzanian field tests showed that Culex quinquefasciatus activity was higher and focused on the bed net roof when a human host was present, in colonized and wild populations. Both C. quinquefasciatus and Anopheles gambiae exhibited similar behavioural modes, with average flight velocities varying by less than 10%. The system offers considerable potential for investigations in vector biology and many other fields. © 2016 The Authors.

  1. A software module for implementing auditory and visual feedback on a video-based eye tracking system

    Science.gov (United States)

    Rosanlall, Bharat; Gertner, Izidor; Geri, George A.; Arrington, Karl F.

    2016-05-01

    We describe here the design and implementation of a software module that provides both auditory and visual feedback of the eye position measured by a commercially available eye tracking system. The present audio-visual feedback module (AVFM) serves as an extension to the Arrington Research ViewPoint EyeTracker, but it can be easily modified for use with other similar systems. Two modes of audio feedback and one mode of visual feedback are provided in reference to a circular area-of-interest (AOI). Auditory feedback can be either a click tone emitted when the user's gaze point enters or leaves the AOI, or a sinusoidal waveform with frequency inversely proportional to the distance from the gaze point to the center of the AOI. Visual feedback is in the form of a small circular light patch that is presented whenever the gaze-point is within the AOI. The AVFM processes data that are sent to a dynamic-link library by the EyeTracker. The AVFM's multithreaded implementation also allows real-time data collection (1 kHz sampling rate) and graphics processing that allow display of the current/past gaze-points as well as the AOI. The feedback provided by the AVFM described here has applications in military target acquisition and personnel training, as well as in visual experimentation, clinical research, marketing research, and sports training.

  2. 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.

  3. Adaptive learning compressive tracking based on Markov location prediction

    Science.gov (United States)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  4. 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.

  5. 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.

  6. ROBUST MOTION SEGMENTATION FOR HIGH DEFINITION VIDEO SEQUENCES USING A FAST MULTI-RESOLUTION MOTION ESTIMATION BASED ON SPATIO-TEMPORAL TUBES

    OpenAIRE

    Brouard , Olivier; Delannay , Fabrice; Ricordel , Vincent; Barba , Dominique

    2007-01-01

    4 pages; International audience; Motion segmentation methods are effective for tracking video objects. However, objects segmentation methods based on motion need to know the global motion of the video in order to back-compensate it before computing the segmentation. In this paper, we propose a method which estimates the global motion of a High Definition (HD) video shot and then segments it using the remaining motion information. First, we develop a fast method for multi-resolution motion est...

  7. 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.

  8. 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.

  9. 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.

  10. A randomized comparison of video demonstration versus hands-on training of medical students for vacuum delivery using Objective Structured Assessment of Technical Skills (OSATS).

    Science.gov (United States)

    Hilal, Ziad; Kumpernatz, Anne K; Rezniczek, Günther A; Cetin, Cem; Tempfer-Bentz, Eva-Katrin; Tempfer, Clemens B

    2017-03-01

    To compare medical students' skills for vaginal operative delivery by vacuum extraction (VE) after hands-on training versus video demonstration. We randomized medical students to an expert demonstration (group 1) or a hands-on (group 2) training using a standardized VE algorithm on a pelvic training model. Students were tested with a 40-item Objective Structured Assessment of Technical Skills (OSATS) scoring system after training and 4 days later. OSATS scores were the primary outcome. Performance time, self-assessment, confidence, and global rating scale were secondary outcomes. We assessed the constructive validity of OSATS in this VE model comparing metric scores of experts and students. In all, 137 students were randomized. OSATS scores were higher in group 2 (n = 63) compared with group 1 (n = 74) (32.89 ± 6.39 vs 27.51 ± 10.27, respectively; P training is superior to video demonstration for teaching VE on a pelvic model.

  11. Advanced digital video surveillance for safeguard and physical protection

    International Nuclear Information System (INIS)

    Kumar, R.

    2002-01-01

    Full text: Video surveillance is a very crucial component in safeguard and physical protection. Digital technology has revolutionized the surveillance scenario and brought in various new capabilities like better image quality, faster search and retrieval of video images, less storage space for recording, efficient transmission and storage of video, better protection of recorded video images, and easy remote accesses to live and recorded video etc. The basic safeguard requirement for verifiably uninterrupted surveillance has remained largely unchanged since its inception. However, changes to the inspection paradigm to admit automated review and remote monitoring have dramatically increased the demands on safeguard surveillance system. Today's safeguard systems can incorporate intelligent motion detection with very low rate of false alarm and less archiving volume, embedded image processing capability for object behavior and event based indexing, object recognition, efficient querying and report generation etc. It also demands cryptographically authenticating, encrypted, and highly compressed video data for efficient, secure, tamper indicating and transmission. In physical protection, intelligent on robust video motion detection, real time moving object detection and tracking from stationary and moving camera platform, multi-camera cooperative tracking, activity detection and recognition, human motion analysis etc. is going to play a key rote in perimeter security. Incorporation of front and video imagery exploitation tools like automatic number plate recognition, vehicle identification and classification, vehicle undercarriage inspection, face recognition, iris recognition and other biometric tools, gesture recognition etc. makes personnel and vehicle access control robust and foolproof. Innovative digital image enhancement techniques coupled with novel sensor design makes low cost, omni-directional vision capable, all weather, day night surveillance a reality

  12. 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

  13. Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

    Science.gov (United States)

    Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

    2005-03-01

    The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

  14. Shape tracking with occlusions via coarse-to-fine region-based sobolev descent

    KAUST Repository

    Yang, Yanchao; Sundaramoorthi, Ganesh

    2015-01-01

    We present a method to track the shape of an object from video. The method uses a joint shape and appearance model of the object, which is propagated to match shape and radiance in subsequent frames, determining object shape. Self-occlusions and dis

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

    Science.gov (United States)

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

    2018-02-01

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

  16. 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.

