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Sample records for video object tracking

  1. 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),

  2. 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

  3. A data set for evaluating the performance of multi-class multi-object video tracking

    OpenAIRE

    Chakraborty, Avishek; Stamatescu, Victor; Wong, Sebastien C.; Wigley, Grant; Kearney, David

    2017-01-01

    One of the challenges in evaluating multi-object video detection, tracking and classification systems is having publically available data sets with which to compare different systems. However, the measures of performance for tracking and classification are different. Data sets that are suitable for evaluating tracking systems may not be appropriate for classification. Tracking video data sets typically only have ground truth track IDs, while classification video data sets only have ground tru...

  4. Video Object Tracking in Neural Axons with Fluorescence Microscopy Images

    Directory of Open Access Journals (Sweden)

    Liang Yuan

    2014-01-01

    tracking. In this paper, we describe two automated tracking methods for analyzing neurofilament movement based on two different techniques: constrained particle filtering and tracking-by-detection. First, we introduce the constrained particle filtering approach. In this approach, the orientation and position of a particle are constrained by the axon’s shape such that fewer particles are necessary for tracking neurofilament movement than object tracking techniques based on generic particle filtering. Secondly, a tracking-by-detection approach to neurofilament tracking is presented. For this approach, the axon is decomposed into blocks, and the blocks encompassing the moving neurofilaments are detected by graph labeling using Markov random field. Finally, we compare two tracking methods by performing tracking experiments on real time-lapse image sequences of neurofilament movement, and the experimental results show that both methods demonstrate good performance in comparison with the existing approaches, and the tracking accuracy of the tracing-by-detection approach is slightly better between the two.

  5. Object Tracking in Frame-Skipping Video Acquired Using Wireless Consumer Cameras

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    Anlong Ming

    2012-10-01

    Full Text Available Object tracking is an important and fundamental task in computer vision and its high-level applications, e.g., intelligent surveillance, motion-based recognition, video indexing, traffic monitoring and vehicle navigation. However, the recent widespread use of wireless consumer cameras often produces low quality videos with frame-skipping and this makes object tracking difficult. Previous tracking methods, for example, generally depend heavily on object appearance or motion continuity and cannot be directly applied to frame-skipping videos. In this paper, we propose an improved particle filter for object tracking to overcome the frame-skipping difficulties. The novelty of our particle filter lies in using the detection result of erratic motion to ameliorate the transition model for a better trial distribution. Experimental results show that the proposed approach improves the tracking accuracy in comparison with the state-of-the-art methods, even when both the object and the consumer are in motion.

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

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    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

  7. A data set for evaluating the performance of multi-class multi-object video tracking

    Science.gov (United States)

    Chakraborty, Avishek; Stamatescu, Victor; Wong, Sebastien C.; Wigley, Grant; Kearney, David

    2017-05-01

    One of the challenges in evaluating multi-object video detection, tracking and classification systems is having publically available data sets with which to compare different systems. However, the measures of performance for tracking and classification are different. Data sets that are suitable for evaluating tracking systems may not be appropriate for classification. Tracking video data sets typically only have ground truth track IDs, while classification video data sets only have ground truth class-label IDs. The former identifies the same object over multiple frames, while the latter identifies the type of object in individual frames. This paper describes an advancement of the ground truth meta-data for the DARPA Neovision2 Tower data set to allow both the evaluation of tracking and classification. The ground truth data sets presented in this paper contain unique object IDs across 5 different classes of object (Car, Bus, Truck, Person, Cyclist) for 24 videos of 871 image frames each. In addition to the object IDs and class labels, the ground truth data also contains the original bounding box coordinates together with new bounding boxes in instances where un-annotated objects were present. The unique IDs are maintained during occlusions between multiple objects or when objects re-enter the field of view. This will provide: a solid foundation for evaluating the performance of multi-object tracking of different types of objects, a straightforward comparison of tracking system performance using the standard Multi Object Tracking (MOT) framework, and classification performance using the Neovision2 metrics. These data have been hosted publically.

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

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    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.

  9. Uncertainty-aware video visual analytics of tracked moving objects

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    Markus Höferlin

    2011-01-01

    Full Text Available Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues, we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration, hypotheses generation, and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG for visualization and enable users to provide filter-based relevance feedback. Additionally, users are supported in deriving hypotheses by context-sensitive statistical graphics. To allow for reliable decision making, we gather uncertainties introduced by the computer vision step, communicate these information to users through uncertainty visualization, and grant fuzzy hypothesis formulation to interact with the machine. Finally, we demonstrate the effectiveness of our approach by the video analysis mini challenge which was part of the IEEE Symposium on Visual Analytics Science and Technology 2009.

  10. Uncertainty-aware video visual analytics of tracked moving objects

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    Markus Höferlin

    1969-12-01

    Full Text Available Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues, we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration, hypotheses generation, and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG for visualization and enable users to provide filter-based relevance feedback. Additionally, users are supported in deriving hypotheses by context-sensitive statistical graphics. To allow for reliable decision making, we gather uncertainties introduced by the computer vision step, communicate these information to users through uncertainty visualization, and grant fuzzy hypothesis formulation to interact with the machine. Finally, we demonstrate the effectiveness of our approach by the video analysis mini challenge which was part of the IEEE Symposium on Visual Analytics Science and Technology 2009.

  11. The research of moving objects behavior detection and tracking algorithm in aerial video

    Science.gov (United States)

    Yang, Le-le; Li, Xin; Yang, Xiao-ping; Li, Dong-hui

    2015-12-01

    The article focuses on the research of moving target detection and tracking algorithm in Aerial monitoring. Study includes moving target detection, moving target behavioral analysis and Target Auto tracking. In moving target detection, the paper considering the characteristics of background subtraction and frame difference method, using background reconstruction method to accurately locate moving targets; in the analysis of the behavior of the moving object, using matlab technique shown in the binary image detection area, analyzing whether the moving objects invasion and invasion direction; In Auto Tracking moving target, A video tracking algorithm that used the prediction of object centroids based on Kalman filtering was proposed.

  12. Multiscale Architectures and Parallel Algorithms for Video Object Tracking

    Science.gov (United States)

    2011-10-01

    Black River Systems. This may have inadvertently introduced bugs that were later discovered by AFRL during testing (of the June 22, 2011 version of...Parallelism in Algorithms and Architectures, pages 289–298, 2007. [3] S. Ali and M. Shah. COCOA - Tracking in aerial imagery. In Daniel J. Henry

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

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    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%.

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

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    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 .

  15. Tracking of Moving Objects in Video Through Invariant Features in Their Graph Representation

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    Averbuch A

    2008-01-01

    Full Text Available Abstract The paper suggests a contour-based algorithm for tracking moving objects in video. The inputs are segmented moving objects. Each segmented frame is transformed into region adjacency graphs (RAGs. The object's contour is divided into subcurves. Contour's junctions are derived. These junctions are the unique “signature� of the tracked object. Junctions from two consecutive frames are matched. The junctions' motion is estimated using RAG edges in consecutive frames. Each pair of matched junctions may be connected by several paths (edges that become candidates that represent a tracked contour. These paths are obtained by the -shortest paths algorithm between two nodes. The RAG is transformed into a weighted directed graph. The final tracked contour construction is derived by a match between edges (subcurves and candidate paths sets. The RAG constructs the tracked contour that enables an accurate and unique moving object representation. The algorithm tracks multiple objects, partially covered (occluded objects, compounded object of merge/split such as players in a soccer game and tracking in a crowded area for surveillance applications. We assume that features of topologic signature of the tracked object stay invariant in two consecutive frames. The algorithm's complexity depends on RAG's edges and not on the image's size.

  16. Detection and objects tracking present in 2D digital video with Matlab

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    Melvin Ramírez Bogantes

    2013-09-01

    Full Text Available This paper presents the main results of research obtained in the design of an algorithm to detect and track an object in a video recording. The algorithm was designed in MatLab software and the videos used, which  presence of the mite Varroa Destructor in the cells of Africanized Honey Bees, were provided by the Centro de Investigación Apícola Tropical (CINAT-UNA.  The main result is the creation of a program capable of detecting and recording the movement of the mite, this is something innovative and useful for studies of the behavior of this species in the cells of honey bees performing the CINAT.

  17. Straightforward multi-object video tracking for quantification of mosquito flight activity.

    Science.gov (United States)

    Wilkinson, David A; Lebon, Cyrille; Wood, Trevor; Rosser, Gabriel; Gouagna, Louis Clément

    2014-12-01

    Mosquito flight activity has been studied using a variety of different methodologies, and largely concentrates on female mosquito activity as vectors of disease. Video recording using standard commercially available hardware has limited accuracy for the measurement of flight activity due to the lack of depth-perception in two-dimensional images, but multi-camera observation for three dimensional trajectory reconstructions remain challenging and inaccessible to the majority of researchers. Here, in silico simulations were used to quantify the limitations of two-dimensional flight observation. We observed that, under the simulated conditions, two dimensional observation of flight was more than 90% accurate for the determination of population flight speeds and thus that two dimensional imaging can be used to provide accurate estimates of mosquito population flight speeds, and to measure flight activity over long periods of time. We optimized single camera video imaging to study male Aedes albopictus mosquitoes over a 30 h time period, and tested two different multi-object tracking algorithms for their efficiency in flight tracking. A. Albopictus males were observed to be most active at the start of the day period (06h00-08h00) with the longest period of activity in the evening (15h00-18h00) and that a single mosquito will fly more than 600 m over the course of 24 h. No activity was observed during the night period (18h00-06h00). Simplistic tracking methodologies, executable on standard computational hardware, are sufficient to produce reliable data when video imaging is optimized under laboratory conditions. As this methodology does not require overly-expensive equipment, complex calibration of equipment or extensive knowledge of computer programming, the technology should be accessible to the majority of computer-literate researchers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Bayesian Tracking of Visual Objects

    Science.gov (United States)

    Zheng, Nanning; Xue, Jianru

    Tracking objects in image sequences involves performing motion analysis at the object level, which is becoming an increasingly important technology in a wide range of computer video applications, including video teleconferencing, security and surveillance, video segmentation, and editing. In this chapter, we focus on sequential Bayesian estimation techniques for visual tracking. We first introduce the sequential Bayesian estimation framework, which acts as the theoretic basis for visual tracking. Then, we present approaches to constructing representation models for specific objects.

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

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    Arran T Reader

    2015-05-01

    Full Text Available 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 versus 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.

  20. Gamifying Video Object Segmentation.

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    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. ANNOTATION SUPPORTED OCCLUDED OBJECT TRACKING

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    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.

  2. Robust video object cosegmentation.

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    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).

  3. Register indicators of physical endurance of biological objects when running a treadmill and swimming with weights using computer video markerless tracking

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    Datsenko A.V.

    2014-12-01

    Full Text Available Purpose: to study the use of video tracking to assess physical endurance and indicators of biological objects fatigue when running on a treadmill and swimming with the load. Material and methods. Physical endurance evaluated by test facilities for running on a treadmill and swimming with the load. As the object of the studies used laboratory rats. Results. For indicators of physical endurance biological objects isolated areas running track of treadmill and electrical stimulation site, when swimming on the total area of the container isolated subarea near the water surface. With video tracking performed computer timing of finding biological object in different zones of the treadmill and containers for swimming. On the basis of data on the time location rats in a given zone apparatus for running and swimming, obtained in the dynamics of the test of physical endurance, build a "fatigue curves", quantified changes in the indices of hard work, depending on the duration of its execution. Conclusion. Video tracking allows to define the execution of physical work to overflowing with loads of aerobic and mixed aerobic-anaerobic power, establish quantitative indicators of changes in the dynamics of biological objects operability testing with the construction of "fatigue curve" and objectively determine the times of occurrence in experimental animals exhaustion when fails to perform physical work.

  4. GPS-Aided Video Tracking

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    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.

  5. Object tracking with stereo vision

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    Huber, Eric

    1994-01-01

    A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking.

  6. 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.

  7. Video Tracking dalam Digital Compositing untuk Paska Produksi Video

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    Ardiyan Ardiyan

    2012-04-01

    Full Text Available Video Tracking is one of the processes in video postproduction and motion picture digitally. The ability of video tracking method in the production is helpful to realize the concept of the visual. It is considered in the process of visual effects making. This paper presents how the tracking process and its benefits in visual needs, especially for video and motion picture production. Some of the things involved in the process of tracking such as failure to do so are made clear in this discussion. 

  8. Object Tracking by Oversampling Local Features.

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    Pernici, Federico; Del Bimbo, Alberto

    2014-12-01

    In this paper, we present the ALIEN tracking method that exploits oversampling of local invariant representations to build a robust object/context discriminative classifier. To this end, we use multiple instances of scale invariant local features weakly aligned along the object template. This allows taking into account the 3D shape deviations from planarity and their interactions with shadows, occlusions, and sensor quantization for which no invariant representations can be defined. A non-parametric learning algorithm based on the transitive matching property discriminates the object from the context and prevents improper object template updating during occlusion. We show that our learning rule has asymptotic stability under mild conditions and confirms the drift-free capability of the method in long-term tracking. A real-time implementation of the ALIEN tracker has been evaluated in comparison with the state-of-the-art tracking systems on an extensive set of publicly available video sequences that represent most of the critical conditions occurring in real tracking environments. We have reported superior or equal performance in most of the cases and verified tracking with no drift in very long video sequences.

  9. Face Recognition and Tracking in Videos

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    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.

  10. An object tracking algorithm with embedded gyro information

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    Zhang, Yutong; Yan, Ding; Yuan, Yating

    2017-01-01

    The high speed attitude maneuver of Unmanned Aerial Vehicle (UAV) always causes large motion between adjacent frames of the video stream produced from the camera fixed on the UAV body, which will severely disrupt the performance of image object tracking process. To solve this problem, this paper proposes a method that using a gyroscope fixed on the camera to measure the angular velocity of camera, and then the object position's substantial change in the video stream is predicted. We accomplished the object tracking based on template matching. Experimental result shows that the object tracking algorithm's performance is improved in its efficiency and robustness with embedded gyroscope information.

  11. Differential geometry measures of nonlinearity for the video tracking problem

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    Mallick, Mahendra; La Scala, Barbara F.

    2006-05-01

    Tracking people and vehicles in an urban environment using video cameras onboard unmanned aerial vehicles has drawn a great deal of interest in recent years due to their low cost compared with expensive radar systems. Video cameras onboard a number of small UAVs can provide inexpensive, effective, and highly flexible airborne intelligence, surveillance and reconnaissance as well as situational awareness functions. The perspective transformation is a commonly used general measurement model for the video camera when the variation in terrain height in the object scene is not negligible and the distance between the camera and the scene is not large. The perspective transformation is a nonlinear function of the object position. Most video tracking applications use a nearly constant velocity model (NCVM) of the target in the local horizontal plane. The filtering problem is nonlinear due to nonlinearity in the measurement model. In this paper, we present algorithms for quantifying the degree of nonlinearity (DoN) by calculating the differential geometry based parameter-effects curvature and intrinsic curvature measures of nonlinearity for the video tracking problem. We use the constant velocity model (CVM) of a target in 2D with simulated video measurements in the image plane. We have presented preliminary results using 200 Monte Carlo simulations and future work will focus on detailed numerical results. Our results for the chosen video tracking problem indicate that the DoN is low and therefore, we expect the extended Kalman filter to be reasonable choice.

  12. Robust Feedback Zoom Tracking for Digital Video Surveillance

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    Jin Wang

    2012-06-01

    Full Text Available 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.

  13. Tracking in Object Action Space

    DEFF Research Database (Denmark)

    Krüger, Volker; Herzog, Dennis

    2013-01-01

    In this paper we focus on the joint problem of tracking humans and recognizing human action in scenarios such as a kitchen scenario or a scenario where a robot cooperates with a human, e.g., for a manufacturing task. In these scenarios, the human directly interacts with objects physically by using......-dimensional action space. In our approach, we use parametric hidden Markov models to represent parametric movements; particle filtering is used to track in the space of action parameters. We demonstrate its effectiveness on synthetic and on real image sequences using human-upper body single arm actions that involve...

  14. Video temporal alignment for object viewpoint

    OpenAIRE

    Papazoglou, Anestis; Del Pero, Luca; Ferrari, Vittorio

    2017-01-01

    We address the problem of temporally aligning semantically similar videos, for example two videos of cars on different tracks. We present an alignment method that establishes frame-to-frame correspondences such that the two cars are seen from a similar viewpoint (e.g. facing right), while also being temporally smooth and visually pleasing. Unlike previous works, we do not assume that the videos show the same scripted sequence of events. We compare against three alternative methods, including ...

  15. 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....

  16. 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...

  17. 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.

  18. Learning to Segment Moving Objects in Videos

    OpenAIRE

    Fragkiadaki, Katerina; Arbelaez, Pablo; Felsen, Panna; Malik, Jitendra

    2014-01-01

    We segment moving objects in videos by ranking spatio-temporal segment proposals according to "moving objectness": how likely they are to contain a moving object. In each video frame, we compute segment proposals using multiple figure-ground segmentations on per frame motion boundaries. We rank them with a Moving Objectness Detector trained on image and motion fields to detect moving objects and discard over/under segmentations or background parts of the scene. We extend the top ranked segmen...

  19. VORTEX: video retrieval and tracking from compressed multimedia databases--template matching from MPEG-2 video compression standard

    Science.gov (United States)

    Schonfeld, Dan; Lelescu, Dan

    1998-10-01

    In this paper, a novel visual search engine for video retrieval and tracking from compressed multimedia databases is proposed. Our approach exploits the structure of video compression standards in order to perform object matching directly on the compressed video data. This is achieved by utilizing motion compensation--a critical prediction filter embedded in video compression standards--to estimate and interpolate the desired method for template matching. Motion analysis is used to implement fast tracking of objects of interest on the compressed video data. Being presented with a query in the form of template images of objects, the system operates on the compressed video in order to find the images or video sequences where those objects are presented and their positions in the image. This in turn enables the retrieval and display of the query-relevant sequences.

  20. Timeline editing of objects in video.

    Science.gov (United States)

    Lu, Shao-Ping; Zhang, Song-Hai; Wei, Jin; Hu, Shi-Min; Martin, Ralph R

    2013-07-01

    We present a video editing technique based on changing the timelines of individual objects in video, which leaves them in their original places but puts them at different times. This allows the production of object-level slow motion effects, fast motion effects, or even time reversal. This is more flexible than simply applying such effects to whole frames, as new relationships between objects can be created. As we restrict object interactions to the same spatial locations as in the original video, our approach can produce highquality results using only coarse matting of video objects. Coarse matting can be done efficiently using automatic video object segmentation, avoiding tedious manual matting. To design the output, the user interactively indicates the desired new life spans of objects, and may also change the overall running time of the video. Our method rearranges the timelines of objects in the video whilst applying appropriate object interaction constraints. We demonstrate that, while this editing technique is somewhat restrictive, it still allows many interesting results.

  1. Target detection and tracking in infrared video

    Science.gov (United States)

    Deng, Zhihui; Zhu, Jihong

    2017-07-01

    In this paper, we propose a method for target detection and tracking in infrared video. The target is defined by its location and extent in a single frame. In the initialization process, we use an adaptive threshold to segment the target and then extract the fern feature and normalize it as a template. The detector uses the random forest and fern to detect the target in the infrared video. The random forest and fern is a random combination of 2bit Binary Pattern, which is robust to infrared targets with blurred and unknown contours. The tracker uses the gray-value weighted mean-Shift algorithm to track the infrared target which is always brighter than the background. And the tracker can track the deformed target efficiently and quickly. When the target disappears, the detector will redetect the target in the coming infrared image. Finally, we verify the algorithm on the real-time infrared target detection and tracking platform. The result shows that our algorithm performs better than TLD in terms of recall and runtime in infrared video.

  2. Video Inpainting of Occluding and Occluded Objects

    Science.gov (United States)

    2005-01-01

    VIDEO INPAINTING OF OCCLUDING AND OCCLUDED OBJECTS By Kedar A. Patwardhan Guillermo Sapiro and Marcelo Bertalmio IMA Preprint Series # 2016 ( January... Inpainting of Occluding and Occluded Objects 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 VIDEO INPAINTING OF OCCLUDING AND OCCLUDED OBJECTS Kedar A

  3. LADAR object detection and tracking

    Science.gov (United States)

    Monaco, Sam D.

    2004-10-01

    The paper describes an innovative LADAR system for use in detecting, acquiring and tracking high-speed ballistic such as bullets and mortar shells and rocket propelled objects such as Rocket Propelled Grenades (RPGs) and TOW missiles. This class of targets proves to be a considerable challenge for classical RADAR systems since the target areas are small, velocities are very high and target range is short. The proposed system is based on detector and illuminator technology without any moving parts. The target area is flood illuminated with one or more modulated sources and a proprietary-processing algorithm utilizing phase difference return signals generates target information. All aspects of the system utilize existing, low risk components that are readily available from optical and electronic vendors. Operating the illuminator in a continuously modulated mode permits the target range to be measured by the phase delay of the modulated beam. Target velocity is measured by the Doppler frequency shift of the returned signal.

  4. Research on Agricultural Surveillance Video of Intelligent Tracking

    Science.gov (United States)

    Cai, Lecai; Xu, Jijia; Liangping, Jin; He, Zhiyong

    Intelligent video tracking technology is the digital video processing and analysis of an important field of application in the civilian and military defense have a wide range of applications. In this paper, a systematic study on the surveillance video of the Smart in the agricultural tracking, particularly in target detection and tracking problem of the study, respectively for the static background of the video sequences of moving targets detection and tracking algorithm, the goal of agricultural production for rapid detection and tracking algorithm and Mean Shift-based translation and rotation of the target tracking algorithm. Experimental results show that the system can effectively and accurately track the target in the surveillance video. Therefore, in agriculture for the intelligent video surveillance tracking study, whether it is from the environmental protection or social security, economic efficiency point of view, are very meaningful.

  5. Articulated object tracking by rendering consistent appearance parts

    OpenAIRE

    Pezzementi, Z.; Voros, Sandrine; Hager, Gregory D.

    2009-01-01

    International audience; We describe a general methodology for tracking 3-dimensional objects in monocular and stereo video that makes use of GPU-accelerated filtering and rendering in combination with machine learning techniques. The method operates on targets consisting of kinematic chains with known geometry. The tracked target is divided into one or more areas of consistent appearance. The appearance of each area is represented by a classifier trained to assign a class-conditional probabil...

  6. Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video

    OpenAIRE

    Shen, Minmin; Szyszka, Paul; Galizia, C. Giovanni; Merhof, Dorit

    2013-01-01

    Automatic tracking of the movement of bee's antennae and mouthparts is necessary for studying associative learning of individuals. However, the problem of tracking them is challenging: First, the different classes of objects possess similar appearance and are close to each other. Second, tracking gaps are often present, due to the low frame-rate of the acquired video and the fast motion of the objects. Most existing insect tracking approaches have been developed for slow moving objects, and a...

  7. Algorithm for dynamic object tracking

    Science.gov (United States)

    Datcu, Mihai P.; Folta, Florin; Toma, Cristian E.

    1992-11-01

    The purpose of this paper is to present a hierarchic processor architecture for the tracking of moving objects. Two goals are envisaged: the definition of a moving window for the target tracking, and multiresolution segmentation needed for scale independent target recognition. Memory windows in single processor systems obtained by software methods are limited in speed for high complexity images. In a multiprocessor system the limitation arises in bus or memory bottleneck. Highly concurrent system architectures have been studied and implemented as crossbar bus systems, multiple buses systems, or hypercube structures. Because of the complexity of these architectures and considering the particularities of image signals we suggest a hierarchic architecture that reduces the number of connections preserving the flexibility and which is well adapted for multiresolution algorithm implementations. The hierarchy is a quadtree. The solution is in using switched bus and block memory partition (granular image memory organization). To organize such an architecture in the first stage, the moving objects are identified in the camera field and the adequate windows are defined. The system is reorganized such as the computing power is concentrated in these windows. Image segmentation and motion prediction are accomplished. Motion parameters are interpreted to adapt the windows and to dynamically reorganize the system. The estimation of the motion parameters is done over low resolution images (top of the pyramid). Multiresolution image representation has been introduced for picture transmission and for scene analysis. The pyramidal implementation was elaborated for the evaluation of the image details at various scales. The multiresolution pyramid is obtained by low pass filtering and subsampling the intermediate result. The technique is applied over a limited range of scale. The multiresolution representations, as a consequence, are close to scale invariance. In the mean time image

  8. Does action disrupt Multiple Object Tracking (MOT?

    Directory of Open Access Journals (Sweden)

    Thornton Ian M.

    2015-01-01

    Full Text Available While the relationship between action and focused attention has been well-studied, less is known about the ability to divide attention while acting. In the current paper we explore this issue using the multiple object tracking (MOT paradigm (Pylyshyn & Storm, 1988. We asked whether planning and executing a display-relevant action during tracking would substantially affect the ability track and later identify targets. In all trials the primary task was to track 4 targets among a set of 8 identical objects. Several times during each trial, one object, selected at random, briefly changed colour. In the baseline MOT trials, these changes were ignored. During active trials, each changed object had to be quickly touched. On a given trial, changed objects were either from the tracking set or were selected at random from all 8 objects. Although there was a small dual-task cost, the need to act did not substantially impair tracking under either touch condition.