  17. 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)

  18. 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)

  19. 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.

  20. REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. 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.

  3. Detection of nuclei in 4D Nomarski DIC microscope images of early Caenorhabditis elegans embryos using local image entropy and object tracking

    Directory of Open Access Journals (Sweden)

    Hamahashi Shugo

    2005-05-01

    Full Text Available Abstract Background The ability to detect nuclei in embryos is essential for studying the development of multicellular organisms. A system of automated nuclear detection has already been tested on a set of four-dimensional (4D Nomarski differential interference contrast (DIC microscope images of Caenorhabditis elegans embryos. However, the system needed laborious hand-tuning of its parameters every time a new image set was used. It could not detect nuclei in the process of cell division, and could detect nuclei only from the two- to eight-cell stages. Results We developed a system that automates the detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. Local image entropy is used to produce regions of the images that have the image texture of the nucleus. From these regions, those that actually detect nuclei are manually selected at the first and last time points of the image set, and an object-tracking algorithm then selects regions that detect nuclei in between the first and last time points. The use of local image entropy makes the system applicable to multiple image sets without the need to change its parameter values. The use of an object-tracking algorithm enables the system to detect nuclei in the process of cell division. The system detected nuclei with high sensitivity and specificity from the one- to 24-cell stages. Conclusion A combination of local image entropy and an object-tracking algorithm enabled highly objective and productive detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. The system will facilitate genomic and computational analyses of C. elegans embryos.

  4. 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)

  5. 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)

  6. 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.

  7. 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.

  8. Method of center localization for objects containing concentric arcs

    Science.gov (United States)

    Kuznetsova, Elena G.; Shvets, Evgeny A.; Nikolaev, Dmitry P.

    2015-02-01

    This paper proposes a method for automatic center location of objects containing concentric arcs. The method utilizes structure tensor analysis and voting scheme optimized with Fast Hough Transform. Two applications of the proposed method are considered: (i) wheel tracking in video-based system for automatic vehicle classification and (ii) tree growth rings analysis on a tree cross cut image.

  9. SEARCHING FOR SUB-KILOMETER TRANS-NEPTUNIAN OBJECTS USING PAN-STARRS VIDEO MODE LIGHT CURVES: PRELIMINARY STUDY AND EVALUATION USING ENGINEERING DATA

    International Nuclear Information System (INIS)

    Wang, J.-H.; Protopapas, P.; Alcock, C. R.; Chen, W.-P.; Burgett, W. S.; Morgan, J. S.; Price, P. A.; Tonry, J. L.; Dombeck, T.; Grav, T.

    2010-01-01

    We present a pre-survey study of using the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) high sampling rate video mode guide star images to search for trans-Neptunian objects (TNOs). Guide stars are primarily used by Pan-STARRS to compensate for image motion and hence improve the point-spread function. With suitable selection of the guide stars within the Pan-STARRS 7 deg 2 field of view, the light curves of these guide stars can also be used to search for occultations by TNOs. The best target stars for this purpose are stars with high signal-to-noise ratio (S/N) and small angular size. In order to do this, we compiled a catalog using the S/N calculated from stars with m V 0 ), we are able to set an upper limit of N(>0.5 km) ∼ 2.47 x 10 10 deg -2 at 95% confidence limit.

  10. Object-Based Visual Attention in 8-Month-Old Infants: Evidence from an Eye-Tracking Study

    Science.gov (United States)

    Bulf, Hermann; Valenza, Eloisa

    2013-01-01

    Visual attention is one of the infant's primary tools for gathering relevant information from the environment for further processing and learning. The space-based component of visual attention in infants has been widely investigated; however, the object-based component of visual attention has received scarce interest. This scarcity is…

  11. Augmented video viewing: transforming video consumption into an active experience

    OpenAIRE

    WIJNANTS, Maarten; Leën, Jeroen; QUAX, Peter; LAMOTTE, Wim

    2014-01-01

    Traditional video productions fail to cater to the interactivity standards that the current generation of digitally native customers have become accustomed to. This paper therefore advertises the \\activation" of the video consumption process. In particular, it proposes to enhance HTML5 video playback with interactive features in order to transform video viewing into a dynamic pastime. The objective is to enable the authoring of more captivating and rewarding video experiences for end-users. T...

  12. Autonomous Multicamera Tracking on Embedded Smart Cameras

    Directory of Open Access Journals (Sweden)

    Bischof Horst

    2007-01-01

    Full Text Available There is currently a strong trend towards the deployment of advanced computer vision methods on embedded systems. This deployment is very challenging since embedded platforms often provide limited resources such as computing performance, memory, and power. In this paper we present a multicamera tracking method on distributed, embedded smart cameras. Smart cameras combine video sensing, processing, and communication on a single embedded device which is equipped with a multiprocessor computation and communication infrastructure. Our multicamera tracking approach focuses on a fully decentralized handover procedure between adjacent cameras. The basic idea is to initiate a single tracking instance in the multicamera system for each object of interest. The tracker follows the supervised object over the camera network, migrating to the camera which observes the object. Thus, no central coordination is required resulting in an autonomous and scalable tracking approach. We have fully implemented this novel multicamera tracking approach on our embedded smart cameras. Tracking is achieved by the well-known CamShift algorithm; the handover procedure is realized using a mobile agent system available on the smart camera network. Our approach has been successfully evaluated on tracking persons at our campus.

  13. Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus.

    Science.gov (United States)

    Alnæs, Dag; Sneve, Markus Handal; Espeseth, Thomas; Endestad, Tor; van de Pavert, Steven Harry Pieter; Laeng, Bruno

    2014-04-01

    Attentional effort relates to the allocation of limited-capacity attentional resources to meet current task demands and involves the activation of top-down attentional systems in the brain. Pupillometry is a sensitive measure of this intensity aspect of top-down attentional control. Studies relate pupillary changes in response to cognitive processing to activity in the locus coeruleus (LC), which is the main hub of the brain's noradrenergic system and it is thought to modulate the operations of the brain's attentional systems. In the present study, participants performed a visual divided attention task known as multiple object tracking (MOT) while their pupil sizes were recorded by use of an infrared eye tracker and then were tested again with the same paradigm while brain activity was recorded using fMRI. We hypothesized that the individual pupil dilations, as an index of individual differences in mental effort, as originally proposed by Kahneman (1973), would be a better predictor of LC activity than the number of tracked objects during MOT. The current results support our hypothesis, since we observed pupil-related activity in the LC. Moreover, the changes in the pupil correlated with activity in the superior colliculus and the right thalamus, as well as cortical activity in the dorsal attention network, which previous studies have shown to be strongly activated during visual tracking of multiple targets. Follow-up pupillometric analyses of the MOT task in the same individuals also revealed that individual differences to cognitive load can be remarkably stable over a lag of several years. To our knowledge this is the first study using pupil dilations as an index of attentional effort in the MOT task and also relating these to functional changes in the brain that directly implicate the LC-NE system in the allocation of processing resources.

  14. 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.

  15. Video library for video imaging detection at intersection stop lines.

    Science.gov (United States)

    2010-04-01

    The objective of this activity was to record video that could be used for controlled : evaluation of video image vehicle detection system (VIVDS) products and software upgrades to : existing products based on a list of conditions that might be diffic...

  16. Persistent Aerial Tracking

    KAUST Repository

    Mueller, Matthias

    2016-01-01

    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

  17. Multithreaded hybrid feature tracking for markerless augmented reality.

    Science.gov (United States)

    Lee, Taehee; Höllerer, Tobias

    2009-01-01

    We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

  18. Simulation of laser detection and ranging (LADAR) and forward-looking infrared (FLIR) data for autonomous tracking of airborne objects

    Science.gov (United States)

    Powell, Gavin; Markham, Keith C.; Marshall, David

    2000-06-01

    This paper presents the results of an investigation leading into an implementation of FLIR and LADAR data simulation for use in a multi sensor data fusion automated target recognition system. At present the main areas of application are in military environments but systems can easily be adapted to other areas such as security applications, robotics and autonomous cars. Recent developments have been away from traditional sensor modeling and toward modeling of features that are external to the system, such as atmosphere and part occlusion, to create a more realistic and rounded system. We have implemented such techniques and introduced a means of inserting these models into a highly detailed scene model to provide a rich data set for later processing. From our study and implementation we are able to embed sensor model components into a commercial graphics and animation package, along with object and terrain models, which can be easily used to create a more realistic sequence of images.

  19. Common and Innovative Visuals: A sparsity modeling framework for video.

    Science.gov (United States)

    Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

    2014-05-02

    Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

  20. Gaze inspired subtitle position evaluation for MOOCs videos

    Science.gov (United States)

    Chen, Hongli; Yan, Mengzhen; Liu, Sijiang; Jiang, Bo

    2017-06-01

    Online educational resources, such as MOOCs, is becoming increasingly popular, especially in higher education field. One most important media type for MOOCs is course video. Besides traditional bottom-position subtitle accompany to the videos, in recent years, researchers try to develop more advanced algorithms to generate speaker-following style subtitles. However, the effectiveness of such subtitle is still unclear. In this paper, we investigate the relationship between subtitle position and the learning effect after watching the video on tablet devices. Inspired with image based human eye tracking technique, this work combines the objective gaze estimation statistics with subjective user study to achieve a convincing conclusion - speaker-following subtitles are more suitable for online educational videos.

  1. 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.

  2. Tracking Success: Outputs Versus Outcomes-A Comparison of Accredited and Non-Accredited Public Health Agencies' Community Health Improvement Plan objectives.

    Science.gov (United States)

    Perrault, Evan K; Inderstrodt-Stephens, Jill; Hintz, Elizabeth A

    2018-06-01

    With funding for public health initiatives declining, creating measurable objectives that are focused on tracking and changing population outcomes (i.e., knowledge, attitudes, or behaviors), instead of those that are focused on health agencies' own outputs (e.g., promoting services, developing communication messages) have seen a renewed focus. This study analyzed 4094 objectives from the Community Health Improvement Plans (CHIPs) of 280 local PHAB-accredited and non-accredited public health agencies across the United States. Results revealed that accredited agencies were no more successful at creating outcomes-focused objectives (35% of those coded) compared to non-accredited agencies (33% of those coded; Z = 1.35, p = .18). The majority of objectives were focused on outputs (accredited: 61.2%; non-accredited: 63.3%; Z = 0.72, p = .47). Outcomes-focused objectives primarily sought to change behaviors (accredited: 85.43%; non-accredited: 80.6%), followed by changes in knowledge (accredited: 9.75%; non-accredited: 10.8%) and attitudes (accredited: 1.6%; non-accredited: 5.1%). Non-accredited agencies had more double-barreled objectives (49.9%) compared to accredited agencies (32%; Z = 11.43, p < .001). The authors recommend that accreditation procedures place a renewed focus on ensuring that public health agencies strive to achieve outcomes. It is also advocated that public health agencies work with interdisciplinary teams of Health Communicators who can help them develop procedures to effectively and efficiently measure outcomes of knowledge and attitudes that are influential drivers of behavioral changes.