  9. A Neuromorphic System for Video Object Recognition

    Directory of Open Access Journals (Sweden)

    Deepak eKhosla

    2014-11-01

    Full Text Available Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS, is inspired by recent findings in computational neuroscience on feed-forward object detection and classification pipelines for processing and extracting relevant information from visual data. The NEOVUS architecture is inspired by the ventral (what and dorsal (where streams of the mammalian visual pathway and combines retinal processing, form-based and motion-based object detection, and convolutional neural nets based object classification. Our system was evaluated by the Defense Advanced Research Projects Agency (DARPA under the NEOVISION2 program on a variety of urban area video datasets collected from both stationary and moving platforms. The datasets are challenging as they include a large number of targets in cluttered scenes with varying illumination and occlusion conditions. The NEOVUS system was also mapped to commercially available off-the-shelf hardware. The dynamic power requirement for the system that includes a 5.6Mpixel retinal camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W, for an effective energy consumption of 5.4 nanoJoules (nJ per bit of incoming video. In a systematic evaluation of five different teams by DARPA on three aerial datasets, the NEOVUS demonstrated the best performance with the highest recognition accuracy and at least three orders of magnitude lower energy consumption than two independent state of the art computer vision systems. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition towards enabling practical low-power and mobile video processing applications.

  10. 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

  11. Robust Multitask Multiview Tracking in Videos.

    Science.gov (United States)

    Mei, Xue; Hong, Zhibin; Prokhorov, Danil; Tao, Dacheng

    2015-11-01

    Various sparse-representation-based methods have been proposed to solve tracking problems, and most of them employ least squares (LSs) criteria to learn the sparse representation. In many tracking scenarios, traditional LS-based methods may not perform well owing to the presence of heavy-tailed noise. In this paper, we present a tracking approach using an approximate least absolute deviation (LAD)-based multitask multiview sparse learning method to enjoy robustness of LAD and take advantage of multiple types of visual features, such as intensity, color, and texture. The proposed method is integrated in a particle filter framework, where learning the sparse representation for each view of the single particle is regarded as an individual task. The underlying relationship between tasks across different views and different particles is jointly exploited in a unified robust multitask formulation based on LAD. In addition, to capture the frequently emerging outlier tasks, we decompose the representation matrix to two collaborative components that enable a more robust and accurate approximation. We show that the proposed formulation can be effectively approximated by Nesterov's smoothing method and efficiently solved using the accelerated proximal gradient method. The presented tracker is implemented using four types of features and is tested on numerous synthetic sequences and real-world video sequences, including the CVPR2013 tracking benchmark and ALOV++ data set. Both the qualitative and quantitative results demonstrate the superior performance of the proposed approach compared with several state-of-the-art trackers.

  12. 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 ...... if a detected object shows a pattern of movement consistent with predefined rules. The method is tested on a number of video sequences and a substantial reduction in the number of false alarms is demonstrated.......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...... to e.g. movement of thicket and changes in illumination. To reduce the number of false alarms a Track Before Detect (TBD) approach is suggested. In this TBD implementation all objects detected in the background subtraction process are followed over a number of frames. An alarm is given only...

  13. 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...

  14. A FragTrack algorithm enhancement for total occlusion management in visual object tracking

    Science.gov (United States)

    Adamo, F.; Mazzeo, P. L.; Spagnolo, P.; Distante, C.

    2015-05-01

    In recent years, "FragTrack" has become one of the most cited real time algorithms for visual tracking of an object in a video sequence. However, this algorithm fails when the object model is not present in the image or it is completely occluded, and in long term video sequences. In these sequences, the target object appearance is considerably modified during the time and its comparison with the template established at the first frame is hard to compute. In this work we introduce improvements to the original FragTrack: the management of total object occlusions and the update of the object template. Basically, we use a voting map generated by a non-parametric kernel density estimation strategy that allows us to compute a probability distribution for the distances of the histograms between template and object patches. In order to automatically determine whether the target object is present or not in the current frame, an adaptive threshold is introduced. A Bayesian classifier establishes, frame by frame, the presence of template object in the current frame. The template is partially updated at every frame. We tested the algorithm on well-known benchmark sequences, in which the object is always present, and on video sequences showing total occlusion of the target object to demonstrate the effectiveness of the proposed method.

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

    Science.gov (United States)

    Lee, Gil-Beom; Lee, Myeong-Jin; Lee, Woo-Kyung; Park, Joo-Heon; Kim, Tae-Hwan

    2017-03-22

    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.

  16. Video-assisted segmentation of speech and audio track

    Science.gov (United States)

    Pandit, Medha; Yusoff, Yusseri; Kittler, Josef; Christmas, William J.; Chilton, E. H. S.

    1999-08-01

    Video database research is commonly concerned with the storage and retrieval of visual information invovling sequence segmentation, shot representation and video clip retrieval. In multimedia applications, video sequences are usually accompanied by a sound track. The sound track contains potential cues to aid shot segmentation such as different speakers, background music, singing and distinctive sounds. These different acoustic categories can be modeled to allow for an effective database retrieval. In this paper, we address the problem of automatic segmentation of audio track of multimedia material. This audio based segmentation can be combined with video scene shot detection in order to achieve partitioning of the multimedia material into semantically significant segments.

  17. 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 exploited. Coding results show the superior efficiency of the proposed scheme compared with MPEG-4...

  18. Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

    Directory of Open Access Journals (Sweden)

    Honghong Yang

    2016-01-01

    Full Text Available Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness.

  19. Integrated audiovisual processing for object localization and tracking

    Science.gov (United States)

    Pingali, Gopal S.

    1997-12-01

    This paper presents a system that combines audio and visual cues for locating and tracking an object, typically a person, in real time. It is shown that combining a speech source localization algorithm with a video-based head tracking algorithm results in a more accurate and robust tracker than that obtained using any one of the audio or visual modalities. Performance evaluation results are presented with a system that runs in real time on a general purpose processor. The multimodal tracker has several applications such as teleconferencing, multimedia kiosks and interactive games.

  20. A quick guide to video-tracking birds

    OpenAIRE

    Bluff, Lucas A; Rutz, Christian

    2008-01-01

    Video tracking is a powerful new tool for studying natural undisturbed behaviour in a wide range of birds, mammals and reptiles. Using integrated animal-borne video tags, video footage and positional data are recorded simultaneously from wild free-ranging animals. At the analysis stage, video scenes are linked to radio fixes, yielding an animal's eye view of resource use and social interactions along a known movement trajectory. Here, we provide a brief description of our basic equipment and ...

  1. Tracking cells in Life Cell Imaging videos using topological alignments

    Directory of Open Access Journals (Sweden)

    Ersoy Ilker

    2009-07-01

    Full Text Available Abstract Background With the increasing availability of live cell imaging technology, tracking cells and other moving objects in live cell videos has become a major challenge for bioimage informatics. An inherent problem for most cell tracking algorithms is over- or under-segmentation of cells – many algorithms tend to recognize one cell as several cells or vice versa. Results We propose to approach this problem through so-called topological alignments, which we apply to address the problem of linking segmentations of two consecutive frames in the video sequence. Starting from the output of a conventional segmentation procedure, we align pairs of consecutive frames through assigning sets of segments in one frame to sets of segments in the next frame. We achieve this through finding maximum weighted solutions to a generalized "bipartite matching" between two hierarchies of segments, where we derive weights from relative overlap scores of convex hulls of sets of segments. For solving the matching task, we rely on an integer linear program. Conclusion Practical experiments demonstrate that the matching task can be solved efficiently in practice, and that our method is both effective and useful for tracking cells in data sets derived from a so-called Large Scale Digital Cell Analysis System (LSDCAS. Availability The source code of the implementation is available for download from http://www.picb.ac.cn/patterns/Software/topaln.

  2. Joint albedo estimation and pose tracking from video.

    Science.gov (United States)

    Taheri, Sima; Sankaranarayanan, Aswin C; Chellappa, Rama

    2013-07-01

    The albedo of a Lambertian object is a surface property that contributes to an object's appearance under changing illumination. As a signature independent of illumination, the albedo is useful for object recognition. Single image-based albedo estimation algorithms suffer due to shadows and non-Lambertian effects of the image. In this paper, we propose a sequential algorithm to estimate the albedo from a sequence of images of a known 3D object in varying poses and illumination conditions. We first show that by knowing/estimating the pose of the object at each frame of a sequence, the object's albedo can be efficiently estimated using a Kalman filter. We then extend this for the case of unknown pose by simultaneously tracking the pose as well as updating the albedo through a Rao-Blackwellized particle filter (RBPF). More specifically, the albedo is marginalized from the posterior distribution and estimated analytically using the Kalman filter, while the pose parameters are estimated using importance sampling and by minimizing the projection error of the face onto its spherical harmonic subspace, which results in an illumination-insensitive pose tracking algorithm. Illustrations and experiments are provided to validate the effectiveness of the approach using various synthetic and real sequences followed by applications to unconstrained, video-based face recognition.

  3. A baseline algorithm for face detection and tracking in video

    Science.gov (United States)

    Manohar, Vasant; Soundararajan, Padmanabhan; Korzhova, Valentina; Boonstra, Matthew; Goldgof, Dmitry; Kasturi, Rangachar

    2007-10-01

    Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research significance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance metrics and establishing a substantial dataset with ground truth for object detection and tracking tasks (text and face) in two video domains -- broadcast news and meetings. In this paper, we present the results of a face detection and tracking algorithm on broadcast news videos with the objective of establishing a baseline performance for this task-domain pair. The detection algorithm uses a statistical approach that was originally developed by Viola and Jones and later extended by Lienhart. The algorithm uses a feature set that is Haar-like and a cascade of boosted decision tree classifiers as a statistical model. In this work, we used the Intel Open Source Computer Vision Library (OpenCV) implementation of the Haar face detection algorithm. The optimal values for the tunable parameters of this implementation were found through an experimental design strategy commonly used in statistical analyses of industrial processes. Tracking was accomplished as continuous detection with the detected objects in two frames mapped using a greedy algorithm based on the distances between the centroids of bounding boxes. Results on the evaluation set containing 50 sequences (~ 2.5 mins.) using the developed performance metrics show good performance of the algorithm reflecting the state-of-the-art which makes it an appropriate choice as the baseline algorithm for the problem.

  4. Deterministic object tracking using Gaussian ringlet and directional edge features

    Science.gov (United States)

    Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

    2017-10-01

    Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

  5. Space object tracking with delayed measurements

    Science.gov (United States)

    Chen, Huimin; Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh

    2010-04-01

    This paper is concerned with the nonlinear filtering problem for tracking a space object with possibly delayed measurements. In a distributed dynamic sensing environment, due to limited communication bandwidth and long distances between the earth and the satellites, it is possible for sensor reports to be delayed when the tracking filter receives them. Such delays can be complete (the full observation vector is delayed) or partial (part of the observation vector is delayed), and with deterministic or random time lag. We propose an approximate approach to incorporate delayed measurements without reprocessing the old measurements at the tracking filter. We describe the optimal and suboptimal algorithms for filter update with delayed measurements in an orbital trajectory estimation problem without clutter. Then we extend the work to a single object tracking under clutter where probabilistic data association filter (PDAF) is used to replace the recursive linear minimum means square error (LMMSE) filter and delayed measurements with arbitrary lags are be handled without reprocessing the old measurements. Finally, we demonstrate the proposed algorithms in realistic space object tracking scenarios using the NASA General Mission Analysis Tool (GMAT).

  6. Moving traffic object retrieval in H.264/MPEG compressed video

    Science.gov (United States)

    Shi, Xu-li; Xiao, Guang; Wang, Shuo-zhong; Zhang, Zhao-yang; An, Ping

    2006-05-01

    Moving object retrieval technique in compressed domain plays an important role in many real-time applications, e.g. Vehicle Detection and Classification. A number of retrieval techniques that operate in compressed domain have been reported in the literature. H.264/AVC is the up-to-date video-coding standard that is likely to lead to the proliferation of retrieval techniques in the compressed domain. Up to now, few literatures on H.264/AVC compressed video have been reported. Compared with the MPEG standard, H.264/AVC employs several new coding block types and different entropy coding method, which result in moving object retrieval in H.264/ AVC compressed video a new task and challenging work. In this paper, an approach to extract and retrieval moving traffic object in H.264/AVC compressed video is proposed. Our algorithm first Interpolates the sparse motion vector of p-frame that is composed of 4*4 blocks, 4*8 blocks and 8*4 blocks and so on. After forward projecting each p-frame vector to the immediate adjacent I-frame and calculating the DCT coefficients of I-frame using information of spatial intra-prediction, the method extracts moving VOPs (video object plan) using an interactive 4*4 block classification process. In Vehicle Detection application, the segmented VOP in 4*4 block-level accuracy is insufficient. Once we locate the target VOP, the actual edges of the VOP in 4*4 block accuracy can be extracted by applying Canny Edge Detection only on the moving VOP in 4*4 block accuracy. The VOP in pixel accuracy is then achieved by decompressing the DCT blocks of the VOPs. The edge-tracking algorithm is applied to find the missing edge pixels. After the segmentation process a retrieval algorithm that based on CSS (Curvature Scale Space) is used to search the interested shape of vehicle in H.264/AVC compressed video sequence. Experiments show that our algorithm can extract and retrieval moving vehicles efficiency and robustly.

  7. A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection.

    Science.gov (United States)

    Li, Jia; Xia, Changqun; Chen, Xiaowu

    2017-10-12

    Image-based salient object detection (SOD) has been extensively studied in past decades. However, video-based SOD is much less explored due to the lack of large-scale video datasets within which salient objects are unambiguously defined and annotated. Toward this end, this paper proposes a video-based SOD dataset that consists of 200 videos. In constructing the dataset, we manually annotate all objects and regions over 7,650 uniformly sampled keyframes and collect the eye-tracking data of 23 subjects who free-view all videos. From the user data, we find that salient objects in a video can be defined as objects that consistently pop-out throughout the video, and objects with such attributes can be unambiguously annotated by combining manually annotated object/region masks with eye-tracking data of multiple subjects. To the best of our knowledge, it is currently the largest dataset for videobased salient object detection. Based on this dataset, this paper proposes an unsupervised baseline approach for video-based SOD by using saliencyguided stacked autoencoders. In the proposed approach, multiple spatiotemporal saliency cues are first extracted at the pixel, superpixel and object levels. With these saliency cues, stacked autoencoders are constructed in an unsupervised manner that automatically infers a saliency score for each pixel by progressively encoding the high-dimensional saliency cues gathered from the pixel and its spatiotemporal neighbors. In experiments, the proposed unsupervised approach is compared with 31 state-of-the-art models on the proposed dataset and outperforms 30 of them, including 19 imagebased classic (unsupervised or non-deep learning) models, six image-based deep learning models, and five video-based unsupervised models. Moreover, benchmarking results show that the proposed dataset is very challenging and has the potential to boost the development of video-based SOD.

  8. 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.

  9. Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

    Science.gov (United States)

    Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

    2017-05-01

    Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

  10. 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.

  11. Eye-Movement Tracking Using Compressed Video Images

    Science.gov (United States)

    Mulligan, Jeffrey B.; Beutter, Brent R.; Hull, Cynthia H. (Technical Monitor)

    1994-01-01

    Infrared video cameras offer a simple noninvasive way to measure the position of the eyes using relatively inexpensive equipment. Several commercial systems are available which use special hardware to localize features in the image in real time, but the constraint of realtime performance limits the complexity of the applicable algorithms. In order to get better resolution and accuracy, we have used off-line processing to apply more sophisticated algorithms to the images. In this case, a major technical challenge is the real-time acquisition and storage of the video images. This has been solved using a strictly digital approach, exploiting the burgeoning field of hardware video compression. In this paper we describe the algorithms we have developed for tracking the movements of the eyes in video images, and present experimental results showing how the accuracy is affected by the degree of video compression.

  12. Object Recognition in Videos Utilizing Hierarchical and Temporal Objectness with Deep Neural Networks

    OpenAIRE

    Peng, Liang

    2017-01-01

    This dissertation develops a novel system for object recognition in videos. The input of the system is a set of unconstrained videos containing a known set of objects. The output is the locations and categories for each object in each frame across all videos. Initially, a shot boundary detection algorithm is applied to the videos to divide them into multiple sequences separated by the identified shot boundaries. Since each of these sequences still contains moderate content variations, we furt...

  13. 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.

  14. Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

    Science.gov (United States)

    Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

    2013-12-01

    This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

  15. Joint estimation fusion and tracking of objects in a single camera using EM-EKF

    Science.gov (United States)

    Sathyaraj. S, Pristley; Leung, Henry

    2013-09-01

    Tracking objects in dynamic scene is an interesting area of research and it has it's applications in many areas like surveillance, missile tracking system,virtual reality and robot vision. Objects in real world exhibit complex interactions with each other. When captured in a video signal, these interactions manifest themselves as in- tertwineing motions , occlusion and pose changes. A video tracking system should track these objects in this complex interactions smoothly . This paper presents a new joint method for tracking moving objects in outdoor and indoor environment. This joint method uses recursive Expectation-Maximization (EM) incorporated with Extended Kalman Filter (EKF) to estimate, fuse and track the object simultaneously, than doing it in two dif- ferent steps. This combined approach provides more realistic solution to the problem. Thereby, outperforming the conventional method of treating it as three di erent problems. We have tested our algorithm with standard dataset and real time video sequences collected from indoor environment. We also nd that the usage of the joint method improves the accuracy and computational cost. This method successfully tracks object with occlusions, di erent orientations and intertwining motion.

  16. Object detection in surveillance video from dense trajectories

    OpenAIRE

    Zhai, Mengyao

    2015-01-01

    Detecting objects such as humans or vehicles is a central problem in surveillance video. Myriad standard approaches exist for this problem. At their core, approaches consider either the appearance of people, patterns of their motion, or differences from the background. In this paper we build on dense trajectories, a state-of-the-art approach for describing spatio-temporal patterns in video sequences. We demonstrate an application of dense trajectories to object detection in surveillance video...

  17. Feature fusion using ranking for object tracking in aerial imagery

    Science.gov (United States)

    Candemir, Sema; Palaniappan, Kannappan; Bunyak, Filiz; Seetharaman, Guna

    2012-06-01

    Aerial wide-area monitoring and tracking using multi-camera arrays poses unique challenges compared to stan- dard full motion video analysis due to low frame rate sampling, accurate registration due to platform motion, low resolution targets, limited image contrast, static and dynamic parallax occlusions.1{3 We have developed a low frame rate tracking system that fuses a rich set of intensity, texture and shape features, which enables adaptation of the tracker to dynamic environment changes and target appearance variabilities. However, improper fusion and overweighting of low quality features can adversely aect target localization and reduce tracking performance. Moreover, the large computational cost associated with extracting a large number of image-based feature sets will in uence tradeos for real-time and on-board tracking. This paper presents a framework for dynamic online ranking-based feature evaluation and fusion in aerial wide-area tracking. We describe a set of ecient descriptors suitable for small sized targets in aerial video based on intensity, texture, and shape feature representations or views. Feature ranking is then used as a selection procedure where target-background discrimination power for each (raw) feature view is scored using a two-class variance ratio approach. A subset of the k-best discriminative features are selected for further processing and fusion. The target match probability or likelihood maps for each of the k features are estimated by comparing target descriptors within a search region using a sliding win- dow approach. The resulting k likelihood maps are fused for target localization using the normalized variance ratio weights. We quantitatively measure the performance of the proposed system using ground-truth tracks within the framework of our tracking evaluation test-bed that incorporates various performance metrics. The proposed feature ranking and fusion approach increases localization accuracy by reducing multimodal eects

  18. 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 the...

  19. Video-based eye tracking for neuropsychiatric assessment.

    Science.gov (United States)

    Adhikari, Sam; Stark, David E

    2017-01-01

    This paper presents a video-based eye-tracking method, ideally deployed via a mobile device or laptop-based webcam, as a tool for measuring brain function. Eye movements and pupillary motility are tightly regulated by brain circuits, are subtly perturbed by many disease states, and are measurable using video-based methods. Quantitative measurement of eye movement by readily available webcams may enable early detection and diagnosis, as well as remote/serial monitoring, of neurological and neuropsychiatric disorders. We successfully extracted computational and semantic features for 14 testing sessions, comprising 42 individual video blocks and approximately 17,000 image frames generated across several days of testing. Here, we demonstrate the feasibility of collecting video-based eye-tracking data from a standard webcam in order to assess psychomotor function. Furthermore, we were able to demonstrate through systematic analysis of this data set that eye-tracking features (in particular, radial and tangential variance on a circular visual-tracking paradigm) predict performance on well-validated psychomotor tests. © 2017 New York Academy of Sciences.

  20. Human object articulation for CCTV video forensics

    Science.gov (United States)

    Zafar, I.; Fraz, M.; Edirisinghe, Eran A.

    2013-03-01

    In this paper we present a system which is focused on developing algorithms for automatic annotation/articulation of humans passing through a surveillance camera in a way useful for describing a person/criminal by a crime scene witness. Each human is articulated/annotated based on two appearance features: 1. primary colors of clothes in the head, body and legs region. 2. presence of text/logo on the clothes. The annotation occurs after a robust foreground extraction based on a modified approach to Gaussian Mixture model and detection of human from segmented foreground images. The proposed pipeline consists of a preprocessing stage where we improve color quality of images using a basic color constancy algorithm and further improve the results using a proposed post-processing method. The results show a significant improvement to the illumination of the video frames. In order to annotate color information for human clothes, we apply 3D Histogram analysis (with respect to Hue, Saturation and Value) on HSV converted image regions of human body parts along with extrema detection and thresholding to decide the dominant color of the region. In order to detect text/logo on the clothes as another feature to articulate humans, we begin with the extraction of connected components of enhanced horizontal, vertical and diagonal edges in the frames. These candidate regions are classified as text or non-text on the bases of their Local Energy based Shape Histogram (LESH) features combined with KL divergence as classification criteria. To detect humans, a novel technique has been proposed that uses a combination of Histogram of Oriented Gradients (HOG) and Contourlet transform based Local Binary Patterns (LBP) with Adaboost as classifier. Initial screening of foreground objects is performed by using HOG features. To further eliminate the false positives due to noise form background and improve results, we apply Contourlet-LBP feature extraction on the images. In the proposed method

  1. Video tracking analysis of behavioral patterns during estrus in goats

    Science.gov (United States)

    ENDO, Natsumi; RAHAYU, Larasati Puji; ARAKAWA, Toshiya; TANAKA, Tomomi

    2015-01-01

    Here, we report a new method for measuring behavioral patterns during estrus in goats based on video tracking analysis. Data were collected from cycling goats, which were in estrus (n = 8) or not in estrus (n = 8). An observation pen (2.5 m × 2.5 m) was set up in the corner of the female paddock with one side adjacent to a male paddock. The positions and movements of goats were tracked every 0.5 sec for 10 min by using a video tracking software, and the trajectory data were used for the analysis. There were no significant differences in the durations of standing and walking or the total length of movement. However, the number of approaches to a male and the duration of staying near the male were higher in goats in estrus than in goats not in estrus. The proposed evaluation method may be suitable for detailed monitoring of behavioral changes during estrus in goats. PMID:26560676

  2. Video markers tracking methods for bike fitting

    Science.gov (United States)

    Rajkiewicz, Piotr; Łepkowska, Katarzyna; Cygan, Szymon

    2015-09-01

    Sports cycling is becoming increasingly popular over last years. Obtaining and maintaining a proper position on the bike has been shown to be crucial for performance, comfort and injury avoidance. Various techniques of bike fitting are available - from rough settings based on body dimensions to professional services making use of sophisticated equipment and expert knowledge. Modern fitting techniques use mainly joint angles as a criterion of proper position. In this work we examine performance of two proposed methods for dynamic cyclist position assessment based on video data recorded during stationary cycling. Proposed methods are intended for home use, to help amateur cyclist improve their position on the bike, and therefore no professional equipment is used. As a result of data processing, ranges of angles in selected joints are provided. Finally strengths and weaknesses of both proposed methods are discussed.

  3. Tracking Objects with Networked Scattered Directional Sensors

    Directory of Open Access Journals (Sweden)

    P. R. Kumar

    2007-12-01

    Full Text Available 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.

  4. 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.

  5. 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.

  6. An automated object-level video editing tool

    Science.gov (United States)

    Ibrahim, Sara; AbdElbaky, Mona; Mohamed, Kholood; Yassin, Kawther; Hemayed, Elsayed

    2009-01-01

    In this paper, we are presenting an object-level video editing tool that provides automatic object removal and video summarizing capabilities based on a user selected object. The tool has three main modules; object selection, object detection and background completion. In the object selection module, user selects the required object to be removed or used as reference for video summarization. The object contour is calculated using Livewire algorithm. The object detection module uses a correlation technique to detect the object in all frames. In the background completion module, the background is filled using a novel and efficient algorithm that combines the advantages of texture synthesis algorithms and inpainting techniques. A detailed description of the tool is presented in this paper along with a variety of experimental results.

  7. How to evaluate objective video quality metrics reliably

    DEFF Research Database (Denmark)

    Korhonen, Jari; Burini, Nino; You, Junyong

    2012-01-01

    The typical procedure for evaluating the performance of different objective quality metrics and indices involves comparisons between subjective quality ratings and the quality indices obtained using the objective metrics in question on the known video sequences. Several correlation indicators can...... as processing of subjective data. We also suggest some general guidelines for researchers to make comparison studies of objective video quality metrics more reliable and useful for the practitioners in the field....

  8. High dynamic range (HDR) virtual bronchoscopy rendering for video tracking

    Science.gov (United States)

    Popa, Teo; Choi, Jae

    2007-03-01

    In this paper, we present the design and implementation of a new rendering method based on high dynamic range (HDR) lighting and exposure control. This rendering method is applied to create video images for a 3D virtual bronchoscopy system. One of the main optical parameters of a bronchoscope's camera is the sensor exposure. The exposure adjustment is needed since the dynamic range of most digital video cameras is narrower than the high dynamic range of real scenes. The dynamic range of a camera is defined as the ratio of the brightest point of an image to the darkest point of the same image where details are present. In a video camera exposure is controlled by shutter speed and the lens aperture. To create the virtual bronchoscopic images, we first rendered a raw image in absolute units (luminance); then, we simulated exposure by mapping the computed values to the values appropriate for video-acquired images using a tone mapping operator. We generated several images with HDR and others with low dynamic range (LDR), and then compared their quality by applying them to a 2D/3D video-based tracking system. We conclude that images with HDR are closer to real bronchoscopy images than those with LDR, and thus, that HDR lighting can improve the accuracy of image-based tracking.

  9. Patch Based Multiple Instance Learning Algorithm for Object Tracking.

    Science.gov (United States)

    Wang, Zhenjie; Wang, Lijia; Zhang, Hua

    2017-01-01

    To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL) algorithm is proposed. The algorithm divides an object into many blocks. Then, the online MIL algorithm is applied on each block for obtaining strong classifier. The algorithm takes account of both the average classification score and classification scores of all the blocks for detecting the object. In particular, compared with the whole object based MIL algorithm, the P-MIL algorithm detects the object according to the unoccluded patches when partial occlusion occurs. After detecting the object, the learning rates for updating weak classifiers' parameters are adaptively tuned. The classifier updating strategy avoids overupdating and underupdating the parameters. Finally, the proposed method is compared with other state-of-the-art algorithms on several classical videos. The experiment results illustrate that the proposed method performs well especially in case of illumination changes or pose variations and partial occlusion. Moreover, the algorithm realizes real-time object tracking.

  10. Real-time object tracking for moving target auto-focus in digital camera

    Science.gov (United States)

    Guan, Haike; Niinami, Norikatsu; Liu, Tong

    2015-02-01

    Focusing at a moving object accurately is difficult and important to take photo of the target successfully in a digital camera. Because the object often moves randomly and changes its shape frequently, position and distance of the target should be estimated at real-time so as to focus at the objet precisely. We propose a new method of real-time object tracking to do auto-focus for moving target in digital camera. Video stream in the camera is used for the moving target tracking. Particle filter is used to deal with problem of the target object's random movement and shape change. Color and edge features are used as measurement of the object's states. Parallel processing algorithm is developed to realize real-time particle filter object tracking easily in hardware environment of the digital camera. Movement prediction algorithm is also proposed to remove focus error caused by difference between tracking result and target object's real position when the photo is taken. Simulation and experiment results in digital camera demonstrate effectiveness of the proposed method. We embedded real-time object tracking algorithm in the digital camera. Position and distance of the moving target is obtained accurately by object tracking from the video stream. SIMD processor is applied to enforce parallel real-time processing. Processing time less than 60ms for each frame is obtained in the digital camera with its CPU of only 162MHz.

  11. Need for Speed: A Benchmark for Higher Frame Rate Object Tracking

    OpenAIRE

    Galoogahi, Hamed Kiani; Fagg, Ashton; Huang, Chen; Ramanan, Deva; Lucey, Simon

    2017-01-01

    In this paper, we propose the first higher frame rate video dataset (called Need for Speed - NfS) and benchmark for visual object tracking. The dataset consists of 100 videos (380K frames) captured with now commonly available higher frame rate (240 FPS) cameras from real world scenarios. All frames are annotated with axis aligned bounding boxes and all sequences are manually labelled with nine visual attributes - such as occlusion, fast motion, background clutter, etc. Our benchmark provides ...

  12. Object Tracking and Designation (OTD). Final report, Phase 2

    Energy Technology Data Exchange (ETDEWEB)

    1990-11-01

    We demonstrated on the Object Tracking and Designation (OTD) project, the effectiveness of the 001 technology to the development of complex scientifically-oriented applications for SDI. This document summarizes the results of the project. In the OTD system, Object sightings from Measurement Processing are sorted by Object Sorting into azimuth/elevation bins, then passed to Object Screening. Object Screening separates sightings which are part of an established track from those for which no track has been established. In Process Sighting, sightings determined to be part of established tracks are sent to Update Tracks; uncorrelated sightings are sent to Generate Tracks. Generate Tracks first performs a rate smoothing of the data in Rate Smoothing. In Candidate Track Selection (CTS) uncorrelated sightings are compared with the previous five to seven frames. Those sightings which can be put together to form a candidate ballistic trajectory are sent to the Trajectory Fitting process. In the Trajectory Fitting process, candidate tracks are fitted to precision trajectories. Valid trajectories are sent to Radiometric Discriminant Initialization in the form of a new track message, and object sightings making up the trajectory are removed from the Object Sighting data structure. In Radiometric Discriminant Initialization, radiometric discriminants are produced from the new track message and the resulting discriminant values used to initialize a track record in the Object Track File data structure which is passed to the Prediction function. The Metric Discrimination process uses angle data to determine object lethality. The object`s designation is then sent to the Prediction process. In the Prediction process the track`s position and uncertainty on the next frame is predicted based upon a coefficient corresponding to the object`s estimated class and on the expected interception of the track and the scanner on the next frame.

  13. Active shape model-based real-time tracking of deformable objects

    Science.gov (United States)

    Kim, Sangjin; Kim, Daehee; Shin, Jeongho; Paik, Joonki

    2005-10-01

    Tracking non-rigid objects such as people in video sequences is a daunting task due to computational complexity and unpredictable environment. The analysis and interpretation of video sequence containing moving, deformable objects have been an active research areas including video tracking, computer vision, and pattern recognition. In this paper we propose a robust, model-based, real-time system to cope with background clutter and occlusion. The proposed algorithm consists of following four steps: (i) localization of an object-of-interest by analyzing four directional motions, (ii) region tracker for tracking moving region detected by the motion detector, (iii) update of training sets using the Smart Snake Algorithm (SSA) without preprocessing, (iv) active shape model-based tracking in region information. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, sape analysis, and model-based coding, to name of few.

  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. Object tracking for a class of dynamic image-based representations

    Science.gov (United States)

    Gan, Zhi-Feng; Chan, Shing-Chow; Ng, King-To; Shum, Heung-Yeung

    2005-07-01

    Image-based rendering (IBR) is an emerging technology for photo-realistic rendering of scenes from a collection of densely sampled images and videos. Recently, an object-based approach for rendering and the compression of a class of dynamic image-based representations called plenoptic videos was proposed. The plenoptic video is a simplified dynamic light field, which is obtained by capturing videos at regularly locations along a series of line segments. In the object-based approach, objects at large depth differences are segmented into layers for rendering and compression. The rendering quality in large environment can be significantly improved, as demonstrated by the pop-up lightfields. In addition, by coding the plenoptic video at the object level, desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects, can be achieved. An important step in the object-based approach is to segment the objects in the video streams into layers or image-based objects, which is largely done by semi-automatic technique. To reduce the segmentation time for segmenting plenoptic videos, efficient tracking techniques are highly desirable. This paper proposes a new automatic object tracking method based on the level-set method. Our method, which utilizes both local and global features of the image sequences instead of global features exploited in previous approach, can achieve better tracking results for objects, especially with non-uniform energy distribution. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Using the alpha map and texture so estimated, it is very convenient to composite the image-based objects onto the background of the original or other plenoptic videos. Furthermore, a MPEG-4 like object-based algorithm is developed for compressing the plenoptic videos, which consist of the alpha maps, depth maps and textures of the

  16. 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

  17. 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.

  18. Ball lightning observation: an objective video-camera analysis report

    OpenAIRE

    Sello, Stefano; Viviani, Paolo; Paganini, Enrico

    2011-01-01

    In this paper we describe a video-camera recording of a (probable) ball lightning event and both the related image and signal analyses for its photometric and dynamical characterization. The results strongly support the BL nature of the recorded luminous ball object and allow the researchers to have an objective and unique video document of a possible BL event for further analyses. Some general evaluations of the obtained results considering the proposed ball lightning models conclude the paper.

  19. 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.

  20. 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...... shape layer is processed by a novel video shape coder. In intra mode, the DSLSC binary image coder presented in is used. This is extended here with an intermode utilizing temporal redundancies in shape image sequences. Then the opaque layer is compressed by a newly designed scheme which models...

  1. Evaluation of Simulated Clinical Breast Exam Motion Patterns Using Marker-Less Video Tracking.

    Science.gov (United States)

    Azari, David P; Pugh, Carla M; Laufer, Shlomi; Kwan, Calvin; Chen, Chia-Hsiung; Yen, Thomas Y; Hu, Yu Hen; Radwin, Robert G

    2016-05-01

    This study investigates using marker-less video tracking to evaluate hands-on clinical skills during simulated clinical breast examinations (CBEs). There are currently no standardized and widely accepted CBE screening techniques. Experienced physicians attending a national conference conducted simulated CBEs presenting different pathologies with distinct tumorous lesions. Single hand exam motion was recorded and analyzed using marker-less video tracking. Four kinematic measures were developed to describe temporal (time pressing and time searching) and spatial (area covered and distance explored) patterns. Mean differences between time pressing, area covered, and distance explored varied across the simulated lesions. Exams were objectively categorized as either sporadic, localized, thorough, or efficient for both temporal and spatial categories based on spatiotemporal characteristics. The majority of trials were temporally or spatially thorough (78% and 91%), exhibiting proportionally greater time pressing and time searching (temporally thorough) and greater area probed with greater distance explored (spatially thorough). More efficient exams exhibited proportionally more time pressing with less time searching (temporally efficient) and greater area probed with less distance explored (spatially efficient). Just two (5.9 %) of the trials exhibited both high temporal and spatial efficiency. Marker-less video tracking was used to discriminate different examination techniques and measure when an exam changes from general searching to specific probing. The majority of participants exhibited more thorough than efficient patterns. Marker-less video kinematic tracking may be useful for quantifying clinical skills for training and assessment. © 2015, Human Factors and Ergonomics Society.

  2. Automated Mulitple Object Optical Tracking and Recognition System Project

    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...

  3. 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.

  4. Automatic Synthesis of Background Music Track Data by Analysis of Video Contents

    Science.gov (United States)

    Modegi, Toshio

    This paper describes an automatic creation technique of background music track data for given video file. Our proposed system is based on a novel BGM synthesizer, called “Matrix Music Player”, which can produce 3125 kinds of high-quality BGM contents by dynamically mixing 5 audio files, which are freely selected from total 25 audio waveform files. In order to retrieve appropriate BGM mixing patterns, we have constructed an acoustic analysis database, which records acoustic features of total 3125 synthesized patterns. Developing a video analyzer which generates image parameters of given video data and converts them to acoustic parameters, we will access the acoustic analysis database and retrieve an appropriate synthesized BGM signal, which can be included in the audio track of the source video file. Based on our proposed method, we have tried BGM synthesis experiments using several around 20-second video clips. The automatically inserted BGM audio streams for all of our given video clips have been objectively acceptable. In this paper, we describe briefly our proposed BGM synthesized method and its experimental results.

  5. Unsupervised Primary Object Discovery in Videos Based on Evolutionary Primary Object Modeling With Reliable Object Proposals.

    Science.gov (United States)

    Koh, Yeong Jun; Kim, Chang-Su

    2017-11-01

    A novel primary object discovery (POD) algorithm, which uses reliable object proposals while exploiting the recurrence property of a primary object in a video sequence, is proposed in this paper. First, we generate both color-based and motion-based object proposals in each frame, and extract the feature of each proposal using the random walk with restart simulation. Next, we estimate the foreground confidence for each proposal to remove unreliable proposals. By superposing the features of the remaining reliable proposals, we construct the primary object models. To this end, we develop the evolutionary primary object modeling technique, which exploits the recurrence property of the primary object. Then, using the primary object models, we choose the main proposal in each frame and find the location of the primary object by merging the main proposal with candidate proposals selectively. Finally, we refine the discovered bounding boxes by exploiting temporal correlations of the recurring primary object. Extensive experimental results demonstrate that the proposed POD algorithm significantly outperforms conventional algorithms.

  6. 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.

  7. 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.

  8. 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.

  9. Objective video presentation QoE predictor for smart adaptive video streaming

    Science.gov (United States)

    Wang, Zhou; Zeng, Kai; Rehman, Abdul; Yeganeh, Hojatollah; Wang, Shiqi

    2015-09-01

    How to deliver videos to consumers over the network for optimal quality-of-experience (QoE) has been the central goal of modern video delivery services. Surprisingly, regardless of the large volume of videos being delivered everyday through various systems attempting to improve visual QoE, the actual QoE of end consumers is not properly assessed, not to say using QoE as the key factor in making critical decisions at the video hosting, network and receiving sites. Real-world video streaming systems typically use bitrate as the main video presentation quality indicator, but using the same bitrate to encode different video content could result in drastically different visual QoE, which is further affected by the display device and viewing condition of each individual consumer who receives the video. To correct this, we have to put QoE back to the driver's seat and redesign the video delivery systems. To achieve this goal, a major challenge is to find an objective video presentation QoE predictor that is accurate, fast, easy-to-use, display device adaptive, and provides meaningful QoE predictions across resolution and content. We propose to use the newly developed SSIMplus index (https://ece.uwaterloo.ca/~z70wang/research/ssimplus/) for this role. We demonstrate that based on SSIMplus, one can develop a smart adaptive video streaming strategy that leads to much smoother visual QoE impossible to achieve using existing adaptive bitrate video streaming approaches. Furthermore, SSIMplus finds many more applications, in live and file-based quality monitoring, in benchmarking video encoders and transcoders, and in guiding network resource allocations.

  10. Object tracking with hierarchical multiview learning

    Science.gov (United States)

    Yang, Jun; Zhang, Shunli; Zhang, Li

    2016-09-01

    Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

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

    Directory of Open Access Journals (Sweden)

    Dajun He

    2004-10-01

    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.

  12. Automated Tracking of Whiskers in Videos of Head Fixed Rodents

    Science.gov (United States)

    Clack, Nathan G.; O'Connor, Daniel H.; Huber, Daniel; Petreanu, Leopoldo; Hires, Andrew; Peron, Simon; Svoboda, Karel; Myers, Eugene W.

    2012-01-01

    We have developed software for fully automated tracking of vibrissae (whiskers) in high-speed videos (>500 Hz) of head-fixed, behaving rodents trimmed to a single row of whiskers. Performance was assessed against a manually curated dataset consisting of 1.32 million video frames comprising 4.5 million whisker traces. The current implementation detects whiskers with a recall of 99.998% and identifies individual whiskers with 99.997% accuracy. The average processing rate for these images was 8 Mpx/s/cpu (2.6 GHz Intel Core2, 2 GB RAM). This translates to 35 processed frames per second for a 640 px×352 px video of 4 whiskers. The speed and accuracy achieved enables quantitative behavioral studies where the analysis of millions of video frames is required. We used the software to analyze the evolving whisking strategies as mice learned a whisker-based detection task over the course of 6 days (8148 trials, 25 million frames) and measure the forces at the sensory follicle that most underlie haptic perception. PMID:22792058

  13. Automated tracking of whiskers in videos of head fixed rodents.

    Science.gov (United States)

    Clack, Nathan G; O'Connor, Daniel H; Huber, Daniel; Petreanu, Leopoldo; Hires, Andrew; Peron, Simon; Svoboda, Karel; Myers, Eugene W

    2012-01-01

    We have developed software for fully automated tracking of vibrissae (whiskers) in high-speed videos (>500 Hz) of head-fixed, behaving rodents trimmed to a single row of whiskers. Performance was assessed against a manually curated dataset consisting of 1.32 million video frames comprising 4.5 million whisker traces. The current implementation detects whiskers with a recall of 99.998% and identifies individual whiskers with 99.997% accuracy. The average processing rate for these images was 8 Mpx/s/cpu (2.6 GHz Intel Core2, 2 GB RAM). This translates to 35 processed frames per second for a 640 px×352 px video of 4 whiskers. The speed and accuracy achieved enables quantitative behavioral studies where the analysis of millions of video frames is required. We used the software to analyze the evolving whisking strategies as mice learned a whisker-based detection task over the course of 6 days (8148 trials, 25 million frames) and measure the forces at the sensory follicle that most underlie haptic perception.

  14. Video tracking in the extreme: video analysis for nocturnal underwater animal movement.

    Science.gov (United States)

    Patullo, B W; Jolley-Rogers, G; Macmillan, D L

    2007-11-01

    Computer analysis of video footage is one option for recording locomotor behavior for a range of neurophysiological and behavioral studies. This technique is reasonably well established and accepted, but its use for some behavioral analyses remains a challenge. For example, filming through water can lead to reflection, and filming nocturnal activity can reduce resolution and clarity of filmed images. The aim of this study was to develop a noninvasive method for recording nocturnal activity in aquatic decapods and test the accuracy of analysis by video tracking software. We selected crayfish, Cherax destructor, because they are often active at night, they live underwater, and data on their locomotion is important for answering biological and physiological questions such as how they explore and navigate. We constructed recording arenas and filmed animals in infrared light. Wethen compared human observer data and software-acquired values. In this article, we outline important apparatus and software issues to obtain reliable computer tracking.

  15. 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...

  16. Hough forests for object detection, tracking, and action recognition.

    Science.gov (United States)

    Gall, Juergen; Yao, Angela; Razavi, Nima; Van Gool, Luc; Lempitsky, Victor

    2011-11-01

    Abstract—The paper introduces Hough forests, which are random forests adapted to perform a generalized Hough transform in an efficient way. Compared to previous Hough-based systems such as implicit shape models, Hough forests improve the performance of the generalized Hough transform for object detection on a categorical level. At the same time, their flexibility permits extensions of the Hough transform to new domains such as object tracking and action recognition. Hough forests can be regarded as task-adapted codebooks of local appearance that allow fast supervised training and fast matching at test time. They achieve high detection accuracy since the entries of such codebooks are optimized to cast Hough votes with small variance and since their efficiency permits dense sampling of local image patches or video cuboids during detection. The efficacy of Hough forests for a set of computer vision tasks is validated through experiments on a large set of publicly available benchmark data sets and comparisons with the state-of-the-art.

  17. 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.

  18. Video Automatic Target Tracking System (VATTS) Operating Procedure,

    Science.gov (United States)

    1980-08-15

    AO-AIO𔃾 790 BOM CORP MCLEAN VA F/A 17/8 VIDEO AUTOMATIC TARGE T TRACKING SYSTEM (VATTS) OPERATING PROCEO -ETC(U) AUG Go C STAMM J P ORRESTER, J...Tape Transport Number Two TKI Tektronics I/0 Terminal DS1 Removable Disk Storage Unit DSO Fixed Disk Storage Unit CRT Cathode Ray Tube 1-3 THE BDM...file (mark on Mag Tape) AZEL Quick look at Trial Information Program DUPTAPE Allows for duplication of magnetic tapes CA Cancel ( terminates program on

  19. 3D modelling of cultural heritage objects using video technology

    Directory of Open Access Journals (Sweden)

    Paulina Deliś

    2014-06-01

    Full Text Available In the paper, the process of creating 3D models of St. Anne’s Church’s facades is described. Some examples of architectural structures inside of St. Anne’s Church’s are presented. Video data were acquired with the fixed focal length lens f = 16 mm. It allowed to determine interior orientation parameters in a calibration process and to remove an influence of distortion. 3D models of heritage objects were generated using the Topcon Image Master software. The process of 3D model creating from video data involved the following steps: video frames selection for the orientation process, orientation of video frames using points with known coordinates from Terrestrial Laser Scanning, wireframe and TIN model generation. In order to assess the accuracy of the developed 3D models, points with known coordinates from Terrestrial Laser Scanning were used. The accuracy analysis showed that the accuracy of 3D models generated from video images is ±0.05 m.[b]Keywords[/b]: terrestrial photogrammetry, video, terrestrial laser scanning, 3D model, heritage objects

  20. 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. Co....... 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.......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...

  1. Robust watermarking of video objects for MPEG-4 applications

    Science.gov (United States)

    Bas, Patrick; Boulgouris, Nikolaos V.; Koravos, Filippos D.; Chassery, Jean-Marc; Strintzis, Michael G.; Macq, Benoit M. M.

    2001-12-01

    This paper presents two different watermarking schemes devoted to protect video objects. The first presented scheme performs embedding and detection in the uncompressed domain. It has been developed to enable signature detection after object manipulations such as rotations, translations and VOL modifications. To achieve these requirements, the first scheme exploits the shape of the object using CPA analysis: a random sequence is transformed to fit the scale and the orientation of the object. The detection of the mark is performed applying an inverse transform and calculating a correlation between the random sequence and the transformed object. The second scheme is based on compressed-domain processing of video objects. Two different signals are embedded, one for synchronization recovery and another for copyright protection. Both signals are embedded and detected in the compressed domain. During detection, first synchronization recovery is performed and then the copyright watermark is extracted.

  2. Extended Keyframe Detection with Stable Tracking for Multiple 3D Object Tracking.

    Science.gov (United States)

    Youngmin Park; Lepetit, V; Woontack Woo

    2011-11-01

    We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches and demonstrate our method on several real sequences.

  3. Homography-based grasp tracking for planar objects

    NARCIS (Netherlands)

    Carloni, Raffaella; Recatala, Gabriel; Melchiorri, Claudio; Sanz, Pedro J.; Cervera, Enric

    The visual tracking of grasp points is an essential operation for the execution of an approaching movement of a robot arm to an object: the grasp points are used as features for the definition of the control law. This work describes a strategy for tracking grasps on planar objects based on the use

  4. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Lien Kuo-Chin

    2008-01-01

    Full Text Available Abstract Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  5. Real-time moving objects detection and tracking from airborne infrared camera

    Science.gov (United States)

    Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

    2017-10-01

    Detecting and tracking moving objects in real-time from an airborne infrared (IR) camera offers interesting possibilities in video surveillance, remote sensing and computer vision applications, such as monitoring large areas simultaneously, quickly changing the point of view on the scene and pursuing objects of interest. To fully exploit such a potential, versatile solutions are needed, but, in the literature, the majority of them works only under specific conditions about the considered scenario, the characteristics of the moving objects or the aircraft movements. In order to overcome these limitations, we propose a novel approach to the problem, based on the use of a cheap inertial navigation system (INS), mounted on the aircraft. To exploit jointly the information contained in the acquired video sequence and the data provided by the INS, a specific detection and tracking algorithm has been developed. It consists of three main stages performed iteratively on each acquired frame. The detection stage, in which a coarse detection map is computed, using a local statistic both fast to calculate and robust to noise and self-deletion of the targeted objects. The registration stage, in which the position of the detected objects is coherently reported on a common reference frame, by exploiting the INS data. The tracking stage, in which the steady objects are rejected, the moving objects are tracked, and an estimation of their future position is computed, to be used in the subsequent iteration. The algorithm has been tested on a large dataset of simulated IR video sequences, recreating different environments and different movements of the aircraft. Promising results have been obtained, both in terms of detection and false alarm rate, and in terms of accuracy in the estimation of position and velocity of the objects. In addition, for each frame, the detection and tracking map has been generated by the algorithm, before the acquisition of the subsequent frame, proving its

  6. Automatic flame tracking technique for atrium fire from video images

    Science.gov (United States)

    Li, Jin; Lu, Puyi; Fong, Naikong; Chow, Wanki; Wong, Lingtim; Xu, Dianguo

    2005-02-01

    Smoke control is one of the important aspects in atrium fire. For an efficient smoke control strategy, it is very important to identify the smoke and fire source in a very short period of time. However, traditional methods such as point type detectors are not effective for smoke and fire detection in large space such as atrium. Therefore, video smoke and fire detection systems are proposed. For the development of the system, automatic extraction and tracking of flame are two important problems needed to be solved. Based on entropy theory, region growing and Otsu method, a new automatic integrated algorithm, which is used to track flame from video images, is proposed in this paper. It can successfully identify flames from different environment, different background and in different form. The experimental results show that this integrated algorithm has stronger robustness and wider adaptability. In addition, because of the low computational demand of this algorithm, it is also possible to be used as part of a robust, real-time smoke and fire detection system.

  7. 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.

  8. Tracking of multiple points using color video image analyzer

    Science.gov (United States)

    Nennerfelt, Leif

    1990-08-01

    The Videomex-X is a new product intended for use in biomechanical measurement. It tracks up to six points at 60 frames per second using colored markers placed on the subject. The system can be used for applications such as gait analysis, studying facial movements, or tracking the pattern of movements of individuals in a group. The Videomex-X is comprised of a high speed color image analyzer, an RBG color video camera, an IBM AT compatible computer and motion analysis software. The markers are made from brightly colored plastic disks and each marker is a different color. Since the markers are unique, the problem of misidentification of markers does not occur. The Videomex-X performs realtime analysis so that the researcher can get immediate feedback on the subject's performance. High speed operation is possible because the system uses distributed processing. The image analyzer is a hardwired parallel image processor which identifies the markers within the video picture and computes their x-y locations. The image analyzer sends the x-y coordinates to the AT computer which performs additional analysis and presents the result. The x-y coordinate data acquired during the experiment may be streamed to the computer's hard disk. This allows the data to be re-analyzed repeatedly using different analysis criteria. The original Videomex-X tracked in two dimensions. However, a 3-D system has recently been completed. The algorithm used by the system to derive performance results from the x-y coordinates is contained in a separate ASCII file. These files can be modified by the operator to produce the required type of data reduction.