  3. 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...

  4. Online Tracking of Outdoor Lighting Variations for Augmented Reality with Moving Cameras

    OpenAIRE

    Liu , Yanli; Granier , Xavier

    2012-01-01

    International audience; In augmented reality, one of key tasks to achieve a convincing visual appearance consistency between virtual objects and video scenes is to have a coherent illumination along the whole sequence. As outdoor illumination is largely dependent on the weather, the lighting condition may change from frame to frame. In this paper, we propose a full image-based approach for online tracking of outdoor illumination variations from videos captured with moving cameras. Our key ide...

  5. A video demonstration of preserved piloting by scent tracking but impaired dead reckoning after fimbria-fornix lesions in the rat.

    Science.gov (United States)

    Whishaw, Ian Q; Gorny, Boguslaw P

    2009-04-24

    ; Martin et al., 1997; Maaswinkel and Whishaw, 1999). The objective of the present video demonstrations was to solve the problem of cue specification in order to examine the relative contribution of the hippocampus in the use of these strategies. The rats were trained in a new task in which they followed linear or polygon scented trails to obtain a large food pellet hidden on an open field. Because rats have a proclivity to carry the food back to the refuge, accuracy and the cues used to return to the home base were dependent variables (Whishaw and Tomie, 1997). To force an animal to use a a dead reckoning strategy to reach its refuge with the food, the rats were tested when blindfolded or under infrared light, a spectral wavelength in which they cannot see, and in some experiments the scent trail was additionally removed once an animal reached the food. To examine the relative contribution of the hippocampus, fimbria-fornix (FF) lesions, which disrupt information flow in the hippocampal formation (Bland, 1986), impair memory (Gaffan and Gaffan, 1991), and produce spatial deficits (Whishaw and Jarrard, 1995), were used.

  6. 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.

  7. Video sensor architecture for surveillance applications.

    Science.gov (United States)

    Sánchez, Jordi; Benet, Ginés; Simó, José E

    2012-01-01

    This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

  8. Video Sensor Architecture for Surveillance Applications

    Directory of Open Access Journals (Sweden)

    José E. Simó

    2012-02-01

    Full Text Available This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

  9. Dashboard Videos

    Science.gov (United States)

    Gleue, Alan D.; Depcik, Chris; Peltier, Ted

    2012-01-01

    Last school year, I had a web link emailed to me entitled "A Dashboard Physics Lesson." The link, created and posted by Dale Basier on his "Lab Out Loud" blog, illustrates video of a car's speedometer synchronized with video of the road. These two separate video streams are compiled into one video that students can watch and analyze. After seeing…

  10. Is action video gaming related to sustained attention of adolescents?

    Science.gov (United States)

    Trisolini, Daniela Carmen; Petilli, Marco Alessandro; Daini, Roberta

    2018-05-01

    Over the past few years, an increasing number of studies have shown that playing action video games can have positive effects on tasks that involve attention and visuo-spatial cognition (e.g., visual search, enumeration tasks, tracking multiple objects). Although playing action video games can improve several cognitive functions, the intensive interaction with the exciting, challenging, intrinsically stimulating and perceptually appealing game environments may adversely affect other functions, including the ability to maintain attention when the level of stimulation is not as intense. This study investigated whether a relationship existed between action video gaming and sustained attention performance in a sample of 45 Italian teenagers. After completing a questionnaire about their video game habits, participants were divided into Action Video Game Player (AVGP) and Non-Action Video Game Player (NAVGP) groups and underwent cognitive tests. The results confirm previous findings of studies of AVGPs as they had significantly enhanced performance for instantly enumerating a set of items. Nevertheless, we found that the drop in performance over time, typical of a sustained attention task, was significantly greater in the AVGP compared with the NAVGP group. This result is consistent with our hypothesis and demonstrates a negative effect of playing action video games.

  11. Enhancing cognition with video games: a multiple game training study.

    Directory of Open Access Journals (Sweden)

    Adam C Oei

    Full Text Available Previous evidence points to a causal link between playing action video games and enhanced cognition and perception. However, benefits of playing other video games are under-investigated. We examined whether playing non-action games also improves cognition. Hence, we compared transfer effects of an action and other non-action types that required different cognitive demands.We instructed 5 groups of non-gamer participants to play one game each on a mobile device (iPhone/iPod Touch for one hour a day/five days a week over four weeks (20 hours. Games included action, spatial memory, match-3, hidden- object, and an agent-based life simulation. Participants performed four behavioral tasks before and after video game training to assess for transfer effects. Tasks included an attentional blink task, a spatial memory and visual search dual task, a visual filter memory task to assess for multiple object tracking and cognitive control, as well as a complex verbal span task. Action game playing eliminated attentional blink and improved cognitive control and multiple-object tracking. Match-3, spatial memory and hidden object games improved visual search performance while the latter two also improved spatial working memory. Complex verbal span improved after match-3 and action game training.Cognitive improvements were not limited to action game training alone and different games enhanced different aspects of cognition. We conclude that training specific cognitive abilities frequently in a video game improves performance in tasks that share common underlying demands. Overall, these results suggest that many video game-related cognitive improvements may not be due to training of general broad cognitive systems such as executive attentional control, but instead due to frequent utilization of specific cognitive processes during game play. Thus, many video game training related improvements to cognition may be attributed to near-transfer effects.

  12. Enhancing Cognition with Video Games: A Multiple Game Training Study

    Science.gov (United States)

    Oei, Adam C.; Patterson, Michael D.