  9. Causal Video Object Segmentation From Persistence of Occlusions

    Science.gov (United States)

    2015-05-01

    spond to “objects” is elusive absent an explicit definition of objects that has a measurable correlate in the image. Gestalt principles [33] provide...object segmentation with no consideration for depth ordering), on which we focus, as well as BVSD [17] ( designed for video segmentation). Evaluation...by Gestalt principles to arrive at a con- vex optimization scheme that can be efficiently solved with primal-dual methods. To compare with existing

  10. 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.

  11. 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.

  12. 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.

  13. Optical tracking of embryonic vertebrates behavioural responses using automated time-resolved video-microscopy system

    Science.gov (United States)

    Walpitagama, Milanga; Kaslin, Jan; Nugegoda, Dayanthi; Wlodkowic, Donald

    2016-12-01

    The fish embryo toxicity (FET) biotest performed on embryos of zebrafish (Danio rerio) has gained significant popularity as a rapid and inexpensive alternative approach in chemical hazard and risk assessment. The FET was designed to evaluate acute toxicity on embryonic stages of fish exposed to the test chemical. The current standard, similar to most traditional methods for evaluating aquatic toxicity provides, however, little understanding of effects of environmentally relevant concentrations of chemical stressors. We postulate that significant environmental effects such as altered motor functions, physiological alterations reflected in heart rate, effects on development and reproduction can occur at sub-lethal concentrations well below than LC10. Behavioral studies can, therefore, provide a valuable integrative link between physiological and ecological effects. Despite the advantages of behavioral analysis development of behavioral toxicity, biotests is greatly hampered by the lack of dedicated laboratory automation, in particular, user-friendly and automated video microscopy systems. In this work we present a proof-of-concept development of an optical system capable of tracking embryonic vertebrates behavioral responses using automated and vastly miniaturized time-resolved video-microscopy. We have employed miniaturized CMOS cameras to perform high definition video recording and analysis of earliest vertebrate behavioral responses. The main objective was to develop a biocompatible embryo positioning structures that were suitable for high-throughput imaging as well as video capture and video analysis algorithms. This system should support the development of sub-lethal and behavioral markers for accelerated environmental monitoring.

  14. Group Tracking of Space Objects within Bayesian Framework

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2013-03-01

    Full Text Available It is imperative to efficiently track and catalogue the extensive dense group space objects for space surveillance. As the main instrument for Low Earth Orbit (LEO space surveillance, ground-based radar system is usually limited by its resolving power while tracking the small space debris with high dense population. Thus, the obtained information about target detection and observation will be seriously missed, which makes the traditional tracking method inefficient. Therefore, we conceived the concept of group tracking. The overall motional tendency of the group objects is particularly focused, while the individual object is simultaneously tracked in effect. The tracking procedure is based on the Bayesian frame. According to the restriction among the group center and observations of multi-targets, the reconstruction of targets’ number and estimation of individual trajectory can be greatly improved on the accuracy and robustness in the case of high miss alarm. The Markov Chain Monte Carlo Particle (MCMC-Particle algorism is utilized for solving the Bayesian integral problem. Finally, the simulation of the group space objects tracking is carried out to validate the efficiency of the proposed method.

  15. 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.

  16. Physical models for moving shadow and object detection in video.

    Science.gov (United States)

    Nadimi, Sohail; Bhanu, Bir

    2004-08-01

    Current moving object detection systems typically detect shadows cast by the moving object as part of the moving object. In this paper, the problem of separating moving cast shadows from the moving objects in an outdoor environment is addressed. Unlike previous work, we present an approach that does not rely on any geometrical assumptions such as camera location and ground surface/object geometry. The approach is based on a new spatio-temporal albedo test and dichromatic reflection model and accounts for both the sun and the sky illuminations. Results are presented for several video sequences representing a variety of ground materials when the shadows are cast on different surface types. These results show that our approach is robust to widely different background and foreground materials, and illuminations.

  17. 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...... consecutive 12-h periods, alternating between white and red (lambda > 600 nm) illumination. Male spiders were significantly more locomotor active than female spiders under both lighting conditions. They walked, on average, twice the distance of females, employed higher velocities, and spent less time...

  18. 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.

  19. 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.

  20. Tracking Large-Scale Video Remix in Real-World Events

    OpenAIRE

    Xie, Lexing; Natsev, Apostol; He, Xuming; Kender, John; Hill, Matthew; Smith, John R

    2012-01-01

    Social information networks, such as YouTube, contains traces of both explicit online interaction (such as "like", leaving a comment, or subscribing to video feed), and latent interactions (such as quoting, or remixing parts of a video). We propose visual memes, or frequently re-posted short video segments, for tracking such latent video interactions at scale. Visual memes are extracted by scalable detection algorithms that we develop, with high accuracy. We further augment visual memes with ...

  1. 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.

  2. 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.

  3. A change detection approach to moving object detection in low frame-rate video

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Harvey, Neal R [Los Alamos National Laboratory; Theiler, James P [Los Alamos National Laboratory

    2009-01-01

    Moving object detection is of significant interest in temporal image analysis since it is a first step in many object identification and tracking applications. A key component in almost all moving object detection algorithms is a pixel-level classifier, where each pixel is predicted to be either part of a moving object or part of the background. In this paper we investigate a change detection approach to the pixel-level classification problem and evaluate its impact on moving object detection. The change detection approach that we investigate was previously applied to multi-and hyper-spectral datasets, where images were typically taken several days, or months apart. In this paper, we apply the approach to low-frame rate (1-2 frames per second) video datasets.

  4. Online object tracking via bag-of-local-patches

    Science.gov (United States)

    Wang, Zhihui; Bo, Chunjuan; Wang, Dong

    2017-01-01

    As one of the most important tasks in computer vision, online object tracking plays a critical role in numerous lines of research, which has drawn a lot of researchers' attention and be of many realistic applications. This paper develops a novel tracking algorithm based on the bag-of-local-patches representation with the discriminative learning scheme. In the first frame, a codebook is learned by applying the Kmeans algorithm to a set of densely sampled local patches of the tracked object, and then used to represent the template and candidate samples. During the tracking process, the similarities between the coding coefficients of the candidates and template are chosen as the likelihood values of these candidates. In addition, we propose effective model updating and discriminative learning schemes to capture the appearance change of the tracked object and incorporate the discriminative information to achieve a robust matching. Both qualitative and quantitative evaluations on some challenging image sequences demonstrate that the proposed tracker performs better than other state-of-the-art tracking methods.

  5. An object detection and tracking system for unmanned surface vehicles

    Science.gov (United States)

    Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

    2017-10-01

    Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

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

    Science.gov (United States)

    2013-10-03

    1 are the average per-frame pix- el error rate compared to the ground-truth. The definition is [20]: error = XOR (f,GT ) F , (11) where f is the...object cutout using localized classifiers. ACM Transactions on Graphics , 28(3):70, 2009. [3] W. Brendel and S. Todorovic. Video object segmentation by...anisotropic kernel mean shift. In ECCV, 2004. [12] J. Kleinberg and E. Tardos. Algorithm design . Pearson Edu- cation and Addison Wesley, 2006. [13] Y

  11. 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

  12. Using LabView for real-time monitoring and tracking of multiple biological objects

    Science.gov (United States)

    Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

    2017-04-01

    Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

  13. 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.

  14. Simultaneous video stabilization and moving object detection in turbulence.

    Science.gov (United States)

    Oreifej, Omar; Li, Xin; Shah, Mubarak

    2013-02-01

    Turbulence mitigation refers to the stabilization of videos with nonuniform deformations due to the influence of optical turbulence. Typical approaches for turbulence mitigation follow averaging or dewarping techniques. Although these methods can reduce the turbulence, they distort the independently moving objects, which can often be of great interest. In this paper, we address the novel problem of simultaneous turbulence mitigation and moving object detection. We propose a novel three-term low-rank matrix decomposition approach in which we decompose the turbulence sequence into three components: the background, the turbulence, and the object. We simplify this extremely difficult problem into a minimization of nuclear norm, Frobenius norm, and l1 norm. Our method is based on two observations: First, the turbulence causes dense and Gaussian noise and therefore can be captured by Frobenius norm, while the moving objects are sparse and thus can be captured by l1 norm. Second, since the object's motion is linear and intrinsically different from the Gaussian-like turbulence, a Gaussian-based turbulence model can be employed to enforce an additional constraint on the search space of the minimization. We demonstrate the robustness of our approach on challenging sequences which are significantly distorted with atmospheric turbulence and include extremely tiny moving objects.

  15. A novel video tracking method to evaluate the effect of influenza infection and antiviral treatment on ferret activity.

    Science.gov (United States)

    Oh, Ding Yuan; Barr, Ian G; Hurt, Aeron C

    2015-01-01

    Ferrets are the preferred animal model to assess influenza virus infection, virulence and transmission as they display similar clinical symptoms and pathogenesis to those of humans. Measures of disease severity in the ferret include weight loss, temperature rise, sneezing, viral shedding and reduced activity. To date, the only available method for activity measurement has been the assignment of an arbitrary score by a 'blind' observer based on pre-defined responsiveness scale. This manual scoring method is subjective and can be prone to bias. In this study, we described a novel video-tracking methodology for determining activity changes in a ferret model of influenza infection. This method eliminates the various limitations of manual scoring, which include the need for a sole 'blind' observer and the requirement to recognise the 'normal' activity of ferrets in order to assign relative activity scores. In ferrets infected with an A(H1N1)pdm09 virus, video-tracking was more sensitive than manual scoring in detecting ferret activity changes. Using this video-tracking method, oseltamivir treatment was found to ameliorate the effect of influenza infection on activity in ferret. Oseltamivir treatment of animals was associated with an improvement in clinical symptoms, including reduced inflammatory responses in the upper respiratory tract, lower body weight loss and a smaller rise in body temperature, despite there being no significant reduction in viral shedding. In summary, this novel video-tracking is an easy-to-use, objective and sensitive methodology for measuring ferret activity.

  16. 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...

  17. Construction of a Video Dataset for Face Tracking Benchmarking Using a Ground Truth Generation Tool

    National Research Council Canada - National Science Library

    Luu Ngoc Do; Hyung Jeong Yang; Soo Hyung Kim; Guee Sang Lee; In Seop Na; Sun Hee Kim

    2014-01-01

    .... Because human face tracking can be widely used for many applications, collecting a dataset of face videos is necessary for evaluating the performance of a tracker and for comparing different approaches...

  18. 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.

  19. 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

  20. 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.

  1. Video Salient Object Detection via Fully Convolutional Networks.

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Shao, Ling

    This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image data sets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the densely annotated video segmentation data set (MAE of .06) and the Freiburg-Berkeley Motion Segmentation data set (MAE of .07), and do so with much improved speed (2 fps with all steps).This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further

  2. Upgrading of efficiency in the tracking of body markers with video techniques

    NARCIS (Netherlands)

    L. Keemink (Lianne); G.A. Hoek van Dijke; C.J. Snijders (Chris)

    1991-01-01

    markdownabstractAbstract Based on a VME system, a low-cost video system has been developed for recording human motion. The paper describes the algorithm which is used for the recordings. The video system makes it possible to track in real time up to six markers on the body, sampled at a 50 Hz

  3. A Unified Framework for Tracking Based Text Detection and Recognition from Web Videos.

    Science.gov (United States)

    Tian, Shu; Yin, Xu-Cheng; Su, Ya; Hao, Hong-Wei

    2017-04-12

    Video text extraction plays an important role for multimedia understanding and retrieval. Most previous research efforts are conducted within individual frames. A few of recent methods, which pay attention to text tracking using multiple frames, however, do not effectively mine the relations among text detection, tracking and recognition. In this paper, we propose a generic Bayesian-based framework of Tracking based Text Detection And Recognition (T2DAR) from web videos for embedded captions, which is composed of three major components, i.e., text tracking, tracking based text detection, and tracking based text recognition. In this unified framework, text tracking is first conducted by tracking-by-detection. Tracking trajectories are then revised and refined with detection or recognition results. Text detection or recognition is finally improved with multi-frame integration. Moreover, a challenging video text (embedded caption text) database (USTB-VidTEXT) is constructed and publicly available. A variety of experiments on this dataset verify that our proposed approach largely improves the performance of text detection and recognition from web videos.

  4. 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.

  5. 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...... approximately down to CCD magnitude mv 7.5), the objects thus listed will include galaxies, nebulae, planets, asteroids, comets and artefacts as satellites.The angular resolution in inertial reference coordinates is a few arcseconds, allowing quite accurate tracking of these objects. Furthermore, the objects...... are easily divided into two classes; Stationary (galaxies, nebulae etc.), and moving object (planets, asteroids, satellite etc.).For missions targeting moving objects, detection down to mv 11 is possible without any system impacts, simply by comparing lists of objects with regular intervals, leaving out all...

  6. 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.

  7. 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).

  8. An algorithm of adaptive scale object tracking in occlusion

    Science.gov (United States)

    Zhao, Congmei

    2017-05-01

    Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

  9. 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.

  10. 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...

  11. Online structured sparse learning with labeled information for robust object tracking

    Science.gov (United States)

    Fan, Baojie; Cong, Yang; Tang, Yandong

    2017-01-01

    We formulate object tracking under the particle filter framework as a collaborative tracking problem. The priori information from training data is exploited effectively to online learn a discriminative and reconstructive dictionary, simultaneously without losing structural information. Specifically, the class label and the semantic structure information are incorporated into the dictionary learning process as the classification error term and ideal coding regularization term, respectively. Combined with the traditional reconstruction error, a unified dictionary learning framework for robust object tracking is constructed. By minimizing the unified objective function with different mixed norm constraints on sparse coefficients, two robust optimizing methods are developed to learn the high-quality dictionary and optimal classifier simultaneously. The best candidate is selected by minimizing the reconstructive error and classification error jointly. As the tracking continues, the proposed algorithms alternate between the robust sparse coding and the dictionary updating. The proposed trackers are empirically compared with 14 state-of-the-art trackers on some challenging video sequences. Both quantitative and qualitative comparisons demonstrate that the proposed algorithms perform well in terms of accuracy and robustness.

  12. A Computer Vision Approach to Object Tracking and Counting

    Directory of Open Access Journals (Sweden)

    Sergiu Mezei

    2010-09-01

    Full Text Available This paper, introduces a new method for counting people or more generally objects that enter or exit a certain area/building or perimeter. We propose an algorithm (method that analyzes a video sequence, detects moving objects and their moving direction and filters them according to some criteria (ex only humans. As result one obtains in and out counters for objects passing the defined perimeter. Automatic object counting is a growing size application in many industry/commerce areas. Counting can be used in statistical analysis and optimal activity scheduling methods. One of the main applications is the approximation of the number of persons passing trough, or reaching a certain area: airports (customs, shopping centers and malls and sports or cultural activities with high attendance. The main purpose is to offer an accurate estimation while still keeping the anonymity of the visitors.

  13. Object tracking in video with TensorFlow

    OpenAIRE

    Ferri, Andrea

    2016-01-01

    This Thesis[13] was born as collaboration between the BSC Computer Science Department [5] and the UPC Image Processing Group [23], with the purpose to develop an hybrid thesis on Deep Learning. Nowadays, the interest around Machine Learning, is one of the fastest growing. So far from the side of the BSC Computer Science Department [5], that mainly uses his computational power for data mining and modelling analysis, the main purpose was to verify the difficulty to adapt his i...

  14. Tracking individuals in surveillance video of a high-density crowd

    NARCIS (Netherlands)

    Hu, N.; Bouma, H.; Worring, M.

    2012-01-01

    Video cameras are widely used for monitoring public areas, such as train stations, airports and shopping centers. When crowds are dense, automatically tracking individuals becomes a challenging task. We propose a new tracker which employs a particle filter tracking framework, where the state

  15. Video Salient Object Detection via Fully Convolutional Networks

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Shao, Ling

    2018-01-01

    This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: (1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data, and (2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image datasets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the DAVIS dataset (MAE of .06) and the FBMS dataset (MAE of .07), and do so with much improved speed (2fps with all steps).

  16. Vision-Based Object Tracking Algorithm With AR. Drone

    Directory of Open Access Journals (Sweden)

    It Nun Thiang

    2015-08-01

    Full Text Available This paper presents a simple and effective vision-based algorithm for autonomous object tracking of a low-cost AR.Drone quadrotor for moving ground and flying targets. The Open-CV is used for computer vision to estimate the position of the object considering the environmental lighting effect. This is also an off-board control as the visual tracking and control process are performed in the laptop with the help of Wi-Fi link. The information obtained from vision algorithm is used to control roll angle and pitch angle of the drone in the case using bottom camera and to control yaw angle and altitude of the drone when the front camera is used as vision sensor. The experimental results from real tests are presented.

  17. 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.

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

    Science.gov (United States)

    2015-09-01

    the performer moved the field of digital provenance forward by designing and implementing techniques for following the chain of custody of data in a... chain of custody of data in a virtualized environment. Specifically, we provided an approach for tracking accesses to objects that originate from...automatically record events that are causally related to each other, and to chain sequences of events. Intuitively, events may be causally related if

  19. Comparison of Three Approximate Kinematic Models for Space Object Tracking

    Science.gov (United States)

    2013-07-01

    Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law , no person shall be subject to a...motion of an Earth orbiting SO follows Newton’s law of universal gravitation and is nonlinear in the ECI (Cartesian) Coordinates. The orbit information...Management for Collision Alert in Orbital Object Tracking,” Proc. SPIE 8044, 2011. [22] Wikipedia, “ Kepler Orbit,” URL: http://en.wikipedia.org/wiki

  20. 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

  1. A Multitarget Tracking Video System Based on Fuzzy and Neuro-Fuzzy Techniques

    Directory of Open Access Journals (Sweden)

    Javier I. Portillo

    2005-08-01

    Full Text Available Automatic surveillance of airport surface is one of the core components of advanced surface movement, guidance, and control systems (A-SMGCS. This function is in charge of the automatic detection, identification, and tracking of all interesting targets (aircraft and relevant ground vehicles in the airport movement area. This paper presents a novel approach for object tracking based on sequences of video images. A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets from the image regions extracted in the images. The advantages of this approach are robustness, flexibility in the design to adapt to different situations, and efficiency for operation in real time, avoiding combinatorial enumeration. Results obtained in representative ground operations show the system capabilities to solve complex scenarios and improve tracking accuracy. Finally, an automatic procedure, based on neuro-fuzzy techniques, has been applied in order to obtain a set of rules from representative examples. Validation of learned system shows the capability to learn the suitable tracker decisions.

  2. A real-time 3D video tracking system for monitoring primate groups.

    Science.gov (United States)

    Ballesta, S; Reymond, G; Pozzobon, M; Duhamel, J-R

    2014-08-30

    To date, assessing the solitary and social behaviors of laboratory primates' colonies relies on time-consuming manual scoring methods. Here, we describe a real-time multi-camera 3D tracking system developed to measure the behavior of socially-housed primates. Their positions are identified using non-invasive color markers such as plastic collars, thus allowing to also track colored objects and to measure their usage. Compared to traditional manual ethological scoring, we show that this system can reliably evaluate solitary behaviors (foraging, solitary resting, toy usage, locomotion) as well as spatial proximity with peers, which is considered as a good proxy of their social motivation. Compared to existing video-based commercial systems currently available to measure animal activity, this system offers many possibilities (real-time data, large volume coverage, multiple animal tracking) at a lower hardware cost. Quantitative behavioral data of animal groups can now be obtained automatically over very long periods of time, thus opening new perspectives in particular for studying the neuroethology of social behavior in primates. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. 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.

  4. APPLICATION OF BINARY DESCRIPTORS TO MULTIPLE FACE TRACKING IN VIDEO SURVEILLANCE SYSTEMS

    Directory of Open Access Journals (Sweden)

    A. L. Oleinik

    2016-07-01

    Full Text Available Subject of Research. The paper deals with the problem of multiple face tracking in a video stream. The primary application of the implemented tracking system is the automatic video surveillance. The particular operating conditions of surveillance cameras are taken into account in order to increase the efficiency of the system in comparison to existing general-purpose analogs. Method. The developed system is comprised of two subsystems: detector and tracker. The tracking subsystem does not depend on the detector, and thus various face detection methods can be used. Furthermore, only a small portion of frames is processed by the detector in this structure, substantially improving the operation rate. The tracking algorithm is based on BRIEF binary descriptors that are computed very efficiently on modern processor architectures. Main Results. The system is implemented in C++ and the experiments on the processing rate and quality evaluation are carried out. MOTA and MOTP metrics are used for tracking quality measurement. The experiments demonstrated the four-fold processing rate gain in comparison to the baseline implementation that processes every video frame with the detector. The tracking quality is on the adequate level when compared to the baseline. Practical Relevance. The developed system can be used with various face detectors (including slow ones to create a fully functional high-speed multiple face tracking solution. The algorithm is easy to implement and optimize, so it may be applied not only in full-scale video surveillance systems, but also in embedded solutions integrated directly into cameras.

  5. Integration of Video Images and CAD Wireframes for 3d Object Localization

    Science.gov (United States)

    Persad, R. A.; Armenakis, C.; Sohn, G.

    2012-07-01

    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.

  6. 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.

  7. Online Object Tracking, Learning and Parsing with And-Or Graphs.

    Science.gov (United States)

    Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

    2017-12-01

    This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

  8. Visual Tracking Utilizing Object Concept from Deep Learning Network

    Science.gov (United States)

    Xiao, C.; Yilmaz, A.; Lia, S.

    2017-05-01

    Despite having achieved good performance, visual tracking is still an open area of research, especially when target undergoes serious appearance changes which are not included in the model. So, in this paper, we replace the appearance model by a concept model which is learned from large-scale datasets using a deep learning network. The concept model is a combination of high-level semantic information that is learned from myriads of objects with various appearances. In our tracking method, we generate the target's concept by combining the learned object concepts from classification task. We also demonstrate that the last convolutional feature map can be used to generate a heat map to highlight the possible location of the given target in new frames. Finally, in the proposed tracking framework, we utilize the target image, the search image cropped from the new frame and their heat maps as input into a localization network to find the final target position. Compared to the other state-of-the-art trackers, the proposed method shows the comparable and at times better performance in real-time.

  9. International Space Station Utilization: Tracking Investigations from Objectives to Results

    Science.gov (United States)

    Ruttley, T. M.; Mayo, Susan; Robinson, J. A.

    2011-01-01

    Since the first module was assembled on the International Space Station (ISS), on-orbit investigations have been underway across all scientific disciplines. The facilities dedicated to research on ISS have supported over 1100 investigations from over 900 scientists representing over 60 countries. Relatively few of these investigations are tracked through the traditional NASA grants monitoring process and with ISS National Laboratory use growing, the ISS Program Scientist s Office has been tasked with tracking all ISS investigations from objectives to results. Detailed information regarding each investigation is now collected once, at the first point it is proposed for flight, and is kept in an online database that serves as a single source of information on the core objectives of each investigation. Different fields are used to provide the appropriate level of detail for research planning, astronaut training, and public communications. http://www.nasa.gov/iss-science/. With each successive year, publications of ISS scientific results, which are used to measure success of the research program, have shown steady increases in all scientific research areas on the ISS. Accurately identifying, collecting, and assessing the research results publications is a challenge and a priority for the ISS research program, and we will discuss the approaches that the ISS Program Science Office employs to meet this challenge. We will also address the online resources available to support outreach and communication of ISS research to the public. Keywords: International Space Station, Database, Tracking, Methods

  10. 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.

  11. Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

    Science.gov (United States)

    Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

    2012-06-01

    We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

  12. 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.

  13. Multiphase joint segmentation-registration and object tracking for layered images.

    Science.gov (United States)

    Chen, Ping-Feng; Krim, Hamid; Mendoza, Olga L

    2010-07-01

    In this paper we propose to jointly segment and register objects of interest in layered images. Layered imaging refers to imageries taken from different perspectives and possibly by different sensors. Registration and segmentation are therefore the two main tasks which contribute to the bottom level, data alignment, of the multisensor data fusion hierarchical structures. Most exploitations of two layered images assumed that scanners are at very high altitudes and that only one transformation ties the two images. Our data are however taken at mid-range and therefore requires segmentation to assist us examining different object regions in a divide-and-conquer fashion. Our approach is a combination of multiphase active contour method with a joint segmentation-registration technique (which we called MPJSR) carried out in a local moving window prior to a global optimization. To further address layered video sequences and tracking objects in frames, we propose a simple adaptation of optical flow calculations along the active contours in a pair of layered image sequences. The experimental results show that the whole integrated algorithm is able to delineate the objects of interest, align them for a pair of layered frames and keep track of the objects over time.

  14. Tracking hidden objects with a single-photon camera

    CERN Document Server

    Gariepy, Genevieve; Henderson, Robert; Leach, Jonathan; Faccio, Daniele

    2015-01-01

    The ability to know what is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous solutions to this challenge were constrained e.g. by their physical size, the requirement of reflective surfaces or long data acquisition times. These impede both the deployment of the technology outside the laboratory and the development of significant advances, such as tracking the movement of large-scale hidden objects. We demonstrate a non-line-of-sight laser ranging technology that relies upon the ability, using only a floor surface, to send and detect light that is scattered around an obstacle. A single-photon avalanche diode (SPAD) camera detects light back-scattered from a hidden object that can then be located with centimetre precision, simultaneously tracking its movement. This non-line-of-sight laser ranging system is also shown to work at human length scales, paving the way for a variety of real-life situations.

  15. The Dynamic Model Embed in Augmented Graph Cuts for Robust Hand Tracking and Segmentation in Videos

    Directory of Open Access Journals (Sweden)

    Jun Wan

    2014-01-01

    Full Text Available Segmenting human hand is important in computer vision applications, for example, sign language interpretation, human computer interaction, and gesture recognition. However, some serious bottlenecks still exist in hand localization systems such as fast hand motion capture, hand over face, and hand occlusions on which we focus in this paper. We present a novel method for hand tracking and segmentation based on augmented graph cuts and dynamic model. First, an effective dynamic model for state estimation is generated, which correctly predicts the location of hands probably having fast motion or shape deformations. Second, new energy terms are brought into the energy function to develop augmented graph cuts based on some cues, namely, spatial information, hand motion, and chamfer distance. The proposed method successfully achieves hand segmentation even though the hand passes over other skin-colored objects. Some challenging videos are provided in the case of hand over face, hand occlusions, dynamic background, and fast motion. Experimental results demonstrate that the proposed method is much more accurate than other graph cuts-based methods for hand tracking and segmentation.

  16. 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.

  17. Learning to Detect Objects from Eye-Tracking Data

    Directory of Open Access Journals (Sweden)

    D.P Papadopoulous

    2014-08-01

    Full Text Available One of the bottlenecks in computer vision, especially in object detection, is the need for a large amount of training data. Typically, this is acquired by manually annotating images by hand. In this study, we explore the possibility of using eye-trackers to provide training data for supervised machine learning. We have created a new large scale eye-tracking dataset, collecting fixation data for 6270 images from the Pascal VOC 2012 database. This represents 10 of the 20 classes included in the Pascal database. Each image was viewed by 5 observers, and a total of over 178k fixations have been collected. While previous attempts at using fixation data in computer vision were based on a free-viewing paradigm, we used a visual search task in order to increase the proportion of fixations on the target object. Furthermore, we divided the dataset into five pairs of semantically similar classes (cat/dog, bicycle/motorbike, horse/cow, boat/aeroplane and sofa/diningtable, with the observer having to decide which class each image belonged to. This kept the observer's task simple, while decreasing the chance of them using the scene gist to identify the target parafoveally. In order to alleviate the central bias in scene viewing, the images were presented to the observers with a random offset. The goal of our project is to use the eye-tracking information in order to detect and localise the attended objects. Our model so far, based on features representing the location of the fixations and an appearance model of the attended regions, can successfully predict the location of the target objects in over half of images.

  18. 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...... in estimating the subjective quality results....

  19. 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.

  20. 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.

  1. ‘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.

  2. A Gaussian process guided particle filter for tracking 3D human pose in video.

    Science.gov (United States)

    Sedai, Suman; Bennamoun, Mohammed; Huynh, Du Q

    2013-11-01

    In this paper, we propose a hybrid method that combines Gaussian process learning, a particle filter, and annealing to track the 3D pose of a human subject in video sequences. Our approach, which we refer to as annealed Gaussian process guided particle filter, comprises two steps. In the training step, we use a supervised learning method to train a Gaussian process regressor that takes the silhouette descriptor as an input and produces multiple output poses modeled by a mixture of Gaussian distributions. In the tracking step, the output pose distributions from the Gaussian process regression are combined with the annealed particle filter to track the 3D pose in each frame of the video sequence. Our experiments show that the proposed method does not require initialization and does not lose tracking of the pose. We compare our approach with a standard annealed particle filter using the HumanEva-I dataset and with other state of the art approaches using the HumanEva-II dataset. The evaluation results show that our approach can successfully track the 3D human pose over long video sequences and give more accurate pose tracking results than the annealed particle filter.

  3. 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...

  4. 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

  5. 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

  6. Tracking Multiple Video Targets with an Improved GM-PHD Tracker.

    Science.gov (United States)

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

    2015-12-03

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

  7. Tracking Multiple Video Targets with an Improved GM-PHD Tracker

    Directory of Open Access Journals (Sweden)

    Xiaolong Zhou

    2015-12-01

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

  8. 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.

  9. Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

    Science.gov (United States)

    Marrón-Romera, Marta; García, Juan C.; Sotelo, Miguel A.; Pizarro, Daniel; Mazo, Manuel; Cañas, José M.; Losada, Cristina; Marcos, Álvaro

    2010-01-01

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found. PMID:22163385

  10. Stereo vision tracking of multiple objects in complex indoor environments.

    Science.gov (United States)

    Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro

    2010-01-01

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

  11. Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

    Directory of Open Access Journals (Sweden)

    Álvaro Marcos

    2010-09-01

    Full Text Available This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

  12. PRICISE TARGET GEOLOCATION AND TRACKING BASED ON UAV VIDEO IMAGERY

    Directory of Open Access Journals (Sweden)

    H. R. Hosseinpoor

    2016-06-01

    Full Text Available 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.

  13. High-speed digital video tracking system for generic applications

    Science.gov (United States)

    Walton, James S.; Hallamasek, Karen G.

    2001-04-01

    The value of high-speed imaging for making subjective assessments is widely recognized, but the inability to acquire useful data from image sequences in a timely fashion has severely limited the use of the technology. 4DVideo has created a foundation for a generic instrument that can capture kinematic data from high-speed images. The new system has been designed to acquire (1) two-dimensional trajectories of points; (2) three-dimensional kinematics of structures or linked rigid-bodies; and (3) morphological reconstructions of boundaries. The system has been designed to work with an unlimited number of cameras configured as nodes in a network, with each camera able to acquire images at 1000 frames per second (fps) or better, with a spatial resolution of 512 X 512 or better, and an 8-bit gray scale. However, less demanding configurations are anticipated. The critical technology is contained in the custom hardware that services the cameras. This hardware optimizes the amount of information stored, and maximizes the available bandwidth. The system identifies targets using an algorithm implemented in hardware. When complete, the system software will provide all of the functionality required to capture and process video data from multiple perspectives. Thereafter it will extract, edit and analyze the motions of finite targets and boundaries.

  14. How many objects are you worth? Quantification of the self-motion load on multiple object tracking

    Directory of Open Access Journals (Sweden)

    Laura Elizabeth Thomas

    2011-09-01

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

  15. Tracking Deforming Objects using Particle Filtering for Geometric Active Contours

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Vaswani, Namrata; Tannenbaum, Allen; Yezzi, Anthony

    2007-01-01

    .... Tracking algorithms using Kalman filters or particle filters have been proposed for finite dimensional representations of shape, but these are dependent on the chosen parametrization and cannot...

  16. 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…

  17. TotalTrack video intubating laryngeal mask in super-obese patients – series of cases

    Directory of Open Access Journals (Sweden)

    Gaszynski T

    2016-03-01

    Full Text Available Tomasz Gaszynski Department of Emergency and Disaster Medicine, Medical University of Lodz, Lodz, Poland Background: Super-obese patients are at increased risk of difficult mask ventilation and difficult intubation. Therefore, devices that allow for simultaneous ventilation/oxygenation during attempts to visualize the entrance to the larynx, increase patient safety. TotalTrack video intubating laryngeal mask is a new device that allows for ventilation during intubation efforts. Patients and methods: Twenty-four super-obese patients (body mass index >50 kg/m2 were divided into two subgroups: intubation efforts using 1 TotalTrack and 2 Macintosh blade standard laryngoscope in induction of general anesthesia. Visualization and successful intubation was evaluated for both groups with ventilation and post-mask complications additionally evaluated for TotalTrack. Results: In all cases in the TotalTrack group, the Cormack-Lehane score was 1, ventilation and intubation was successful in 11/12 patients. No hypoxia during intubation efforts was recorded. No serious complications of use of TotalTrack were observed. In the Macintosh blade laryngoscope group, all patients were intubated, but the Cormack-Lehane score was 2 in four cases, and 3 in three cases. Conclusion: TotalTrack video intubating laryngeal mask is a device that allows for better visualization of the larynx compared to the standard Macintosh blade laryngoscope, it provides effective ventilation/oxygenation and intubation in super-obese patients. Keywords: super-obese, intubation, ventilation, laryngeal mask, standard laryngoscope, video laryngoscope 

  18. 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.

  19. Tracking objects with fixed-wing UAV using model predictive control and machine vision

    OpenAIRE

    Skjong, Espen; Nundal, Stian Aas

    2014-01-01

    This thesis describes the development of an object tracking system for unmanned aerial vehicles (UAVs), intended to be used for search and rescue (SAR) missions. The UAV is equipped with a two-axis gimbal system, which houses an infrared (IR) camera used to detect and track objects of interest, and a lower level autopilot. An external computer vision (CV) module is assumed implemented and connected to the object tracking system, providing object positions and velocities to the control system....

  20. An improved mixture-of-Gaussians background model with frame difference and blob tracking in video stream.

    Science.gov (United States)

    Yao, Li; Ling, Miaogen

    2014-01-01

    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.

  1. 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.

  2. Object classification methods for application in FPGA based vehicle video detector

    Directory of Open Access Journals (Sweden)

    Wiesław PAMUŁA

    2009-01-01

    Full Text Available The paper presents a discussion of properties of object classification methods utilized in processing video streams from a camera. Methods based on feature extraction, model fitting and invariant determination are evaluated. Petri nets are used for modelling the processing flow. Data objects and transitions are defined which are suitable for efficient implementation in FPGA circuits. Processing characteristics and problems of the implementations are shown. An invariant based method is assessed as most suitable for application in a vehicle video detector.

  3. 2011 Tohoku tsunami video and TLS based measurements: hydrographs, currents, inundation flow velocities, and ship tracks

    Science.gov (United States)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Takeda, S.; Mohammed, F.; Skanavis, V.; Synolakis, C. E.; Takahashi, T.

    2012-12-01

    The March 11, 2011, magnitude Mw 9.0 earthquake off the coast of the Tohoku region caused catastrophic damage and loss of life in Japan. The mid-afternoon tsunami arrival combined with survivors equipped with cameras on top of vertical evacuation buildings provided spontaneous spatially and temporally resolved inundation recordings. This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Myako, Kamaishi, Kesennuma and Yoriisohama along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were explored, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance in April, 2011. A follow-up survey in June, 2011 focused on terrestrial laser scanning (TLS) at locations with high quality eyewitness videos. We acquired precise topographic data using TLS at the video sites producing a 3-dimensional "point cloud" dataset. A camera mounted on the Riegl VZ-400 scanner yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing. The original video recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). The analysis of the tsunami videos follows an adapted four step procedure originally developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on ground control points measured in the LiDAR data. In a second step the video image motion induced by the panning of the video camera was determined from subsequent images by particle image velocimetry (PIV) applied to fixed objects. The third step involves the transformation of the raw tsunami video images from image coordinates to world coordinates with a direct linear transformation (DLT) procedure. Finally, the instantaneous tsunami

  4. On metrics for objective and subjective evaluation of high dynamic range video

    Science.gov (United States)

    Minoo, Koohyar; Gu, Zhouye; Baylon, David; Luthra, Ajay

    2015-09-01

    In high dynamic range (HDR) video, it is possible to represent a wider range of intensities and contrasts compared to the current standard dynamic range (SDR) video. HDR video can simultaneously preserve details in very bright and very dark areas of a scene whereas these details become lost or washed out in SDR video. Because the perceived quality due to this increased fidelity may not fit the same model of perceived quality in the SDR video, it is not clear whether the objective metrics that have been widely used and studied for SDR visual experience are reasonably accurate for HDR cases, in terms of correlation with subjective measurement for HDR video quality. This paper investigates several objective metrics and their correlation to subjective quality for a variety of HDR video content. Results are given for the case of HDR content compressed at different bit rates. In addition to rating the relevance of each objective metric in terms of its correlation to the subjective measurements, comparisons are also presented to show how closely different objective metrics can predict the results obtained by subjective quality assessment in terms of coding efficiency provided by different coding processes.

  5. 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

  6. 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.

  7. Hyperspectral Foveated Imaging Sensor for Objects Identification and Tracking Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Optical tracking and identification sensors have numerous NASA and non-NASA applications. For example, airborne or spaceborne imaging sensors are used to visualize...

  8. Transmission of object based fine-granular-scalability video over networks

    Science.gov (United States)

    Shi, Xu-li; Jin, Zhi-cheng; Teng, Guo-wei; Zhang, Zhao-yang; An, Ping; Xiao, Guang

    2006-05-01

    It is a hot focus of current researches in video standards that how to transmit video streams over Internet and wireless networks. One of the key methods is FGS(Fine-Granular-Scalability), which can always adapt to the network bandwidth varying but with some sacrifice of coding efficiency, is supported by MPEG-4. Object-based video coding algorithm has been firstly included in MPEG-4 standard that can be applied in interactive video. However, the real time segmentation of VOP(video object plan) is difficult that limit the application of MPEG-4 standard in interactive video. H.264/AVC is the up-to-date video-coding standard, which enhance compression performance and provision a network-friendly video representation. In this paper, we proposed a new Object Based FGS(OBFGS) coding algorithm embedded in H.264/AVC that is different from that in mpeg-4. After the algorithms optimization for the H.264 encoder, the FGS first finish the base-layer coding. Then extract moving VOP using the base-layer information of motion vectors and DCT coefficients. Sparse motion vector field of p-frame composed of 4*4 blocks, 4*8 blocks and 8*4 blocks in base-layer is interpolated. The DCT coefficient of I-frame is calculated by using information of spatial intra-prediction. After forward projecting each p-frame vector to the immediate adjacent I-frame, the method extracts moving VOPs (video object plan) using a recursion 4*4 block classification process. Only the blocks that belong to the moving VOP in 4*4 block-level accuracy is coded to produce enhancement-layer stream. Experimental results show that our proposed system can obtain high interested VOP quality at the cost of fewer coding efficiency.

  9. 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.

  10. A combined object-tracking algorithm for omni-directional vision-based AGV navigation

    Science.gov (United States)

    Yuan, Wei; Sun, Jie; Cao, Zuo-Liang; Tian, Jing; Yang, Ming

    2010-03-01

    A combined object-tracking algorithm that realizes the realtime tracking of the selected object through the omni-directional vision with a fisheye lens is presented. The new method combines the modified continuously adaptive mean shift algorithm with the Kalman filter method. With the proposed method, the object-tracking problem when the object reappears after being sheltered completely or moving out of the field of view is solved. The experimental results perform well, and the algorithm proposed here improves the robustness and accuracy of the tracking in the omni-directional vision.

  11. Tracking of objectively measured physical activity from childhood to adolescence

    DEFF Research Database (Denmark)

    Kristensen, Peter Lund; Møller, N C; Korsholm, L

    2007-01-01

    A number of studies have investigated tracking of physical activity from childhood to adolescence and, in general, these studies have been based on methods with some degree of subjectivity (e.g., questionnaires). The aim of the present study was to evaluate tracking of physical activity from...... childhood to adolescence using accelerometry, taking into account major sources of variation in physical activity. Both a crude and an adjusted model was fitted, and, in the adjusted model, analyses were corrected for seasonal variation, within-week variation, activity registration during night time sleep......, in the adjusted model highly significant stability coefficients of 0.53 and 0.48 for boys and girls, respectively, were observed. It was concluded that physical activity behavior tends to track moderately from childhood to adolescence....

  12. 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.

  13. Robust deformable and occluded object tracking with dynamic graph.

    Science.gov (United States)

    Cai, Zhaowei; Wen, Longyin; Lei, Zhen; Vasconcelos, Nuno; Li, Stan Z

    2014-12-01

    While some efforts have been paid to handle deformation and occlusion in visual tracking, they are still great challenges. In this paper, a dynamic graph-based tracker (DGT) is proposed to address these two challenges in a unified framework. In the dynamic target graph, nodes are the target local parts encoding appearance information, and edges are the interactions between nodes encoding inner geometric structure information. This graph representation provides much more information for tracking in the presence of deformation and occlusion. The target tracking is then formulated as tracking this dynamic undirected graph, which is also a matching problem between the target graph and the candidate graph. The local parts within the candidate graph are separated from the background with Markov random field, and spectral clustering is used to solve the graph matching. The final target state is determined through a weighted voting procedure according to the reliability of part correspondence, and refined with recourse to a foreground/background segmentation. An effective online updating mechanism is proposed to update the model, allowing DGT to robustly adapt to variations of target structure. Experimental results show improved performance over several state-of-the-art trackers, in various challenging scenarios.

  14. Three-dimensional tracking of objects in holographic imaging

    Science.gov (United States)

    DaneshPanah, Mehdi; Javidi, Bahram

    2007-09-01

    In this paper we overview on a three dimensional imaging and tracking algorithm in order to track biological specimen in sequence of holographic microscopy images. We use a region tracking method based on MAP estimator in a Bayesian framework and we adapt it to 3D holographic data sequences to efficiently track the desired microorganism. In our formulation, the target-background interface is modeled as the isolevel of a level set function which is evolved at each frame via level set update rule. The statistical characteristics of the target microorganism versus the background are exploited to evolve the interface from one frame to another. Using the bivariate Gaussian distribution to model the reconstructed hologram data enables one to take into account the correlation between the amplitude and phase of the reconstructed field to obtain a more accurate solution. Also, the level set surface evolution provides a robust, efficient and numerically stable method which deals automatically with the change in the topology and geometrical deformations that a microorganism may be subject to.

  15. 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...

  16. Efficient Tracking of Moving Objects with Precision Guarantees

    DEFF Research Database (Denmark)

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

    2004-01-01

    We are witnessing continued improvements in wireless communications and geo-positioning. In addition, the performance/price ratio for consumer electronics continues to improve. These developments pave the way to a kind of location-based service that relies on the tracking of the continuously...

  17. Design of video surveillance and tracking system based on attitude and heading reference system and PTZ camera

    Science.gov (United States)

    Yang, Jian; Xie, Xiaofang; Wang, Yan

    2017-04-01

    Based on the AHRS (Attitude and Heading Reference System) and PTZ (Pan/Tilt/Zoom) camera, we designed a video monitoring and tracking system. The overall structure of the system and the software design are given. The key technologies such as serial port communication and head attitude tracking are introduced, and the codes of the key part are given.

  18. 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.

  19. Video-Based Eye Tracking in Sex Research: A Systematic Literature Review.

    Science.gov (United States)

    Wenzlaff, Frederike; Briken, Peer; Dekker, Arne

    2015-12-21

    Although eye tracking has been used for decades, it has gained popularity in the area of sex research only recently. The aim of this article is to examine the potential merits of eye tracking for this field. We present a systematic review of the current use of video-based eye-tracking technology in this area, evaluate the findings, and identify future research opportunities. A total of 34 relevant studies published between 2006 and 2014 were identified for inclusion by means of online databases and other methods. We grouped them into three main areas of research: body perception and attractiveness, forensic research, and sexual orientation. Despite the methodological and theoretical differences across the studies, eye tracking has been shown to be a promising tool for sex research. The article suggests there is much potential for further studies to employ this technique because it is noninvasive and yet still allows for the assessment of both conscious and unconscious perceptional processes. Furthermore, eye tracking can be implemented in investigations of various theoretical backgrounds, ranging from biology to the social sciences.

  20. Steady-state particle tracking in the object-oriented regional groundwater model ZOOMQ3D

    OpenAIRE

    Jackson, C.R.

    2002-01-01

    This report describes the development of a steady-state particle tracking code for use in conjunction with the object-oriented regional groundwater flow model, ZOOMQ3D (Jackson, 2001). Like the flow model, the particle tracking software, ZOOPT, is written using an object-oriented approach to promote its extensibility and flexibility. ZOOPT enables the definition of steady-state pathlines in three dimensions. Particles can be tracked in both the forward and reverse directions en...

  1. Automatic real-time tracking of fetal mouth in fetoscopic video sequence for supporting fetal surgeries

    Science.gov (United States)

    Xu, Rong; Xie, Tianliang; Ohya, Jun; Zhang, Bo; Sato, Yoshinobu; Fujie, Masakatsu G.

    2013-03-01

    Recently, a minimally invasive surgery (MIS) called fetoscopic tracheal occlusion (FETO) was developed to treat severe congenital diaphragmatic hernia (CDH) via fetoscopy, by which a detachable balloon is placed into the fetal trachea for preventing pulmonary hypoplasia through increasing the pressure of the chest cavity. This surgery is so dangerous that a supporting system for navigating surgeries is deemed necessary. In this paper, to guide a surgical tool to be inserted into the fetal trachea, an automatic approach is proposed to detect and track the fetal face and mouth via fetoscopic video sequencing. More specifically, the AdaBoost algorithm is utilized as a classifier to detect the fetal face based on Haarlike features, which calculate the difference between the sums of the pixel intensities in each adjacent region at a specific location in a detection window. Then, the CamShift algorithm based on an iterative search in a color histogram is applied to track the fetal face, and the fetal mouth is fitted by an ellipse detected via an improved iterative randomized Hough transform approach. The experimental results demonstrate that the proposed automatic approach can accurately detect and track the fetal face and mouth in real-time in a fetoscopic video sequence, as well as provide an effective and timely feedback to the robot control system of the surgical tool for FETO surgeries.

  2. Inpainting for videos with dynamic objects using texture and structure reconstruction

    Science.gov (United States)

    Voronin, V. V.; Marchuk, V. I.; Gapon, N. V.; Zhuravlev, A. V.; Maslennikov, S.; Stradanchenko, S.

    2015-05-01

    This paper describes a novel inpainting approach for removing marked dynamic objects from videos captured with a camera, so long as the objects occlude parts of the scene with a static background. Proposed approach allow to remove objects or restore missing or tainted regions present in a video sequence by utilizing spatial and temporal information from neighboring scenes. The algorithm iteratively performs following operations: achieve frame; update the scene model; update positions of moving objects; replace parts of the frame occupied by the objects marked for remove with use of a background model. In this paper, we extend an image inpainting algorithm based texture and structure reconstruction by incorporating an improved strategy for video. An image inpainting approach based on the construction of a composite curve for the restoration of the edges of objects in a frame using the concepts of parametric and geometric continuity is presented. It is shown that this approach allows to restore the curved edges and provide more flexibility for curve design in damaged frame by interpolating the boundaries of objects by cubic splines. After edge restoration stage, a texture reconstruction using patch-based method is carried out. We demonstrate the performance of a new approach via several examples, showing the effectiveness of our algorithm and compared with state-of-the-art video inpainting methods.

  3. Praćenje cilja pomoću video senzora primenom estimatora sa više modela / Target tracking by video sensor with multiple model approach

    Directory of Open Access Journals (Sweden)

    Dragoslav Ugarak

    2006-07-01

    Full Text Available U radu je opisan matematički model praćenja cilja na osnovu određivanja uglova i daljine cilja obradom video snimaka u toku praćenja. Izvršena je sinteza višemodelskog (MM estimatora stanja na bazi Kalmanovih filtera i utvrđena tačnost estimacije i predikcije kretanja cilja na konkretnom primeru. / This paper presents mathematical model of target tracking based on angle and target range determination by analyzing video frames during the tracking. The multiple model approach is performed using Kalman filter, and estimation and target motion prediction accuracy is determined using concrete example.

  4. Newton’s Cradle Experiment Using Video Tracking Analysis with Multiple Representation Approach

    Science.gov (United States)

    Anissofira, A.; Latief, F. D. E.; Kholida, L.; Sinaga, P.

    2017-09-01

    This paper reports a Physics lesson using video tracking analysis applied in Newton’s Cradle experiment to train student’s multiple representation skill. This study involved 30 science high school students from class XI. In this case, Tracker software was used to verify energy conservation law, with help from data result such as graphs and tables. Newton’s Cradle is commonly used to demonstrate the law of energy and momentum conservation. It consists of swinging spherical bobs which transfers energy from one to another by means of elastic collisions. From the video analysis, it is found that there is a difference in the velocity of the two bobs of opposite ends. Furthermore, investigation of what might cause it to happen can be done by observing and analysing the recorded video. This paper discusses students’ response and teacher’s reflection after using Tracker video analysis software in the Physics lesson. Since Tracker has the ability to provide us with multiple means of data representation way, we conclude that this method could be a good alternative solution and might also be considered better than performing a hands-on experiment activity in which not every school have suitable laboratory equipment.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Seufferlein Thomas

    2010-04-01

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

  7. 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.

  8. 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.

  9. Hidden communicative competence: case study evidence using eye-tracking and video analysis.

    Science.gov (United States)

    Grayson, Andrew; Emerson, Anne; Howard-Jones, Patricia; O'Neil, Lynne

    2012-01-01

    A facilitated communication (FC) user with an autism spectrum disorder produced sophisticated texts by pointing, with physical support, to letters on a letterboard while their eyes were tracked and while their pointing movements were video recorded. This FC user has virtually no independent means of expression, and is held to have no literacy skills. The resulting data were subjected to a variety of analyses aimed at describing the relationship between the FC user's looking and pointing behaviours, in order to make inferences about the complex question of 'authorship'. The eye-tracking data present a challenge to traditional 'facilitator influence' accounts of authorship, and are consistent with the proposition that this FC user does indeed author the sophisticated texts that are attributed to him; he looks for longer at to-be-typed letters before typing them, and looks ahead to subsequent letters of words before the next letter of the word is typed.