    2013-01-01

    Background Previous evidence points to a causal link between playing action video games and enhanced cognition and perception. However, benefits of playing other video games are under-investigated. We examined whether playing non-action games also improves cognition. Hence, we compared transfer effects of an action and other non-action types that required different cognitive demands. Methodology/Principal Findings We instructed 5 groups of non-gamer participants to play one game each on a mobile device (iPhone/iPod Touch) for one hour a day/five days a week over four weeks (20 hours). Games included action, spatial memory, match-3, hidden- object, and an agent-based life simulation. Participants performed four behavioral tasks before and after video game training to assess for transfer effects. Tasks included an attentional blink task, a spatial memory and visual search dual task, a visual filter memory task to assess for multiple object tracking and cognitive control, as well as a complex verbal span task. Action game playing eliminated attentional blink and improved cognitive control and multiple-object tracking. Match-3, spatial memory and hidden object games improved visual search performance while the latter two also improved spatial working memory. Complex verbal span improved after match-3 and action game training. Conclusion/Significance Cognitive improvements were not limited to action game training alone and different games enhanced different aspects of cognition. We conclude that training specific cognitive abilities frequently in a video game improves performance in tasks that share common underlying demands. Overall, these results suggest that many video game-related cognitive improvements may not be due to training of general broad cognitive systems such as executive attentional control, but instead due to frequent utilization of specific cognitive processes during game play. Thus, many video game training related improvements to cognition may be

  13. Enhancing cognition with video games: a multiple game training study.

    Science.gov (United States)

    Oei, Adam C; Patterson, Michael D

    2013-01-01

    Previous evidence points to a causal link between playing action video games and enhanced cognition and perception. However, benefits of playing other video games are under-investigated. We examined whether playing non-action games also improves cognition. Hence, we compared transfer effects of an action and other non-action types that required different cognitive demands. We instructed 5 groups of non-gamer participants to play one game each on a mobile device (iPhone/iPod Touch) for one hour a day/five days a week over four weeks (20 hours). Games included action, spatial memory, match-3, hidden- object, and an agent-based life simulation. Participants performed four behavioral tasks before and after video game training to assess for transfer effects. Tasks included an attentional blink task, a spatial memory and visual search dual task, a visual filter memory task to assess for multiple object tracking and cognitive control, as well as a complex verbal span task. Action game playing eliminated attentional blink and improved cognitive control and multiple-object tracking. Match-3, spatial memory and hidden object games improved visual search performance while the latter two also improved spatial working memory. Complex verbal span improved after match-3 and action game training. Cognitive improvements were not limited to action game training alone and different games enhanced different aspects of cognition. We conclude that training specific cognitive abilities frequently in a video game improves performance in tasks that share common underlying demands. Overall, these results suggest that many video game-related cognitive improvements may not be due to training of general broad cognitive systems such as executive attentional control, but instead due to frequent utilization of specific cognitive processes during game play. Thus, many video game training related improvements to cognition may be attributed to near-transfer effects.

  14. Video microblogging

    DEFF Research Database (Denmark)

    Bornoe, Nis; Barkhuus, Louise

    2010-01-01

    Microblogging is a recently popular phenomenon and with the increasing trend for video cameras to be built into mobile phones, a new type of microblogging has entered the arena of electronic communication: video microblogging. In this study we examine video microblogging, which is the broadcasting...... of short videos. A series of semi-structured interviews offers an understanding of why and how video microblogging is used and what the users post and broadcast....

  15. 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

  16. 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.

  17. Video demystified

    CERN Document Server

    Jack, Keith

    2004-01-01

    This international bestseller and essential reference is the "bible" for digital video engineers and programmers worldwide. This is by far the most informative analog and digital video reference available, includes the hottest new trends and cutting-edge developments in the field. Video Demystified, Fourth Edition is a "one stop" reference guide for the various digital video technologies. The fourth edition is completely updated with all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video (Video over DSL, Ethernet, etc.), as well as discussions of the latest standards throughout. The accompanying CD-ROM is updated to include a unique set of video test files in the newest formats. *This essential reference is the "bible" for digital video engineers and programmers worldwide *Contains all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video *Completely revised with all the latest and most up-to-date industry standards.

  18. Video-Based Big Data Analytics in Cyberlearning

    Science.gov (United States)

    Wang, Shuangbao; Kelly, William

    2017-01-01

    In this paper, we present a novel system, inVideo, for video data analytics, and its use in transforming linear videos into interactive learning objects. InVideo is able to analyze video content automatically without the need for initial viewing by a human. Using a highly efficient video indexing engine we developed, the system is able to analyze…

  19. 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.

  20. Video pedagogy

    OpenAIRE

    Länsitie, Janne; Stevenson, Blair; Männistö, Riku; Karjalainen, Tommi; Karjalainen, Asko

    2016-01-01

    The short film is an introduction to the concept of video pedagogy. The five categories of video pedagogy further elaborate how videos can be used as a part of instruction and learning process. Most pedagogical videos represent more than one category. A video itself doesn’t necessarily define the category – the ways in which the video is used as a part of pedagogical script are more defining factors. What five categories did you find? Did you agree with the categories, or are more...

  1. 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.

  2. 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

  3. Nighttime vision-based car detection and tracking for smart road lighting system

    NARCIS (Netherlands)

    Matsiki, D.; Shrestha, P.; With, de P.H.N.