  10. 2011 Tohoku tsunami hydrographs, currents, flow velocities and ship tracks based on video and TLS measurements

    Science.gov (United States)

    Fritz, Hermann M.; Phillips, David A.; Okayasu, Akio; Shimozono, Takenori; Liu, Haijiang; Takeda, Seiichi; Mohammed, Fahad; Skanavis, Vassilis; Synolakis, Costas E.; Takahashi, Tomoyuki

    2013-04-01

    The March 11, 2011, magnitude Mw 9.0 earthquake off the Tohoku coast of Japan caused catastrophic damage and loss of life to a tsunami aware population. The mid-afternoon tsunami arrival combined with survivors equipped with cameras on top of vertical evacuation buildings provided fragmented spatially and temporally resolved inundation recordings. This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Myako, Kamaishi, Kesennuma and Yoriisohama along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were explored, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance in April, 2011. A follow-up survey in June, 2011 focused on terrestrial laser scanning (TLS) at locations with high quality eyewitness videos. We acquired precise topographic data using TLS at the video sites producing a 3-dimensional "point cloud" dataset. A camera mounted on the Riegl VZ-400 scanner yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing. The original video recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). The analysis of the tsunami videos follows an adapted four step procedure originally developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on ground control points measured in the LiDAR data. In a second step the video image motion induced by the panning of the video camera was determined from subsequent images by particle image velocimetry (PIV) applied to fixed objects. The third step involves the transformation of the raw tsunami video images from image coordinates to world coordinates with a direct linear transformation (DLT) procedure. Finally, the

  11. 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…

  12. Correlation and 3D-tracking of objects by pointing sensors

    Science.gov (United States)

    Griesmeyer, J. Michael

    2017-04-04

    A method and system for tracking at least one object using a plurality of pointing sensors and a tracking system are disclosed herein. In a general embodiment, the tracking system is configured to receive a series of observation data relative to the at least one object over a time base for each of the plurality of pointing sensors. The observation data may include sensor position data, pointing vector data and observation error data. The tracking system may further determine a triangulation point using a magnitude of a shortest line connecting a line of sight value from each of the series of observation data from each of the plurality of sensors to the at least one object, and perform correlation processing on the observation data and triangulation point to determine if at least two of the plurality of sensors are tracking the same object. Observation data may also be branched, associated and pruned using new incoming observation data.

  13. 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.

  14. Objective Video Quality Assessment Based on Machine Learning for Underwater Scientific Applications.

    Science.gov (United States)

    Moreno-Roldán, José-Miguel; Luque-Nieto, Miguel-Ángel; Poncela, Javier; Otero, Pablo

    2017-03-23

    Video services are meant to be a fundamental tool in the development of oceanic research. The current technology for underwater networks (UWNs) imposes strong constraints in the transmission capacity since only a severely limited bitrate is available. However, previous studies have shown that the quality of experience (QoE) is enough for ocean scientists to consider the service useful, although the perceived quality can change significantly for small ranges of variation of video parameters. In this context, objective video quality assessment (VQA) methods become essential in network planning and real time quality adaptation fields. This paper presents two specialized models for objective VQA, designed to match the special requirements of UWNs. The models are built upon machine learning techniques and trained with actual user data gathered from subjective tests. Our performance analysis shows how both of them can successfully estimate quality as a mean opinion score (MOS) value and, for the second model, even compute a distribution function for user scores.

  15. 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.

  16. Towards a Stable Robotic Object Manipulation Through 2D-3D Features Tracking

    Directory of Open Access Journals (Sweden)

    Sorin M. Grigorescu

    2013-04-01

    Full Text Available In this paper, a new object tracking system is proposed to improve the object manipulation capabilities of service robots. The goal is to continuously track the state of the visualized environment in order to send visual information in real time to the path planning and decision modules of the robot; that is, to adapt the movement of the robotic system according to the state variations appearing in the imaged scene. The tracking approach is based on a probabilistic collaborative tracking framework developed around a 2D patch-based tracking system and a 2D-3D point features tracker. The real-time visual information is composed of RGB-D data streams acquired from state-of-the-art structured light sensors. For performance evaluation, the accuracy of the developed tracker is compared to a traditional marker-based tracking system which delivers 3D information with respect to the position of the marker.

  17. Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

    Science.gov (United States)

    Tian, Yuan; Guan, Tao; Wang, Cheng

    2010-01-01

    To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

  18. MediaMill at TRECVID 2014: Searching Concepts, Objects, Instances and Events in Video

    NARCIS (Netherlands)

    Snoek, C.G.M.; van de Sande, K.E.A.; Fontijne, D.; Cappallo, S.; van Gemert, J.; Habibian, A.; Mensink, T.; Mettes, P.; Tao, R.; Koelma, D.C.; Smeulders, A.W.M.

    2014-01-01

    In this paper we summarize our TRECVID 2014 video retrieval experiments. The MediaMill team participated in five tasks: concept detection, object localization, instance search, event recognition and recounting. We experimented with concept detection using deep learning and color difference coding,

  19. 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.

  20. 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.

  1. Robust Object Tracking with a Hierarchical Ensemble Framework

    Science.gov (United States)

    2016-10-09

    significant- ly reduce the feature dimensions so that our approach can handle colorful images without suffering from exponential memory explosion; 4...objects can often distract such local patches and lead to drift. Matching mechanism is used to classify candidate regions which are most similar to

  2. Behavioral dynamics and neural grounding of a dynamic field theory of multi-object tracking.

    Science.gov (United States)

    Spencer, J P; Barich, K; Goldberg, J; Perone, S

    2012-09-01

    The ability to dynamically track moving objects in the environment is crucial for efficient interaction with the local surrounds. Here, we examined this ability in the context of the multi-object tracking (MOT) task. Several theories have been proposed to explain how people track moving objects; however, only one of these previous theories is implemented in a real-time process model, and there has been no direct contact between theories of object tracking and the growing neural literature using ERPs and fMRI. Here, we present a neural process model of object tracking that builds from a Dynamic Field Theory of spatial cognition. Simulations reveal that our dynamic field model captures recent behavioral data examining the impact of speed and tracking duration on MOT performance. Moreover, we show that the same model with the same trajectories and parameters can shed light on recent ERP results probing how people distribute attentional resources to targets vs. distractors. We conclude by comparing this new theory of object tracking to other recent accounts, and discuss how the neural grounding of the theory might be effectively explored in future work.

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

    Directory of Open Access Journals (Sweden)

    Ebrahimi Touradj

    2004-01-01

    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 -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 cope with multiple

  4. 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

  5. Autonomous Motion Segmentation of Multiple Objects in Low Resolution Video Using Variational Level Sets

    Energy Technology Data Exchange (ETDEWEB)

    Moelich, M

    2003-11-18

    This report documents research that was done during a ten week internship in the Sapphire research group at the Lawrence Livermore National Laboratory during the Summer of 2003. The goal of the study was to develop an algorithm that is capable of isolating (segmenting) moving objects in low resolution video sequences. This capability is currently being developed by the Sapphire research group as the first stage in a longer term video data mining project. This report gives a chronological account of what ideas were tried in developing the algorithm and what was learned from each attempt. The final version of the algorithm, which is described in detail, gives good results and is fast.

  6. An Adaptive Object Tracking Using Kalman Filter and Probability Product Kernel

    Directory of Open Access Journals (Sweden)

    Hamd Ait Abdelali

    2016-01-01

    Full Text Available We present a new method for object tracking; we use an efficient local search scheme based on the Kalman filter and the probability product kernel (KFPPK to find the image region with a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed system.

  7. Tracking Student Achievement in Music Performance: Developing Student Learning Objectives for Growth Model Assessments

    Science.gov (United States)

    Wesolowski, Brian C.

    2015-01-01

    Student achievement growth data are increasingly used for assessing teacher effectiveness and tracking student achievement in the classroom. Guided by the student learning objective (SLO) framework, music teachers are now responsible for collecting, tracking, and reporting student growth data. Often, the reported data do not accurately reflect the…

  8. 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.

  9. 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......-room and three combined-room measurements, it was found that the traditional measure of speech, such as the speech transmission index, was not correlated with the subjective classifications. Thus, a correlation analysis was conducted as an attempt to find the hidden factors behind the subjective perceptions...

  10. Simulation of video sequences for an accurate evaluation of tracking algorithms on complex scenes

    Science.gov (United States)

    Dubreu, Christine; Manzanera, Antoine; Bohain, Eric

    2008-04-01

    As target tracking is arousing more and more interest, the necessity to reliably assess tracking algorithms in any conditions is becoming essential. The evaluation of such algorithms requires a database of sequences representative of the whole range of conditions in which the tracking system is likely to operate, together with its associated ground truth. However, building such a database with real sequences, and collecting the associated ground truth appears to be hardly possible and very time-consuming. Therefore, more and more often, synthetic sequences are generated by complex and heavy simulation platforms to evaluate the performance of tracking algorithms. Some methods have also been proposed using simple synthetic sequences generated without such complex simulation platforms. These sequences are generated from a finite number of discriminating parameters, and are statistically representative, as regards these parameters, of real sequences. They are very simple and not photorealistic, but can be reliably used for low-level tracking algorithms evaluation in any operating conditions. The aim of this paper is to assess the reliability of these non-photorealistic synthetic sequences for evaluation of tracking systems on complex-textured objects, and to show how the number of parameters can be increased to synthesize more elaborated scenes and deal with more complex dynamics, including occlusions and three-dimensional deformations.

  11. 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.

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

    CSIR Research Space (South Africa)

    Senekal, F

    2010-11-01

    Full Text Available typically have certain visual characteristics and where the environmental variables such as lighting and camera position can be controlled as well. In the work conducted here, a method is sought that can be applied in arbitrary situations.... In such situations, there may be considerable variation in the visual characteristics of the object that should be tracked and in the environmental conditions. In a general situation, the object that should be tracked might have variations in the colour...

  13. Detection and tracking of dynamic objects by using a multirobot system: application to critical infrastructures surveillance.

    Science.gov (United States)

    Rodríguez-Canosa, Gonzalo; del Cerro Giner, Jaime; Cruz, Antonio Barrientos

    2014-02-12

    The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed.

  14. Video inpainting with short-term windows: application to object removal and error concealment.

    Science.gov (United States)

    Ebdelli, Mounira; Le Meur, Olivier; Guillemot, Christine

    2015-10-01

    In this paper, we propose a new video inpainting method which applies to both static or free-moving camera videos. The method can be used for object removal, error concealment, and background reconstruction applications. To limit the computational time, a frame is inpainted by considering a small number of neighboring pictures which are grouped into a group of pictures (GoP). More specifically, to inpaint a frame, the method starts by aligning all the frames of the GoP. This is achieved by a region-based homography computation method which allows us to strengthen the spatial consistency of aligned frames. Then, from the stack of aligned frames, an energy function based on both spatial and temporal coherency terms is globally minimized. This energy function is efficient enough to provide high quality results even when the number of pictures in the GoP is rather small, e.g. 20 neighboring frames. This drastically reduces the algorithm complexity and makes the approach well suited for near real-time video editing applications as well as for loss concealment applications. Experiments with several challenging video sequences show that the proposed method provides visually pleasing results for object removal, error concealment, and background reconstruction context.

  15. 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.

  16. Mission planning optimization of video satellite for ground multi-object staring imaging

    Science.gov (United States)

    Cui, Kaikai; Xiang, Junhua; Zhang, Yulin

    2018-03-01

    This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

  17. Tracking the global jet streams through objective analysis

    Science.gov (United States)

    Gallego, D.; Peña-Ortiz, C.; Ribera, P.

    2009-12-01

    Although the tropospheric jet streams are probably the more important single dynamical systems in the troposphere, their study at climatic scale has been usually troubled by the difficulty of characterising their structure. During the last years, a deal of effort has been made in order to construct long-term scale objective climatologies of the jet stream or at least to understand the variability of the westerly flux in the upper troposphere. A main problem with studying the jets is the necessity of using highly derivated fields as the potential vorticity or even the analysis of chemical tracers. Despite their utility, these approaches are very problematic to construct an automatic searching algorithm because of the difficulty of defining criteria for these extremely noisy fields. Some attempts have been addressed trying to use only the wind field to find the jet. This direct approach avoids the use of derivate variables, but it must contain some stringent criteria to filter the large number of tropospheric wind maxima not related to the jet currents. This approach has offered interesting results for the relatively simple structure of the Southern Hemisphere tropospheric jets (Gallego et al. Clim. Dyn, 2005). However, the much more complicated structure of its northern counterpart has resisted the analysis with the same degree of detail by using the wind alone. In this work we present a new methodology able to characterise the position, strength and altitude of the jet stream at global scale on a daily basis. The method is based on the analysis of the 3-D wind field alone and it searches, at each longitude, relative wind maxima in the upper troposphere between the levels of 400 and 100 hPa. An ad-hoc defined density function (dependent on the season and the longitude) of the detection positions is used as criteria to filter spurious wind maxima not related to the jet. The algorithm has been applied to the NCEP/NCAR reanalysis and the results show that the basic

  18. Ground-based Tracking of Geosynchronous Space Objects with a GM-CPHD Filter

    Science.gov (United States)

    Jones, B.; Hatten, N.; Ravago, N.; Russell, R.

    2016-09-01

    This paper presents a multi-target tracker for space objects near geosynchronous orbit using the Gaussian Mixture Cardinalized Probability Hypothesis Density (CPHD) filter. Given limited sensor coverage and more than 1,000 objects near geosynchronous orbit, long times between measurement updates for a single object can yield propagated uncertainties sufficiently large to create ambiguities in observation-to-track association. Recent research considers various methods for tracking space objects via Bayesian multi-target filters, with the CPHD being one such example. The implementation of the CPHD filter presented in this paper includes models consistent with the space-object tracking problem to form a new space-object tracker. This tracker combines parallelization with efficient models and integrators to reduce the run time of Gaussian-component propagation. To allow for instantiating new objects, the proposed filter uses a variation of the probabilistic admissible region that adheres to assumptions in the derivation of the CPHD filter. Finally, to reduce computation time while mitigating the so-called "spooky action at a distance" phenomenon in the CPHD filter, we propose splitting the multi-target state into distinct, non-interacting populations based on the sensor's field of view. In a scenario with 700 near-geosynchronous objects observed via three ground stations, the tracker maintains custody of initially known objects and instantiates tracks for newly detected ones. The mean filter estimation after a 48 hour observation campaign is comparable to the measurement error statistics.

  19. An efficient Lagrangean relaxation-based object tracking algorithm in wireless sensor networks.

    Science.gov (United States)

    Lin, Frank Yeong-Sung; Lee, Cheng-Ta

    2010-01-01

    In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.

  20. Anisotropic versus isotropic distribution of attention in object tracking: Disentangling influences of overt and covert attention

    NARCIS (Netherlands)

    Frielink-Loing, A.F.; Koning, A.R.; Lier, R.J. van

    2015-01-01

    In recent studies, multiple-object tracking (MOT) tasks combined with probe detection tasks have been used to investigate the distribution of attention around moving objects (e.g., Atsma, Koning & van Lier, 2012). During these tasks, participants were allowed to move their eyes freely around the

  1. 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.

  2. Objective Video Quality Assessment of Direct Recording and Datavideo HDR-40 Recording System

    Directory of Open Access Journals (Sweden)

    Nofia Andreana

    2016-10-01

    Full Text Available Digital Video Recorder (DVR is a digital video recorder with hard drive storage media. When the capacity of the hard disk runs out. It will provide information to users and if there is no response, it will be overwritten automatically and the data will be lost. The main focus of this paper is to enable recording directly connected to a computer editor. The output of both systems (DVR and Direct Recording will be compared with an objective assessment using the Mean Square Error (MSE and Peak Signal to Noise Ratio (PSNR parameter. The results showed that the average value of MSE Direct Recording dB 797.8556108, 137.4346100 DVR MSE dB and the average value of PSNR Direct Recording and DVR PSNR dB 19.5942333 27.0914258 dB. This indicates that the DVR has a much better output quality than Direct Recording.

  3. Object class segmentation of RGB-D video using recurrent convolutional neural networks.

    Science.gov (United States)

    Pavel, Mircea Serban; Schulz, Hannes; Behnke, Sven

    2017-04-01

    Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations required for this task. They are, however, restricted by their small, fixed-sized filters, which limits their ability to learn long-range dependencies. Recurrent Neural Networks (RNN), on the other hand, do not suffer from this restriction. Their iterative interpretation allows them to model long-range dependencies by propagating activity. This property is especially useful when labeling video sequences, where both spatial and temporal long-range dependencies occur. In this work, a novel RNN architecture for object class segmentation is presented. We investigate several ways to train such a network. We evaluate our models on the challenging NYU Depth v2 dataset for object class segmentation and obtain competitive results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Aiming at the English language proficiency objectives of the National Core Curriculum for basic education through video games

    OpenAIRE

    Lukkarinen, M. (Markus)

    2013-01-01

    The objective of this paper is to study the Finnish National core curriculum for basic education and its English language proficiency objectives and analyse how video games can help ninth graders to aim at these objectives and improve their English language skills. Additionally, this thesis examines if the genre of a video game played has an impact on the English language learning experience, i.e., whether playing, for instance, a role-playing game benefits the student more in terms of Englis...

  5. 3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking

    Directory of Open Access Journals (Sweden)

    R. Chellappa

    2008-03-01

    Full Text Available We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The “shape filter” has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.

  6. 3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking

    Directory of Open Access Journals (Sweden)

    Chellappa R

    2008-01-01

    Full Text Available Abstract We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The "shape filter" has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.

  7. Comparing dogs and great apes in their ability to visually track object transpositions.

    Science.gov (United States)

    Rooijakkers, Eveline F; Kaminski, Juliane; Call, Josep

    2009-11-01

    Knowing that objects continue to exist after disappearing from sight and tracking invisible object displacements are two basic elements of spatial cognition. The current study compares dogs and apes in an invisible transposition task. Food was hidden under one of two cups in full view of the subject. After that both cups were displaced, systematically varying two main factors, whether cups were crossed during displacement and whether the cups were substituted by the other cup or instead cups were moved to new locations. While the apes were successful in all conditions, the dogs had a strong preference to approach the location where they last saw the reward, especially if this location remained filled. In addition, dogs seem to have special difficulties to track the reward when both containers crossed their path during displacement. These results confirm the substantial difference that exists between great apes and dogs with regard to mental representation abilities required to track the invisible displacements of objects.

  8. 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.

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

    Science.gov (United States)

    Kim, Taesik; Min, Hong; Jung, Jinman

    2017-02-23

    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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Optimized UAV object tracking framework based on Integrated Particle filter with ego-motion transformation matrix

    Directory of Open Access Journals (Sweden)

    Askar Wesam

    2017-01-01

    Full Text Available Vision based object tracking problem still a hot and important area of research specially when the tracking algorithms are performed by the aircraft unmanned vehicle (UAV. Tracking with the UAV requires special considerations due to the flight maneuvers, environmental conditions and aircraft moving camera. The ego motion calculations can compensate the effect of the moving background resulted from the moving camera. In this paper an optimized object tracking framework is introduced to tackle this problem based on particle filter. It integrates the calculated ego motion transformation matrix with the dynamic model of the particle filter during the prediction stage. Then apply the correction stage on the particle filter observation model which based on two kinds of features includes Haar-like Rectangles and edge orientation histogram (EOH features. The Gentle AdaBoost classifier is used to select the most informative features as a preliminary step. The experimental results achieved more than 94.6% rate of successful tracking during different scenarios of the VIVID database in real time tracking speed.

  15. A Real-Time Method to Detect and Track Moving Objects (DATMO from Unmanned Aerial Vehicles (UAVs Using a Single Camera

    Directory of Open Access Journals (Sweden)

    Bruce MacDonald

    2012-04-01

    Full Text Available We develop a real-time method to detect and track moving objects (DATMO from unmanned aerial vehicles (UAVs using a single camera. To address the challenging characteristics of these vehicles, such as continuous unrestricted pose variation and low-frequency vibrations, new approaches must be developed. The main concept proposed in this work is to create an artificial optical flow field by estimating the camera motion between two subsequent video frames. The core of the methodology consists of comparing this artificial flow with the real optical flow directly calculated from the video feed. The motion of the UAV between frames is estimated with available parallel tracking and mapping techniques that identify good static features in the images and follow them between frames. By comparing the two optical flows, a list of dynamic pixels is obtained and then grouped into dynamic objects. Tracking these dynamic objects through time and space provides a filtering procedure to eliminate spurious events and misdetections. The algorithms have been tested with a quadrotor platform using a commercial camera.

  16. Spatio-temporal patterns of brain activity distinguish strategies of multiple-object tracking.

    Science.gov (United States)

    Merkel, Christian; Stoppel, Christian M; Hillyard, Steven A; Heinze, Hans-Jochen; Hopf, Jens-Max; Schoenfeld, Mircea Ariel

    2014-01-01

    Human observers can readily track up to four independently moving items simultaneously, even in the presence of moving distractors. Here we combined EEG and magnetoencephalography recordings to investigate the neural processes underlying this remarkable capability. Participants were instructed to track four of eight independently moving items for 3 sec. When the movement ceased a probe stimulus consisting of four items with a higher luminance was presented. The location of the probe items could correspond fully, partly, or not at all with the tracked items. Participants reported whether the probe items fully matched the tracked items or not. About half of the participants showed slower RTs and higher error rates with increasing correspondence between tracked items and the probe. The other half, however, showed faster RTs and lower error rates when the probe fully matched the tracked items. This latter behavioral pattern was associated with enhanced probe-evoked neural activity that was localized to the lateral occipital cortex in the time range 170-210 msec. This enhanced response in the object-selective lateral occipital cortex suggested that these participants performed the tracking task by visualizing the overall shape configuration defined by the vertices of the tracked items, thereby producing a behavioral advantage on full-match trials. In a later time range (270-310 msec) probe-evoked neural activity increased monotonically as a function of decreasing target-probe correspondence in all participants. This later modulation, localized to superior parietal cortex, was proposed to reflect the degree of mismatch between the probe and the automatically formed visual STM representation of the tracked items.

  17. 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.

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

    Science.gov (United States)

    Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert

    2014-01-01

    In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance modeling and engagement simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar parameters are presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits are discussed.

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  4. 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.

  5. Online learning and fusion of orientation appearance models for robust rigid object tracking

    NARCIS (Netherlands)

    Marras, Ioannis; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    2014-01-01

    We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the

  6. Online learning and fusion of orientation appearance models for robust rigid object tracking

    NARCIS (Netherlands)

    Marras, Ioannis; Alabort, Joan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    We present a robust framework for learning and fusing different modalities for rigid object tracking. Our method fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depths cameras such as the Kinect. To combine these two completely different

  7. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    Directory of Open Access Journals (Sweden)

    Ming-Xin Jiang

    2013-01-01

    Full Text Available We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA. Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the more discriminative image and the less discriminative image, and the samples are projected. The object tracking results are obtained using Bayesian maximum a posteriori probability estimation. Finally, we employ a template update strategy which combines incremental subspace learning and the error matrix to reduce tracking drift. Compared with other popular methods, our method reduces the computational complexity and is very robust to abnormal changes. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm achieves more favorable performance than several state-of-the-art methods.

  8. 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...

  9. 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...

  10. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task

    OpenAIRE

    Wahn, Basil; FERRIS, DANIEL P.; Hairston, W. David; K?nig, Peter

    2016-01-01

    Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted...

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

    Science.gov (United States)

    2017-09-01

    timation and object tracking fields. We believe these capabilities are required to support online adaptive learning of objects in dynamic environments . This...dense 3d modeling of indoor environments . The International Journal of Robotics Research. 2012;31(5):647–663. Approved for public release...Institute of Technology; 2013. 43. Tipaldi GD, Meyer-Delius D, Burgard W. Lifelong localization in changing environments . The International Journal of

  12. 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.

  13. Cross-Modal Attention Effects in the Vestibular Cortex during Attentive Tracking of Moving Objects.

    Science.gov (United States)

    Frank, Sebastian M; Sun, Liwei; Forster, Lisa; Tse, Peter U; Greenlee, Mark W

    2016-12-14

    The midposterior fundus of the Sylvian fissure in the human brain is central to the cortical processing of vestibular cues. At least two vestibular areas are located at this site: the parietoinsular vestibular cortex (PIVC) and the posterior insular cortex (PIC). It is now well established that activity in sensory systems is subject to cross-modal attention effects. Attending to a stimulus in one sensory modality enhances activity in the corresponding cortical sensory system, but simultaneously suppresses activity in other sensory systems. Here, we wanted to probe whether such cross-modal attention effects also target the vestibular system. To this end, we used a visual multiple-object tracking task. By parametrically varying the number of tracked targets, we could measure the effect of attentional load on the PIVC and the PIC while holding the perceptual load constant. Participants performed the tracking task during functional magnetic resonance imaging. Results show that, compared with passive viewing of object motion, activity during object tracking was suppressed in the PIVC and enhanced in the PIC. Greater attentional load, induced by increasing the number of tracked targets, was associated with a corresponding increase in the suppression of activity in the PIVC. Activity in the anterior part of the PIC decreased with increasing load, whereas load effects were absent in the posterior PIC. Results of a control experiment show that attention-induced suppression in the PIVC is stronger than any suppression evoked by the visual stimulus per se. Overall, our results suggest that attention has a cross-modal modulatory effect on the vestibular cortex during visual object tracking. In this study we investigate cross-modal attention effects in the human vestibular cortex. We applied the visual multiple-object tracking task because it is known to evoke attentional load effects on neural activity in visual motion-processing and attention-processing areas. Here we

  14. 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.