    2011-01-01

    The objective of this paper is to detect cars in nighttime videos for controlling the illumination of level of road lights, thereby saving power consumption. We present an e??ective method to detect and track cars based on the presence of head lights or rear lights. We detect the headlights and rear

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Adaptive and accelerated tracking-learning-detection

    Science.gov (United States)

    Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

    2013-08-01

    An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

  9. A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network

    Science.gov (United States)

    Li, Yiming; Bhanu, Bir

    Video networks are becoming increasingly important for solving many real-world problems. Multiple video sensors require collaboration when performing various tasks. One of the most basic tasks is the tracking of objects, which requires mechanisms to select a camera for a certain object and hand-off this object from one camera to another so as to accomplish seamless tracking. In this chapter, we provide a comprehensive comparison of current and emerging camera selection and hand-off techniques. We consider geometry-, statistics-, and game theory-based approaches and provide both theoretical and experimental comparison using centralized and distributed computational models. We provide simulation and experimental results using real data for various scenarios of a large number of cameras and objects for in-depth understanding of strengths and weaknesses of these techniques.

  10. Seguimiento del contorno externo de la boca en imágenes de vídeo Outer Lip contour tracking in video images

    Directory of Open Access Journals (Sweden)

    Alexánder Ceballos

    2009-01-01

    Full Text Available El seguimiento preciso de la boca de una persona, cuando está hablando, es un desafío importante en varias aplicaciones, como la identificación de la cara o la interacción con el computador. La complejidad de forma, textura y color de la boca, y los cambios de iluminación y fondos de los posibles escenarios hacen que este sea aún un problema abierto. En este artículo se propone un algoritmo para el seguimiento del contorno externo de la boca, sin utilizar marcadores o alguna clase de maquillaje para resaltar los labios, basado en apariencia y en restricciones morfológicas definidas en el estándar MPEG-4. El algoritmo es robusto ante la presencia de barba, tono de piel y calidad de la imagen.An accurate tracking of a person's mouth when he/she is speaking is an important challenge in several applications such as face identification or interaction with computer. Complexity of shape, texture, and color of the mouth, as well as changes in lighting and backgrounds of possible scenarios makes of it an open problem yet. This article proposed an algorithm for a tracking of the mouth external contour without using markers or any kind of make-up for highlighting lips, based on appearance and morphological restrictions defined by the MPEG-4 Standard. Algorithm is robust before the presence of beard, skin tone, and image quality.

  11. Feasibility Study On Missile Launch Detection And Trajectory Tracking

    Science.gov (United States)

    2016-09-01

    Feature (SURF) detection, and Kalman filtering are frequently used for object tracking. These methods have been applied frequently on video records...missile by processing the thermal imagery from the thermal-imaging sensor, which captures the temperature gradient of the surroundings within its field of...view. As the missile’s propulsion motor emits gases at high temperature to generate the thrust required for its flight, the heat 2 signature of

  12. 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

  13. Assisting doctors on assessing movements in infants using motion tracking

    DEFF Research Database (Denmark)

    Olsen, Mikkel; Herskind, Anna; Nielsen, Jens Bo

    2015-01-01

    In this work, we consider the possibilities of having an automatic computer-based system for tracking the movements of infants. An existing motion tracking system is used to process recorded video sequences containing both color and spatial information of the infant's body pose and movements....... The system uses these sequences of data to estimate the underlying skeleton of the infant and parametrize the movements. Post-processing of these parameters can yield objective measurements of an infant's movement patterns. This could e.g. be quantification of (a)symmetry and recognition of certain gestures/actions...

  14. DCS Budget Tracking System

    Data.gov (United States)

    Social Security Administration — DCS Budget Tracking System database contains budget information for the Information Technology budget and the 'Other Objects' budget. This data allows for monitoring...

  15. Camera network video summarization

    Science.gov (United States)

    Panda, Rameswar; Roy-Chowdhury, Amit K.

    2017-05-01

    Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

  16. Immersive video

    Science.gov (United States)

    Moezzi, Saied; Katkere, Arun L.; Jain, Ramesh C.

    1996-03-01

    Interactive video and television viewers should have the power to control their viewing position. To make this a reality, we introduce the concept of Immersive Video, which employs computer vision and computer graphics technologies to provide remote users a sense of complete immersion when viewing an event. Immersive Video uses multiple videos of an event, captured from different perspectives, to generate a full 3D digital video of that event. That is accomplished by assimilating important information from each video stream into a comprehensive, dynamic, 3D model of the environment. Using this 3D digital video, interactive viewers can then move around the remote environment and observe the events taking place from any desired perspective. Our Immersive Video System currently provides interactive viewing and `walkthrus' of staged karate demonstrations, basketball games, dance performances, and typical campus scenes. In its full realization, Immersive Video will be a paradigm shift in visual communication which will revolutionize television and video media, and become an integral part of future telepresence and virtual reality systems.

  17. 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%.

  18. The effects of video game playing on attention, memory, and executive control.

    Science.gov (United States)

    Boot, Walter R; Kramer, Arthur F; Simons, Daniel J; Fabiani, Monica; Gratton, Gabriele

    2008-11-01

    Expert video game players often outperform non-players on measures of basic attention and performance. Such differences might result from exposure to video games or they might reflect other group differences between those people who do or do not play video games. Recent research has suggested a causal relationship between playing action video games and improvements in a variety of visual and attentional skills (e.g., [Green, C. S., & Bavelier, D. (2003). Action video game modifies visual selective attention. Nature, 423, 534-537]). The current research sought to replicate and extend these results by examining both expert/non-gamer differences and the effects of video game playing on tasks tapping a wider range of cognitive abilities, including attention, memory, and executive control. Non-gamers played 20+ h of an action video game, a puzzle game, or a real-time strategy game. Expert gamers and non-gamers differed on a number of basic cognitive skills: experts could track objects moving at greater speeds, better detected changes to objects stored in visual short-term memory, switched more quickly from one task to another, and mentally rotated objects more efficiently. Strikingly, extensive video game practice did not substantially enhance performance for non-gamers on most cognitive tasks, although they did improve somewhat in mental rotation performance. Our results suggest that at least some differences between video game experts and non-gamers in basic cognitive performance result either from far more extensive video game experience or from pre-existing group differences in abilities that result in a self-selection effect.

  19. Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

    Science.gov (United States)

    Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

    2017-03-01

    Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task

  20. Video games

    OpenAIRE

    Kolář, Vojtěch

    2012-01-01

    This thesis is based on a detailed analysis of various topics related to the question of whether video games can be art. In the first place it analyzes the current academic discussion on this subject and confronts different opinions of both supporters and objectors of the idea, that video games can be a full-fledged art form. The second point of this paper is to analyze the properties, that are inherent to video games, in order to find the reason, why cultural elite considers video games as i...

  1. 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.

  2. 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...

  3. 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

  4. Akademisk video

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2017-01-01

    Dette kapitel har fokus på metodiske problemstillinger, der opstår i forhold til at bruge (digital) video i forbindelse med forskningskommunikation, ikke mindst online. Video har længe været benyttet i forskningen til dataindsamling og forskningskommunikation. Med digitaliseringen og internettet ...

  5. 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.

  6. Toy Trucks in Video Analysis

    DEFF Research Database (Denmark)

    Buur, Jacob; Nakamura, Nanami; Larsen, Rainer Rye

    2015-01-01

    discovered that using scale-models like toy trucks has a strongly encouraging effect on developers/designers to collaboratively make sense of field videos. In our analysis of such scale-model sessions, we found some quite fundamental patterns of how participants utilise objects; the participants build shared......Video fieldstudies of people who could be potential users is widespread in design projects. How to analyse such video is, however, often challenging, as it is time consuming and requires a trained eye to unlock experiential knowledge in people’s practices. In our work with industrialists, we have...... narratives by moving the objects around, they name them to handle the complexity, they experience what happens in the video through their hands, and they use the video together with objects to create alternative narratives, and thus alternative solutions to the problems they observe. In this paper we claim...

  7. Motion-Blur-Free High-Speed Video Shooting Using a Resonant Mirror

    Directory of Open Access Journals (Sweden)

    Michiaki Inoue

    2017-10-01

    Full Text Available This study proposes a novel concept of actuator-driven frame-by-frame intermittent tracking for motion-blur-free video shooting of fast-moving objects. The camera frame and shutter timings are controlled for motion blur reduction in synchronization with a free-vibration-type actuator vibrating with a large amplitude at hundreds of hertz so that motion blur can be significantly reduced in free-viewpoint high-frame-rate video shooting for fast-moving objects by deriving the maximum performance of the actuator. We develop a prototype of a motion-blur-free video shooting system by implementing our frame-by-frame intermittent tracking algorithm on a high-speed video camera system with a resonant mirror vibrating at 750 Hz. It can capture 1024 × 1024 images of fast-moving objects at 750 fps with an exposure time of 0.33 ms without motion blur. Several experimental results for fast-moving objects verify that our proposed method can reduce image degradation from motion blur without decreasing the camera exposure time.

  8. 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.

  9. An algorithm to track laboratory zebrafish shoals.

    Science.gov (United States)

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

    2018-05-01

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

  10. Video Podcasts

    DEFF Research Database (Denmark)

    Nortvig, Anne Mette; Sørensen, Birgitte Holm

    2016-01-01

    This project’s aim was to support and facilitate master’s students’ preparation and collaboration by making video podcasts of short lectures available on YouTube prior to students’ first face-to-face seminar. The empirical material stems from group interviews, from statistical data created through...... YouTube analytics and from surveys answered by students after the seminar. The project sought to explore how video podcasts support learning and reflection online and how students use and reflect on the integration of online activities in the videos. Findings showed that students engaged actively...

  11. Video games.

    Science.gov (United States)

    Funk, Jeanne B

    2005-06-01

    The video game industry insists that it is doing everything possible to provide information about the content of games so that parents can make informed choices; however, surveys indicate that ratings may not reflect consumer views of the nature of the content. This article describes some of the currently popular video games, as well as developments that are on the horizon, and discusses the status of research on the positive and negative impacts of playing video games. Recommendations are made to help parents ensure that children play games that are consistent with their values.

  12. Real and virtual explorations of the environment and interactive tracking of movable objects for the blind on the basis of tactile-acoustical maps and 3D environment models.

    Science.gov (United States)

    Hub, Andreas; Hartter, Tim; Kombrink, Stefan; Ertl, Thomas

    2008-01-01

    PURPOSE.: This study describes the development of a multi-functional assistant system for the blind which combines localisation, real and virtual navigation within modelled environments and the identification and tracking of fixed and movable objects. The approximate position of buildings is determined with a global positioning sensor (GPS), then the user establishes exact position at a specific landmark, like a door. This location initialises indoor navigation, based on an inertial sensor, a step recognition algorithm and map. Tracking of movable objects is provided by another inertial sensor and a head-mounted stereo camera, combined with 3D environmental models. This study developed an algorithm based on shape and colour to identify objects and used a common face detection algorithm to inform the user of the presence and position of others. The system allows blind people to determine their position with approximately 1 metre accuracy. Virtual exploration of the environment can be accomplished by moving one's finger on a touch screen of a small portable tablet PC. The name of rooms, building features and hazards, modelled objects and their positions are presented acoustically or in Braille. Given adequate environmental models, this system offers blind people the opportunity to navigate independently and safely, even within unknown environments. Additionally, the system facilitates education and rehabilitation by providing, in several languages, object names, features and relative positions.

  13. Minimum Delay Moving Object Detection

    KAUST Repository

    Lao, Dong; Sundaramoorthi, Ganesh

    2017-01-01

    We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon

  14. Small Orbital Stereo Tracking Camera Technology Development

    Science.gov (United States)

    Gagliano, L.; Bryan, T.; MacLeod, T.