  15. 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.

  16. Tracking of maneuvering non-ellipsoidal extended target with varying number of sub-objects

    Science.gov (United States)

    Hu, Qi; Ji, Hongbing; Zhang, Yongquan

    2018-01-01

    A target that generates multiple measurements at each time step is called the extended target and an ellipse can be used to approximate its extension. When the spatial distributions of measurements can reflect its true shape, in this situation the extended target is called a non-ellipsoidal extended target and its complicated extended state cannot be accurately approximated by single ellipse. In view of this, the non-ellipsoidal extended target tracking (NETT) filter was proposed, which uses multiple ellipses (called sub-objects) to approximate the extended state. However, the existing NETT filters are limited to the framework that the number of sub-objects remains still, which does not match the actual tracking situations. When the attitude of the target changes, the view from the sensor on the target may change, then the shape of the non-ellipsoidal extended target varies as well as the reasonable number of sub-objects needed for approximation. To solve this problem, we propose a varying number of sub-objects for non-ellipsoidal extended target tracking gamma Gaussian inverse Wishart (VN-NETT-GGIW) filter. The proposed filter estimates the kinematic, extension and measurement-rate states of each sub-object as well as the number of sub-objects. The simulation results show that the proposed filter can be used for the target changing attitude situation and is more close to the practice application.

  17. 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.

  18. 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.

  19. 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.

  20. "Can you see me now?" An objective metric for predicting intelligibility of compressed American Sign Language video

    Science.gov (United States)

    Ciaramello, Francis M.; Hemami, Sheila S.

    2007-02-01

    For members of the Deaf Community in the United States, current communication tools include TTY/TTD services, video relay services, and text-based communication. With the growth of cellular technology, mobile sign language conversations are becoming a possibility. Proper coding techniques must be employed to compress American Sign Language (ASL) video for low-rate transmission while maintaining the quality of the conversation. In order to evaluate these techniques, an appropriate quality metric is needed. This paper demonstrates that traditional video quality metrics, such as PSNR, fail to predict subjective intelligibility scores. By considering the unique structure of ASL video, an appropriate objective metric is developed. Face and hand segmentation is performed using skin-color detection techniques. The distortions in the face and hand regions are optimally weighted and pooled across all frames to create an objective intelligibility score for a distorted sequence. The objective intelligibility metric performs significantly better than PSNR in terms of correlation with subjective responses.

  1. Multiple object tracking in molecular bioimaging by Rao-Blackwellized marginal particle filtering.

    Science.gov (United States)

    Smal, I; Meijering, E; Draegestein, K; Galjart, N; Grigoriev, I; Akhmanova, A; van Royen, M E; Houtsmuller, A B; Niessen, W

    2008-12-01

    Time-lapse fluorescence microscopy imaging has rapidly evolved in the past decade and has opened new avenues for studying intracellular processes in vivo. Such studies generate vast amounts of noisy image data that cannot be analyzed efficiently and reliably by means of manual processing. Many popular tracking techniques exist but often fail to yield satisfactory results in the case of high object densities, high noise levels, and complex motion patterns. Probabilistic tracking algorithms, based on Bayesian estimation, have recently been shown to offer several improvements over classical approaches, by better integration of spatial and temporal information, and the possibility to more effectively incorporate prior knowledge about object dynamics and image formation. In this paper, we extend our previous work in this area and propose an improved, fully automated particle filtering algorithm for the tracking of many subresolution objects in fluorescence microscopy image sequences. It involves a new track management procedure and allows the use of multiple dynamics models. The accuracy and reliability of the algorithm are further improved by applying marginalization concepts. Experiments on synthetic as well as real image data from three different biological applications clearly demonstrate the superiority of the algorithm compared to previous particle filtering solutions.

  2. Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

    Directory of Open Access Journals (Sweden)

    Mohd Asyraf Zulkifley

    2012-11-01

    Full Text Available In video analytics, robust observation detection is very important as thecontent of the videos varies a lot, especially for tracking implementation. Contraryto the image processing field, the problems of blurring, moderate deformation, lowillumination surroundings, illumination change and homogenous texture are normallyencountered in video analytics. Patch-Based Observation Detection (PBOD is developed toimprove detection robustness to complex scenes by fusing both feature- and template-basedrecognition methods. While we believe that feature-based detectors are more distinctive,however, for finding the matching between the frames are best achieved by a collectionof points as in template-based detectors. Two methods of PBOD—the deterministic andprobabilistic approaches—have been tested to find the best mode of detection. Bothalgorithms start by building comparison vectors at each detected points of interest. Thevectors are matched to build candidate patches based on their respective coordination. Forthe deterministic method, patch matching is done in 2-level test where threshold-basedposition and size smoothing are applied to the patch with the highest correlation value. Forthe second approach, patch matching is done probabilistically by modelling the histogramsof the patches by Poisson distributions for both RGB and HSV colour models. Then,maximum likelihood is applied for position smoothing while a Bayesian approach is appliedfor size smoothing. The result showed that probabilistic PBOD outperforms the deterministicapproach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavyprocessing requirement.

  3. Young infants' visual fixation patterns in addition and subtraction tasks support an object tracking account.

    Science.gov (United States)

    Bremner, J Gavin; Slater, Alan M; Hayes, Rachel A; Mason, Uschi C; Murphy, Caroline; Spring, Jo; Draper, Lucinda; Gaskell, David; Johnson, Scott P

    2017-10-01

    Investigating infants' numerical ability is crucial to identifying the developmental origins of numeracy. Wynn (1992) claimed that 5-month-old infants understand addition and subtraction as indicated by longer looking at outcomes that violate numerical operations (i.e., 1+1=1 and 2-1=2). However, Wynn's claim was contentious, with others suggesting that her results might reflect a familiarity preference for the initial array or that they could be explained in terms of object tracking. To cast light on this controversy, Wynn's conditions were replicated with conventional looking time supplemented with eye-tracker data. In the incorrect outcome of 2 in a subtraction event (2-1=2), infants looked selectively at the incorrectly present object, a finding that is not predicted by an initial array preference account or a symbolic numerical account but that is consistent with a perceptual object tracking account. It appears that young infants can track at least one object over occlusion, and this may form the precursor of numerical ability. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  4. Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model

    Directory of Open Access Journals (Sweden)

    Changhong Fu

    2016-08-01

    Full Text Available In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algorithm initially finds feature correspondences in a way that an improved binary descriptor is developed for global feature matching and an iterative Lucas–Kanade optical flow algorithm is employed for local feature tracking. The second main module is the use of an efficient local geometric filter (LGF, which handles outlier feature correspondences based on a new forward-backward pairwise dissimilarity measure, thereby maintaining pairwise geometric consistency. In the proposed LGF module, a hierarchical agglomerative clustering, i.e., bottom-up aggregation, is applied using an effective single-link method. The third proposed module is a heuristic local outlier factor (to the best of our knowledge, it is utilized for the first time to deal with outlier features in a visual tracking application, which further maximizes the representation of the target object in which we formulate outlier feature detection as a binary classification problem with the output features of the LGF module. Extensive UAV flight experiments show that the proposed visual tracker achieves real-time frame rates of more than thirty-five frames per second on an i7 processor with 640 × 512 image resolution and outperforms the most popular state-of-the-art trackers favorably in terms of robustness, efficiency and accuracy.

  5. Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity

    Directory of Open Access Journals (Sweden)

    Hyuncheol Kim

    2014-01-01

    Full Text Available We address object tracking problem as a multitask feature learning process based on low-rank representation of features with joint sparsity. We first select features with low-rank representation within a number of initial frames to obtain subspace basis. Next, the features represented by the low-rank and sparse property are learned using a modified joint sparsity-based multitask feature learning framework. Both the features and sparse errors are then optimally updated using a novel incremental alternating direction method. The low-rank minimization problem for learning multitask features can be achieved by a few sequences of efficient closed form update process. Since the proposed method attempts to perform the feature learning problem in both multitask and low-rank manner, it can not only reduce the dimension but also improve the tracking performance without drift. Experimental results demonstrate that the proposed method outperforms existing state-of-the-art tracking methods for tracking objects in challenging image sequences.

  6. 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 ...

  7. Multiple object, three-dimensional motion tracking using the Xbox Kinect sensor

    Science.gov (United States)

    Rosi, T.; Onorato, P.; Oss, S.

    2017-11-01

    In this article we discuss the capability of the Xbox Kinect sensor to acquire three-dimensional motion data of multiple objects. Two experiments regarding fundamental features of Newtonian mechanics are performed to test the tracking abilities of our setup. Particular attention is paid to check and visualise the conservation of linear momentum, angular momentum and energy. In both experiments, two objects are tracked while falling in the gravitational field. The obtained data is visualised in a 3D virtual environment to help students understand the physics behind the performed experiments. The proposed experiments were analysed with a group of university students who are aspirant physics and mathematics teachers. Their comments are presented in this paper.

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

    OpenAIRE

    Muhammad Nanda Kurniawan; Didit Widiyanto

    2014-01-01

    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 (GLV...

  9. Implementation of Image Processing Algorithms and Glvq to Track an Object Using Ar.drone Camera

    OpenAIRE

    Kurniawan, Muhammad Nanda; Widiyanto, Didit

    2014-01-01

    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 fina...

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

    OpenAIRE

    Taesik Kim; Hong Min; Jinman Jung

    2017-01-01

    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 s...

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

    Science.gov (United States)

    Mandal, Saptarshi

    2016-01-01

    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. PMID:27725830

  12. 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.

  13. 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.

  14. Modeling optical pattern recognition algorithms for object tracking based on nonlinear equivalent models and subtraction of frames

    Science.gov (United States)

    Krasilenko, Vladimir G.; Nikolskyy, Aleksandr I.; Lazarev, Alexander A.

    2015-12-01

    We have proposed and discussed optical pattern recognition algorithms for object tracking based on nonlinear equivalent models and subtraction of frames. Experimental results of suggested algorithms in Mathcad and LabVIEW are shown. Application of equivalent functions and difference of frames gives good results for recognition and tracking moving objects.

  15. 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

  16. 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.

  17. The Use of Eye Tracking in Research on Video-Based Second Language (L2) Listening Assessment: A Comparison of Context Videos and Content Videos

    Science.gov (United States)

    Suvorov, Ruslan

    2015-01-01

    Investigating how visuals affect test takers' performance on video-based L2 listening tests has been the focus of many recent studies. While most existing research has been based on test scores and self-reported verbal data, few studies have examined test takers' viewing behavior (Ockey, 2007; Wagner, 2007, 2010a). To address this gap, in the…

  18. Comparison Of Processing Time Of Different Size Of Images And Video Resolutions For Object Detection Using Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Yogesh Yadav

    2017-01-01

    Full Text Available Object Detection with small computation cost and processing time is a necessity in diverse domains such as traffic analysis security cameras video surveillance etc .With current advances in technology and decrease in prices of image sensors and video cameras the resolution of captured images is more than 1MP and has higher frame rates. This implies a considerable data size that needs to be processed in a very short period of time when real-time operations and data processing is needed. Real time video processing with high performance can be achieved with GPU technology. The aim of this study is to evaluate the influence of different image and video resolutions on the processing time number of objects detections and accuracy of the detected object. MOG2 algorithm is used for processing video input data with GPU module. Fuzzy interference system is used to evaluate the accuracy of number of detected object and to show the difference between CPU and GPU computing methods.

  19. 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.

  20. 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.

  1. Object Tracking Using Local Multiple Features and a Posterior Probability Measure

    Directory of Open Access Journals (Sweden)

    Wenhua Guo

    2017-03-01

    Full Text Available Object tracking has remained a challenging problem in recent years. Most of the trackers can not work well, especially when dealing with problems such as similarly colored backgrounds, object occlusions, low illumination, or sudden illumination changes in real scenes. A centroid iteration algorithm using multiple features and a posterior probability criterion is presented to solve these problems. The model representation of the object and the similarity measure are two key factors that greatly influence the performance of the tracker. Firstly, this paper propose using a local texture feature which is a generalization of the local binary pattern (LBP descriptor, which we call the double center-symmetric local binary pattern (DCS-LBP. This feature shows great discrimination between similar regions and high robustness to noise. By analyzing DCS-LBP patterns, a simplified DCS-LBP is used to improve the object texture model called the SDCS-LBP. The SDCS-LBP is able to describe the primitive structural information of the local image such as edges and corners. Then, the SDCS-LBP and the color are combined to generate the multiple features as the target model. Secondly, a posterior probability measure is introduced to reduce the rate of matching mistakes. Three strategies of target model update are employed. Experimental results show that our proposed algorithm is effective in improving tracking performance in complicated real scenarios compared with some state-of-the-art methods.

  2. A Position Controller Model on Color-Based Object Tracking using Fuzzy Logic

    Science.gov (United States)

    Cahyo Wibowo, Budi; Much Ibnu Subroto, Imam; Arifin, Bustanul

    2017-04-01

    Robotics vision is applying technology on the camera to view the environmental conditions as well as the function of the human eye. Colour object tracking system is one application of robotics vision technology with the ability to follow the object being detected. Several methods have been used to generate a good response position control, but most are still using conventional control approach. Fuzzy logic which includes several step of which is to determine the value of crisp input must be fuzzification. The output of fuzzification is forwarded to the process of inference in which there are some fuzzy logic rules. The inference output forwarded to the process of defuzzification to be transformed into outputs (crisp output) to drive the servo motors on the X-axis and Y-axis. Fuzzy logic control is applied to the color-based object tracking system, the system is successful to follow a moving object with average speed of 7.35 cm/s in environments with 117 lux light intensity.

  3. Binocular visual tracking and grasping of a moving object with a 3D trajectory predictor

    Directory of Open Access Journals (Sweden)

    J. Fuentes‐Pacheco

    2009-12-01

    Full Text Available This paper presents a binocular eye‐to‐hand visual servoing system that is able to track and grasp a moving object in real time.Linear predictors are employed to estimate the object trajectory in three dimensions and are capable of predicting futurepositions even if the object is temporarily occluded. For its development we have used a CRS T475 manipulator robot with sixdegrees of freedom and two fixed cameras in a stereo pair configuration. The system has a client‐server architecture and iscomposed of two main parts: the vision system and the control system. The vision system uses color detection to extract theobject from the background and a tracking technique based on search windows and object moments. The control system usesthe RobWork library to generate the movement instructions and to send them to a C550 controller by means of the serial port.Experimental results are presented to verify the validity and the efficacy of the proposed visual servoing system.

  4. 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.

  5. Swarming visual sensor network for real-time multiple object tracking

    Science.gov (United States)

    Baranov, Yuri P.; Yarishev, Sergey N.; Medvedev, Roman V.

    2016-04-01

    Position control of multiple objects is one of the most actual problems in various technology areas. For example, in construction area this problem is represented as multi-point deformation control of bearing constructions in order to prevent collapse, in mining - deformation control of lining constructions, in rescue operations - potential victims and sources of ignition location, in transport - traffic control and traffic violations detection, in robotics -traffic control for organized group of robots and many other problems in different areas. Usage of stationary devices for solving these problems is inappropriately due to complex and variable geometry of control areas. In these cases self-organized systems of moving visual sensors is the best solution. This paper presents a concept of scalable visual sensor network with swarm architecture for multiple object pose estimation and real-time tracking. In this article recent developments of distributed measuring systems were reviewed with consequent investigation of advantages and disadvantages of existing systems, whereupon theoretical principles of design of swarming visual sensor network (SVSN) were declared. To measure object coordinates in the world coordinate system using TV-camera intrinsic (focal length, pixel size, principal point position, distortion) and extrinsic (rotation matrix, translation vector) calibration parameters were needed to be determined. Robust camera calibration was a too resource-intensive task for using moving camera. In this situation position of the camera is usually estimated using a visual mark with known parameters. All measurements were performed in markcentered coordinate systems. In this article a general adaptive algorithm of coordinate conversion of devices with various intrinsic parameters was developed. Various network topologies were reviewed. Minimum error in objet tracking was realized by finding the shortest path between object of tracking and bearing sensor, which set

  6. A Continuous Object Boundary Detection and Tracking Scheme for Failure-Prone Sensor Networks.

    Science.gov (United States)

    Imran, Sajida; Ko, Young-Bae

    2017-02-13

    In wireless sensor networks, detection and tracking of continuous natured objects is more challenging owing to their unique characteristics such as uneven expansion and contraction. A continuous object is usually spread over a large area, and, therefore, a substantial number of sensor nodes are needed to detect the object. Nodes communicate with each other as well as with the sink to exchange control messages and report their detection status. The sink performs computations on the received data to estimate the object boundary. For accurate boundary estimation, nodes at the phenomenon boundary need to be carefully selected. Failure of one or multiple boundary nodes (BNs) can significantly affect the object detection and boundary estimation accuracy at the sink. We develop an efficient failure-prone object detection approach that not only detects and recovers from BN failures but also reduces the number and size of transmissions without compromising the boundary estimation accuracy. The proposed approach utilizes the spatial and temporal features of sensor nodes to detect object BNs. A Voronoi diagram-based network clustering, and failure detection and recovery scheme is used to increase boundary estimation accuracy. Simulation results show the significance of our approach in terms of energy efficiency, communication overhead, and boundary accuracy.

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

    Science.gov (United States)

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

    2016-06-01

    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.

  8. 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.

  9. Detecting single-target changes in multiple object tracking: The case of peripheral vision.

    Science.gov (United States)

    Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2016-05-01

    In the present study, we investigated whether peripheral vision can be used to monitor multiple moving objects and to detect single-target changes. For this purpose, in Experiment 1, a modified multiple object tracking (MOT) setup with a large projection screen and a constant-position centroid phase had to be checked first. Classical findings regarding the use of a virtual centroid to track multiple objects and the dependency of tracking accuracy on target speed could be successfully replicated. Thereafter, the main experimental variations regarding the manipulation of to-be-detected target changes could be introduced in Experiment 2. In addition to a button press used for the detection task, gaze behavior was assessed using an integrated eyetracking system. The analysis of saccadic reaction times in relation to the motor response showed that peripheral vision is naturally used to detect motion and form changes in MOT, because saccades to the target often occurred after target-change offset. Furthermore, for changes of comparable task difficulties, motion changes are detected better by peripheral vision than are form changes. These findings indicate that the capabilities of the visual system (e.g., visual acuity) affect change detection rates and that covert-attention processes may be affected by vision-related aspects such as spatial uncertainty. Moreover, we argue that a centroid-MOT strategy might reduce saccade-related costs and that eyetracking seems to be generally valuable to test the predictions derived from theories of MOT. Finally, we propose implications for testing covert attention in applied settings.

  10. 2011 Tohoku tsunami runup hydrographs, ship tracks, upriver and overland flow velocities based on video, LiDAR and AIS measurements

    Science.gov (United States)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Takeda, S.; Mohammed, F.; Skanavis, V.; Synolakis, C.; Takahashi, T.

    2014-12-01

    The 2004 Indian Ocean tsunami marked the advent of survivor videos mainly from tourist areas in Thailand and basin-wide locations. Near-field video recordings on Sumatra's north tip at Banda Aceh were limited to inland areas a few kilometres off the beach (Fritz et al., 2006). The March 11, 2011, magnitude Mw 9.0 earthquake off the Tohoku coast of Japan caused catastrophic damage and loss of life resulting in the costliest natural disaster in recorded history. The mid-afternoon tsunami arrival combined with survivors equipped with cameras on top of vertical evacuation buildings provided numerous inundation recordings with unprecedented spatial and temporal resolution. High quality tsunami video recording sites at Yoriisohama, Kesennuma, Kamaishi and Miyako along Japan's Sanriku coast were surveyed, eyewitnesses interviewed and precise topographic data recorded using terrestrial laser scanning (TLS). The original video recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). The analysis of the tsunami videos follows an adapted four step procedure (Fritz et al., 2012). Measured overland flow velocities during tsunami runup exceed 13 m/s at Yoriisohama. The runup hydrograph at Yoriisohama highlights the under sampling at the Onagawa Nuclear Power Plant (NPP) pressure gauge, which skips the shorter period second crest. Combined tsunami and runup hydrographs are derived from the videos based on water surface elevations at surface piercing objects and along slopes identified in the acquired topographic TLS data. Several hydrographs reveal a draw down to minus 10 m after a first wave crest exposing harbor bottoms at Yoriisohama and Kamaishi. In some cases ship moorings resist the main tsunami crest only to be broken by the extreme draw down. A multi-hour ship track for the Asia Symphony with the vessels complete tsunami drifting motion in Kamaishi Bay is recovered from the universal ship borne AIS (Automatic Identification System). Multiple

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

    African Journals Online (AJOL)

    Computer-generated and video images are superimposed. The man-machine interface functions deal mainly with on line building of graphic aids to improve perception, updating the geometric database of the robotic site, and video control of the robot. The superimposition of the real and virtual worlds is carried out through ...

  12. Arousal-Augmented Priming Effects: Rock Music Videos and Sex Object Schemas.

    Science.gov (United States)

    Hansen, Christine Hall; Krygowski, Walter

    1994-01-01

    Investigates effects of undergraduate students' physiological arousal induced by physical activity on schematic priming effects from music videos. Finds that in high-arousal conditions priming effects were more extreme and more closely resembled music video content than in low-arousal conditions. (SR)

  13. 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.

  14. Eye Tracking Research and Technology: Towards Objective Measurement of Data Quality.

    Science.gov (United States)

    Reingold, Eyal M

    2014-03-01

    Two methods for objectively measuring eye tracking data quality are explored. The first method works by tricking the eye tracker to detect an abrupt change in the gaze position of an artificial eye that in actuality does not move. Such a device, referred to as an artificial saccade generator, is shown to be extremely useful for measuring the temporal accuracy and precision of eye tracking systems and for validating the latency to display change in gaze contingent display paradigms. The second method involves an artificial pupil that is mounted on a computer controlled moving platform. This device is designed to be able to provide the eye tracker with motion sequences that closely resemble biological eye movements. The main advantage of using artificial motion for testing eye tracking data quality is the fact that the spatiotemporal signal is fully specified in a manner independent of the eye tracker that is being evaluated and that nearly identical motion sequence can be reproduced multiple times with great precision. The results of the present study demonstrate that the equipment described has the potential to become an important tool in the comprehensive evaluation of data quality.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ingram, S; Rao, A; Wendt, R; Castillo, R; Court, L [UT MD Anderson Cancer Center, Houston, TX (United States); UT Graduate School of Biomedical Sciences, Houston, TX (United States); Yang, J; Beadle, B [UT MD Anderson Cancer Center, Houston, TX (United States)

    2014-06-01

    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.

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

    Science.gov (United States)

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

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

  17. 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.

  18. 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.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Lvwen Huang

    2017-08-01

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

  1. 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.

  2. An AEGIS-CPHD Filter to Maintain Custody of GEO Space Objects with Limited Tracking Data

    Science.gov (United States)

    Gehly, S.; Jones, B.; Axelrad, P.

    2014-09-01

    The problem of space situational awareness (SSA) involves characterizing space objects subject to nonlinear dynamics and sparse measurements. Space objects in GEO are primarily tracked using optical sensors, which have limited fields of view, imperfect ability to detect objects, and are limited to taking measurements at night, all of which result in large gaps between measurements. In addition, the nonlinear dynamics result in state uncertainty representations which are generally non-Gaussian. When estimating the states of a catalog of space objects, these issues must be resolved within the framework of a multitarget filter. To address the issue of non-Gaussian uncertainty, the Adaptive Entropy-based Gaussian-mixture Information Synthesis (AEGIS) filter can be used. AEGIS is an implementation of the Unscented Kalman Filter (UKF) using an adaptive number of Gaussian mixture components to approximate the non-Gaussian state probability density function (pdf). Mixture components are split when nonlinearity is detected during propagation, typically during long data gaps, and can be merged or removed following measurement updates to reduce computational effort. Previous research has examined the use of AEGIS in multitarget filters based in Finite Set Statistics (FISST), including the Probability Hypothesis Density (PHD) filter and Cardinalized PHD (CPHD) filter. This paper uses the CPHD filter because in other applications it has been demonstrated to be more effective at estimating and maintaining the cardinality, or number of objects present, when objects are often leaving the sensor field of view (FOV). An important consideration in implementing the filter is the computation of the probability of detection. Existing formulations use a state-dependent probability of detection to assign a value based on whether the mean estimated state is in the sensor FOV. This paper employs a more realistic development by mapping the full state pdf into measurement space and

  3. Robust 3D Object Tracking from Monocular Images using Stable Parts.

    Science.gov (United States)

    Crivellaro, Alberto; Rad, Mahdi; Verdie, Yannick; Yi, Kwang Moo; Fua, Pascal; Lepetit, Vincent

    2017-05-26

    We present an algorithm for estimating the pose of a rigid object in real-time under challenging conditions. Our method effectively handles poorly textured objects in cluttered, changing environments, even when their appearance is corrupted by large occlusions, and it relies on grayscale images to handle metallic environments on which depth cameras would fail. As a result, our method is suitable for practical Augmented Reality applications including industrial environments. At the core of our approach is a novel representation for the 3D pose of object parts: We predict the 3D pose of each part in the form of the 2D projections of a few control points. The advantages of this representation is three-fold: We can predict the 3D pose of the object even when only one part is visible; when several parts are visible, we can easily combine them to compute a better pose of the object; the 3D pose we obtain is usually very accurate, even when only few parts are visible. We show how to use this representation in a robust 3D tracking framework. In addition to extensive comparisons with the state-of-the-art, we demonstrate our method on a practical Augmented Reality application for maintenance assistance in the ATLAS particle detector at CERN.