    On-Orbit Small Debris Tracking and Characterization is a technical gap in the current National Space Situational Awareness necessary to safeguard orbital assets and crew. This poses a major risk of MOD damage to ISS and Exploration vehicles. In 2015 this technology was added to NASAs Office of Chief Technologist roadmap. For missions flying in or assembled in or staging from LEO, the physical threat to vehicle and crew is needed in order to properly design the proper level of MOD impact shielding and proper mission design restrictions. Need to verify debris flux and size population versus ground RADAR tracking. Use of ISS for In-Situ Orbital Debris Tracking development provides attitude, power, data and orbital access without a dedicated spacecraft or restricted operations on-board a host vehicle as a secondary payload. Sensor Applicable to in-situ measuring orbital debris in flux and population in other orbits or on other vehicles. Could enhance safety on and around ISS. Some technologies extensible to monitoring of extraterrestrial debris as well To help accomplish this, new technologies must be developed quickly. The Small Orbital Stereo Tracking Camera is one such up and coming technology. It consists of flying a pair of intensified megapixel telephoto cameras to evaluate Orbital Debris (OD) monitoring in proximity of International Space Station. It will demonstrate on-orbit optical tracking (in situ) of various sized objects versus ground RADAR tracking and small OD models. The cameras are based on Flight Proven Advanced Video Guidance Sensor pixel to spot algorithms (Orbital Express) and military targeting cameras. And by using twin cameras we can provide Stereo images for ranging & mission redundancy. When pointed into the orbital velocity vector (RAM), objects approaching or near the stereo camera set can be differentiated from the stars moving upward in background.

  15. Camera Networks The Acquisition and Analysis of Videos over Wide Areas

    CERN Document Server

    Roy-Chowdhury, Amit K

    2012-01-01

    As networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important area of research and technology development. There are many challenges that need to be addressed in the process. Some of them are listed below: - Traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter, recognition of objects, and activities; - Aggregating local information for wide

  16. Video Comparator

    International Nuclear Information System (INIS)

    Rose, R.P.

    1978-01-01

    The Video Comparator is a comparative gage that uses electronic images from two sources, a standard and an unknown. Two matched video cameras are used to obtain the electronic images. The video signals are mixed and displayed on a single video receiver (CRT). The video system is manufactured by ITP of Chatsworth, CA and is a Tele-Microscope II, Model 148. One of the cameras is mounted on a toolmaker's microscope stand and produces a 250X image of a cast. The other camera is mounted on a stand and produces an image of a 250X template. The two video images are mixed in a control box provided by ITP and displayed on a CRT. The template or the cast can be moved to align the desired features. Vertical reference lines are provided on the CRT, and a feature on the cast can be aligned with a line on the CRT screen. The stage containing the casts can be moved using a Boeckleler micrometer equipped with a digital readout, and a second feature aligned with the reference line and the distance moved obtained from the digital display

  17. 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.

  18. Modeling self-occlusions in dynamic shape and appearance tracking

    KAUST Repository

    Yang, Yanchao

    2013-12-01

    We present a method to track the precise shape of a dynamic object in video. Joint dynamic shape and appearance models, in which a template of the object is propagated to match the object shape and radiance in the next frame, are advantageous over methods employing global image statistics in cases of complex object radiance and cluttered background. In cases of complex 3D object motion and relative viewpoint change, self-occlusions and disocclusions of the object are prominent, and current methods employing joint shape and appearance models are unable to accurately adapt to new shape and appearance information, leading to inaccurate shape detection. In this work, we model self-occlusions and dis-occlusions in a joint shape and appearance tracking framework. Experiments on video exhibiting occlusion/dis-occlusion, complex radiance and background show that occlusion/dis-occlusion modeling leads to superior shape accuracy compared to recent methods employing joint shape/appearance models or employing global statistics. © 2013 IEEE.

  19. Combating bad weather part I rain removal from video

    CERN Document Server

    Mukhopadhyay, Sudipta

    2015-01-01

    Current vision systems are designed to perform in normal weather condition. However, no one can escape from severe weather conditions. Bad weather reduces scene contrast and visibility, which results in degradation in the performance of various computer vision algorithms such as object tracking, segmentation and recognition. Thus, current vision systems must include some mechanisms that enable them to perform up to the mark in bad weather conditions such as rain and fog. Rain causes the spatial and temporal intensity variations in images or video frames. These intensity changes are due to the

  20. A robust approach towards unknown transformation, regional adjacency graphs, multigraph matching, segmentation video frames from unnamed aerial vehicles (UAV)

    Science.gov (United States)

    Gohatre, Umakant Bhaskar; Patil, Venkat P.

    2018-04-01

    In computer vision application, the multiple object detection and tracking, in real-time operation is one of the important research field, that have gained a lot of attentions, in last few years for finding non stationary entities in the field of image sequence. The detection of object is advance towards following the moving object in video and then representation of object is step to track. The multiple object recognition proof is one of the testing assignment from detection multiple objects from video sequence. The picture enrollment has been for quite some time utilized as a reason for the location the detection of moving multiple objects. The technique of registration to discover correspondence between back to back casing sets in view of picture appearance under inflexible and relative change. The picture enrollment is not appropriate to deal with event occasion that can be result in potential missed objects. In this paper, for address such problems, designs propose novel approach. The divided video outlines utilizing area adjancy diagram of visual appearance and geometric properties. Then it performed between graph sequences by using multi graph matching, then getting matching region labeling by a proposed graph coloring algorithms which assign foreground label to respective region. The plan design is robust to unknown transformation with significant improvement in overall existing work which is related to moving multiple objects detection in real time parameters.