  4. 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.

  5. "Untitled": Black Sounds and Music Video as an Object of Study

    National Research Council Canada - National Science Library

    Kevin D Ball

    2016-01-01

    ...) employ a Third Cinema model to create a dialogue among spectators in an enclosed space, whereas music video can meet spectators on their own terms-in Facebook timelines, GIF art spinoffs, tweets and iPhone apps...

  6. Efficient Visual Tracking with Spatial Constraints

    NARCIS (Netherlands)

    Zhang, L.

    2015-01-01

    Object tracking is an important component in computer vision, which is the field that aims to replicate the abilities of human vision by automatically analyzing and understanding the content of digital images or videos. Tracking has applications in a wide range of domains. For instance, tracking

  7. Persistent Target Tracking Using Likelihood Fusion in Wide-Area and Full Motion Video Sequences

    Science.gov (United States)

    2012-07-01

    problems associated with a moving platform including gimbal -based stabilization errors, relative motion where sensor and target are both moving, seams in...Image Processing, 2000, pp. 561–564. [46] A. Hafiane, K. Palaniappan, and G. Seetharaman, “ UAV -video registra- tion using block-based features,” in IEEE

  8. Enhancing Vocabulary Learning through Captioned Video: An Eye-Tracking Study

    Science.gov (United States)

    Perez, Maribel Montero; Peters, Elke; Desmet, Piet

    2015-01-01

    This study investigates the effect of two attention-enhancing techniques on L2 students' learning and processing of novel French words (i.e., target words) through video with L2 subtitles or captions. A combination of eye-movement data and vocabulary tests was gathered to study the effects of Type of Captioning (full or keyword captioning) and…

  9. Surveying drainage culvert use by carnivores: sampling design and cost-benefit analyzes of track-pads vs. video-surveillance methods.

    Science.gov (United States)

    Mateus, Ana Rita A; Grilo, Clara; Santos-Reis, Margarida

    2011-10-01

    Environmental assessment studies often evaluate the effectiveness of drainage culverts as habitat linkages for species, however, the efficiency of the sampling designs and the survey methods are not known. Our main goal was to estimate the most cost-effective monitoring method for sampling carnivore culvert using track-pads and video-surveillance. We estimated the most efficient (lower costs and high detection success) interval between visits (days) when using track-pads and also determined the advantages of using each method. In 2006, we selected two highways in southern Portugal and sampled 15 culverts over two 10-day sampling periods (spring and summer). Using the track-pad method, 90% of the animal tracks were detected using a 2-day interval between visits. We recorded a higher number of crossings for most species using video-surveillance (n = 129) when compared with the track-pad technique (n = 102); however, the detection ability using the video-surveillance method varied with type of structure and species. More crossings were detected in circular culverts (1 m and 1.5 m diameter) than in box culverts (2 m to 4 m width), likely because video cameras had a reduced vision coverage area. On the other hand, carnivore species with small feet such as the common genet Genetta genetta were detected less often using the track-pad surveying method. The cost-benefit analyzes shows that the track-pad technique is the most appropriate technique, but video-surveillance allows year-round surveys as well as the behavior response analyzes of species using crossing structures.

  10. Pursuit-evasion games with information uncertainties for elusive orbital maneuver and space object tracking

    Science.gov (United States)

    Shen, Dan; Jia, Bin; Chen, Genshe; Blasch, Erik; Pham, Khanh

    2015-05-01

    This paper develops and evaluates a pursuit-evasion (PE) game approach for elusive orbital maneuver and space object tracking. Unlike the PE games in the literature, where the assumption is that either both players have perfect knowledge of the opponents' positions or use primitive sensing models, the proposed PE approach solves the realistic space situation awareness (SSA) problem with imperfect information, where the evaders will exploit the pursuers' sensing and tracking models to confuse their opponents by maneuvering their orbits to increase the uncertainties, which the pursuers perform orbital maneuvers to minimize. In the game setup, each game player P (pursuer) and E (evader) has its own motion equations with a small continuous low-thrust. The magnitude of the low thrust is fixed and the direction can be controlled by the associated game player. The entropic uncertainty is used to generate the cost functions of game players. The Nash or mixed Nash equilibrium is composed of the directional controls of low-thrusts. Numerical simulations are emulated to demonstrate the performance. Simplified perturbations models (SGP4/SDP4) are exploited to calculate the ground truth of the satellite states (position and speed).

  11. 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.

  12. Towards a ground truth of AADT on using video data and tracking software?

    DEFF Research Database (Denmark)

    Øhlenschlæger, Rasmus; Lahrmann, Harry Spaabæk; B. Moeslund, Thomas

    to measure traffic volumes are increasingly used, but there is limited documentation on the reliability of these. This paper compares manual registrations, treated as ground truth, the hardware independent software RUBA and an on-the-shelf product. While the RUBA software, in general, had a reasonable......There is an increase in traffic volumes and, as such, a requirement for maximisation of the road capacity. It is crucial that there is awareness of the traffic volumes in order to make the right choices regarding road development. Video registrations and related software to video analysis...... precision on the direction parallel to the camera direction (8% and 3% deviations, respectively); it was less precise regarding transversal-driving vehicles (23% deviation). The on-the-shelf hardware had a significantly higher deviation regarding the two parallel directions, (35% and 67% deviations...

  13. 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].

  14. 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.

  15. COCOA: tracking in aerial imagery

    Science.gov (United States)

    Ali, Saad; Shah, Mubarak

    2006-05-01

    Unmanned Aerial Vehicles (UAVs) are becoming a core intelligence asset for reconnaissance, surveillance and target tracking in urban and battlefield settings. In order to achieve the goal of automated tracking of objects in UAV videos we have developed a system called COCOA. It processes the video stream through number of stages. At first stage platform motion compensation is performed. Moving object detection is performed to detect the regions of interest from which object contours are extracted by performing a level set based segmentation. Finally blob based tracking is performed for each detected object. Global tracks are generated which are used for higher level processing. COCOA is customizable to different sensor resolutions and is capable of tracking targets as small as 100 pixels. It works seamlessly for both visible and thermal imaging modes. The system is implemented in Matlab and works in a batch mode.

  16. What is a Visual Object? Evidence from the Reduced Interference of Grouping in Multiple Object Tracking for Children with Autism Spectrum Disorders

    Directory of Open Access Journals (Sweden)

    Lee de-Wit

    2012-05-01

    Full Text Available Objects offer a critical unit with which we can organise our experience of the world. However, whilst their influence on perception and cognition may be fundamental, understanding how objects are constructed from sensory input remains a key challenge for vision research and psychology in general. A potential window into the means by which objects are constructed in the visual system is offered by the influence that they have on the allocation of attention. In Multiple Object Tracking (MOT, for example, attention is automatically allocated to whole objects, even when this interferes with the tracking of the parts of these objects. In this study we demonstrate that this default tendency to track whole objects is reduced in children with Autisim Spectrum Disorders (ASD. This result both validates the use of MOT as a window into how objects are generated in the visual system and highlights how the reduced bias towards more global processing in ASD could influence further stages of cognition by altering the way in which attention selects information for further processing.

  17. 3D modeling of architectural objects from video data obtained with the fixed focal length lens geometry

    Science.gov (United States)

    Deliś, Paulina; Kędzierski, Michał; Fryśkowska, Anna; Wilińska, Michalina

    2013-12-01

    The article describes the process of creating 3D models of architectural objects on the basis of video images, which had been acquired by a Sony NEX-VG10E fixed focal length video camera. It was assumed, that based on video and Terrestrial Laser Scanning data it is possible to develop 3D models of architectural objects. The acquisition of video data was preceded by the calibration of video camera. The process of creating 3D models from video data involves the following steps: video frames selection for the orientation process, orientation of video frames using points with known coordinates from Terrestrial Laser Scanning (TLS), generating a TIN model using automatic matching methods. The above objects have been measured with an impulse laser scanner, Leica ScanStation 2. Created 3D models of architectural objects were compared with 3D models of the same objects for which the self-calibration bundle adjustment process was performed. In this order a PhotoModeler Software was used. In order to assess the accuracy of the developed 3D models of architectural objects, points with known coordinates from Terrestrial Laser Scanning were used. To assess the accuracy a shortest distance method was used. Analysis of the accuracy showed that 3D models generated from video images differ by about 0.06 ÷ 0.13 m compared to TLS data. Artykuł zawiera opis procesu opracowania modeli 3D obiektów architektonicznych na podstawie obrazów wideo pozyskanych kamerą wideo Sony NEX-VG10E ze stałoogniskowym obiektywem. Przyjęto założenie, że na podstawie danych wideo i danych z naziemnego skaningu laserowego (NSL) możliwe jest opracowanie modeli 3D obiektów architektonicznych. Pozyskanie danych wideo zostało poprzedzone kalibracją kamery wideo. Model matematyczny kamery był oparty na rzucie perspektywicznym. Proces opracowania modeli 3D na podstawie danych wideo składał się z następujących etapów: wybór klatek wideo do procesu orientacji, orientacja klatek wideo na

  18. 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

  19. An Agile Framework for Real-Time Visual Tracking in Videos

    Science.gov (United States)

    2012-09-05

    IMPLEMENTATION OF OUR APPROACH We implemented tracking in C++ using the OpenCV library for real-time computer vision. The ensemble in our case consisted...of the algorithm,” OpenCV Document, Intel, Microprocessor Research Labs, 2000. [6] Kaiki Huang and Tieniu Tan, “Vs-star: A Visual Interpretation

  20. 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...

  1. Ultra-scale vehicle tracking in low spatial-resolution and low frame-rate overhead video

    Energy Technology Data Exchange (ETDEWEB)

    Carrano, C J

    2009-05-20

    Overhead persistent surveillance systems are becoming more capable at acquiring wide-field image sequences for long time-spans. The need to exploit this data is becoming ever greater. The ability to track a single vehicle of interest or to track all the observable vehicles, which may number in the thousands, over large, cluttered regions while they persist in the imagery either in real-time or quickly on-demand is very desirable. With this ability we can begin to answer a number of interesting questions such as, what are normal traffic patterns in a particular region or where did that truck come from? There are many challenges associated with processing this type of data, some of which we will address in the paper. Wide-field image sequences are very large with many thousands of pixels on a side and are characterized by lower resolutions (e.g. worse than 0.5 meters/pixel) and lower frame rates (e.g. a few Hz or less). The objects in the scenery can vary in size, density, and contrast with respect to the background. At the same time the background scenery provides a number of clutter sources both man-made and natural. We describe our current implementation of an ultrascale capable multiple-vehicle tracking algorithm for overhead persistent surveillance imagery as well as discuss the tracking and timing performance of the currently implemented algorithm which is aimed at utilizing grayscale electrooptical image sequences alone for the track segment generation.

  2. Objects2action: Classifying and localizing actions without any video example

    NARCIS (Netherlands)

    Jain, M.; van Gemert, J.C.; Mensink, T.; Snoek, C.G.M.

    2015-01-01

    The goal of this paper is to recognize actions in video without the need for examples. Different from traditional zero-shot approaches we do not demand the design and specification of attribute classifiers and class-to-attribute mappings to allow for transfer from seen classes to unseen classes. Our

  3. The Davideon Project: Capitalizing the Possibilities of Streaming Video as Flexible Learning Objects for the Humanities

    Science.gov (United States)

    Rosendaal, Andre; Oomen, Johan

    2005-01-01

    Streaming video is a potentially revolutionary tool in humanities courses. The Davideon project, a large-scale effort conducted by the University of Groningen in conjunction with the University of Amsterdam, Windesheim University, and the Netherlands Institute for Sound and Vision, focused on integrating audiovisual materials into pedagogically…

  4. Effect of age and stereopsis on a multiple-object tracking task.

    Directory of Open Access Journals (Sweden)

    Marjolaine Plourde

    Full Text Available 3D vision develops during childhood and tends to diminish after 65 years of age. It is still relatively unknown how stereopsis is used in more complex/ecological contexts such as when walking about in crowds where objects are in motion and occlusions occur. One task that shares characteristics with the requirements for processing dynamic crowds is the multiple object-tracking task (MOT. In the present study we evaluated the impact of stereopsis on a MOT task as a function of age. A total of 60 observers consisting of three groups of 20 subjects (7-12 years old, 18-40 years old and 65 years and older completed the task in both conditions (with and without stereoscopic effects. The adult group obtained the better scores, followed by the children and the older adult group. The performance difference between the stereoscopic and non-stereoscopic conditions was significant and similar for the adults and the children but was non significant for the older observers. These results show that stereopsis helps children and adults accomplish a MOT task, but has no impact on older adults' performances. The present results have implications as to how populations differ in their efficiency of using stereoscopic cues for disambiguating complex dynamic scenes.

  5. Effect of age and stereopsis on a multiple-object tracking task

    Science.gov (United States)

    2017-01-01

    3D vision develops during childhood and tends to diminish after 65 years of age. It is still relatively unknown how stereopsis is used in more complex/ecological contexts such as when walking about in crowds where objects are in motion and occlusions occur. One task that shares characteristics with the requirements for processing dynamic crowds is the multiple object-tracking task (MOT). In the present study we evaluated the impact of stereopsis on a MOT task as a function of age. A total of 60 observers consisting of three groups of 20 subjects (7–12 years old, 18–40 years old and 65 years and older) completed the task in both conditions (with and without stereoscopic effects). The adult group obtained the better scores, followed by the children and the older adult group. The performance difference between the stereoscopic and non-stereoscopic conditions was significant and similar for the adults and the children but was non significant for the older observers. These results show that stereopsis helps children and adults accomplish a MOT task, but has no impact on older adults’ performances. The present results have implications as to how populations differ in their efficiency of using stereoscopic cues for disambiguating complex dynamic scenes. PMID:29244875

  6. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task.

    Directory of Open Access Journals (Sweden)

    Basil Wahn

    Full Text Available Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.

  7. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task.

    Science.gov (United States)

    Wahn, Basil; Ferris, Daniel P; Hairston, W David; König, Peter

    2016-01-01

    Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.

  8. 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...... was tracked for 24 hr. Initially, Cypermethrin induced an almost instant paralysis of the hind legs and a lack of coordination in movement seen in the jagged and circular track appearance. This phase culminated in total quiescence, lasting approximately 12 hr in males and 24-48 hr in females. Following...

  9. 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.

  10. Tracking initially unresolved thrusting objects in 3D using a single stationary optical sensor

    Science.gov (United States)

    Lu, Qin; Bar-Shalom, Yaakov; Willett, Peter; Granström, Karl; Ben-Dov, R.; Milgrom, B.

    2017-05-01

    This paper considers the problem of estimating the 3D states of a salvo of thrusting/ballistic endo-atmospheric objects using 2D Cartesian measurements from the focal plane array (FPA) of a single fixed optical sensor. Since the initial separations in the FPA are smaller than the resolution of the sensor, this results in merged measurements in the FPA, compounding the usual false-alarm and missed-detection uncertainty. We present a two-step methodology. First, we assume a Wiener process acceleration (WPA) model for the motion of the images of the projectiles in the optical sensor's FPA. We model the merged measurements with increased variance, and thence employ a multi-Bernoulli (MB) filter using the 2D measurements in the FPA. Second, using the set of associated measurements for each confirmed MB track, we formulate a parameter estimation problem, whose maximum likelihood estimate can be obtained via numerical search and can be used for impact point prediction. Simulation results illustrate the performance of the proposed method.

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

    OpenAIRE

    Carbone, Marco Benoit; Ruffino, Paolo

    2012-01-01

    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’...

  12. 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.

  13. Functional connectivity indicates differential roles for the intraparietal sulcus and the superior parietal lobule in multiple object tracking.

    Science.gov (United States)

    Alnæs, Dag; Sneve, Markus H; Richard, Geneviève; Skåtun, Kristina C; Kaufmann, Tobias; Nordvik, Jan Egil; Andreassen, Ole A; Endestad, Tor; Laeng, Bruno; Westlye, Lars T

    2015-12-01

    Attentive tracking requires sustained object-based attention, rather than passive vigilance or rapid attentional shifts to brief events. Several theories of tracking suggest a mechanism of indexing objects that allows for attentional resources to be directed toward the moving targets. Imaging studies have shown that cortical areas belonging to the dorsal frontoparietal attention network increase BOLD-signal during multiple object tracking (MOT). Among these areas, some studies have assigned IPS a particular role in object indexing, but the neuroimaging evidence has been sparse. In the present study, we tested participants on a continuous version of the MOT task in order to investigate how cortical areas engage in functional networks during attentional tracking. Specifically, we analyzed the data using eigenvector centrality mapping (ECM) analysis, which provides estimates of individual voxels' connectedness with hub-like parts of the functional network. The results obtained using permutation based voxel-wise statistics support the proposed role for the IPS in object indexing as this region displayed increased centrality during tracking as well as increased functional connectivity with both prefrontal and visual perceptual cortices. In contrast, the opposite pattern was observed for the SPL, with decreasing centrality, as well as reduced functional connectivity with the visual and frontal cortices, in agreement with a hypothesized role for SPL in attentional shifts. These findings provide novel evidence that IPS and SPL serve different functional roles during MOT, while at the same time being highly engaged during tracking as measured by BOLD-signal changes. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Electromagnetic tracking of handheld high-resolution endomicroscopy probes to assist with real-time video mosaicking

    Science.gov (United States)

    Vyas, Khushi; Hughes, Michael; Yang, Guang-Zhong

    2015-03-01

    Optical fiber bundle based endomicroscopy is a low-cost optical biopsy technique for in vivo cellular level imaging. A limitation of such an imaging system, however, is its small field-of-view (FOV), typically less than 1 mm2. With such a small FOV it is difficult to associate individual image frames with the larger scale anatomical structure. Video-sequence mosaicking algorithms have been proposed as a solution for increasing the image FOV while maintaining cellular-level resolution by stitching together the endomicroscopy images. Although extensive research has focused on image processing and mosaicking algorithms, there has been limited work on localization of the probe to assist with building high quality mosaics over large areas of tissue. In this paper, we propose the use of electromagnetic (EM) navigation to assist with large-area mosaicking of hand-held high-resolution endomicroscopy probes. A six degree-of-freedom EM sensor is used to track in real-time the position and orientation of the tip of the imaging probe during free-hand scanning. We present a proof-of-principle system for EM-video data co-calibration and registration and then describe a two-step image registration algorithm that assists mosaic reconstruction. Preliminary experimental investigations are carried out on phantoms and ex vivo porcine tissue for free-hand scanning. The results demonstrate that the proposed methodology significantly improves the quality and accuracy of reconstructed mosaics compared to reconstructions based only on conventional pair-wise image registration. In principle, this approach can be applied to other optical biopsy techniques such as confocal endomicroscopy and endocytoscopy.

  15. Developing situation awareness amongst nursing and paramedicine students utilizing eye tracking technology and video debriefing techniques: a proof of concept paper.

    Science.gov (United States)

    O'Meara, Peter; Munro, Graham; Williams, Brett; Cooper, Simon; Bogossian, Fiona; Ross, Linda; Sparkes, Louise; Browning, Mark; McClounan, Mariah

    2015-04-01

    The aims of this quasi-experimental before-and-after study were to first determine whether the use of eye tracking technology combined with video debriefing techniques has the potential to improve the quality of feedback and enhance situation awareness (SA) in simulated settings and second to determine students' satisfaction towards simulated learning. Nursing and paramedicine students from three universities participated in three 8-minute simulation scenarios of acutely deteriorating patients. Eye tracking glasses video recorded the scenarios and tracked right eye movement. On completion, participants were questioned using the Situation Awareness Global Assessment Technique, completed the Satisfaction with Simulation Experience Scale (SSES), and provided textual feedback and received video-based verbal feedback. Participants lacked awareness of presenting medical conditions and patient environments and had poor recall of patient vital signs. Significant improvements in SA scores were demonstrated between the first and third scenarios (P = 0.04). Participants reported greater insight into their performance and were satisfied with simulated learning. Use of visual field review techniques appears to enhance the use of realistic simulated practice as a means of addressing significant performance deficits. Eye tracking and point of view recording techniques are feasible and with applicable debriefing techniques could enhance clinical and situated performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Basic Surgical Skill Retention: Can Patriot Motion Tracking System Provide an Objective Measurement for it?

    Science.gov (United States)

    Shaharan, Shazrinizam; Nugent, Emmeline; Ryan, Donncha M; Traynor, Oscar; Neary, Paul; Buckley, Declan

    2016-01-01

    Knot tying is a fundamental skill that surgical trainees have to learn early on in their training. The aim of this study was to establish the predictive and concurrent validity of the Patriot as an assessment tool and determine the skill retention in first-year surgical trainees after 5 months of training. First-year surgical trainees were recruited in their first month of the training program. Experts were invited to set the proficiency level. The subjects performed hand knot tying on a bench model. The skill was assessed at baseline in the first month of training and at 5 months. The assessment tools were the Patriot electromagnetic tracking system and Objective Structured Assessment of Technical Skills (OSATS). The trainees' scores were compared to the proficiency score. The data were analyzed using paired t-test and Pearson correlation analysis. A total of 14 first-year trainees participated in this study. The time taken to complete the task and the path length (PL) were significantly shorter (p = 0.007 and p = 0.0085, respectively) at 5 months. OSATS scoring showed a significant improvement (p = 0.0004). There was a significant correlation between PL and OSATS at baseline (r = -0.873) and at Month 5 (r = -0.774). In all, 50% of trainees reached the proficiency PL at baseline and at Month 5. Among them, 3 trainees improved their PL to reach proficiency and the other 3 trainees failed to reach proficiency. The parameters from the Patriot motion tracker demonstrated a significant correlation with the classical observational assessment tool and were capable of highlighting the skill retention in surgical trainees. Therefore, the automated scoring system has a significant role in the surgical training curriculum as an adjunct to the available assessment tool. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  17. 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.

  18. The Video Mesh: A Data Structure for Image-based Three-dimensional Video Editing

    OpenAIRE

    Chen, Jiawen; Paris, Sylvain; Wang, Jue; Matusik, Wojciech; Cohen, Michael; Durand, Fredo

    2011-01-01

    This paper introduces the video mesh, a data structure for representing video as 2.5D “paper cutouts.” The video mesh allows interactive editing of moving objects and modeling of depth, which enables 3D effects and post-exposure camera control. The video mesh sparsely encodes optical flow as well as depth, and handles occlusion using local layering and alpha mattes. Motion is described by a sparse set of points tracked over time. Each point also stores a depth value. The video mesh is a trian...

  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. Evaluating sub-lethal effects of orchard-applied pyrethroids using video-tracking software to quantify honey bee behaviors.

    Science.gov (United States)

    Ingram, Erin M; Augustin, Julie; Ellis, Marion D; Siegfried, Blair D

    2015-09-01

    Managed honey bee, Apis mellifera L., colonies are contracted to pollinate fruit and nut orchards improving crop quality and yield. Colonies placed in orchards are potentially exposed to pyrethroid insecticides used for broad-spectrum pest control. Pyrethroids have been reported to pose minimal risk to bees due to their low application rates in the field and putative repellent properties. This repellency is believed to alter foraging behavior with the benefit of preventing bees from encountering a lethal dose in the field. However, sub-lethal exposure to pyrethroids may adversely impact bee behavior potentially resulting in social dysfunction or disruption of foraging. This study quantified behaviors associated with sub-lethal exposure to orchard-applied pyrethroids including, lambda-cyhalothrin, esfenvalerate, and permethrin, using video tracking software, Ethovision XT (Noldus Information Technologies). Bee locomotion, social interaction, and time spent near a food source were measured over a 24-h period. Bees treated with a pyrethroid traveled 30-71% less than control bees. Social interaction time decreased by 43% for bees treated with a high sub-lethal dose of esfenvalerate. Bees exposed to a high sub-lethal dose of permethrin spent 67% less time in social interaction and spent more than 5 times as long in the food zone compared to control bees. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Performance Evaluation of Random Set Based Pedestrian Tracking Algorithms

    OpenAIRE

    Ristic, Branko; Sherrah, Jamie; García-Fernández, Ángel F.

    2012-01-01

    The paper evaluates the error performance of three random finite set based multi-object trackers in the context of pedestrian video tracking. The evaluation is carried out using a publicly available video dataset of 4500 frames (town centre street) for which the ground truth is available. The input to all pedestrian tracking algorithms is an identical set of head and body detections, obtained using the Histogram of Oriented Gradients (HOG) detector. The tracking error is measured using the re...

  2. 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.

  3. 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.

  4. Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds.

    Science.gov (United States)

    Lapierre, Mark D; Cropper, Simon J; Howe, Piers D L

    2017-01-01

    To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.

  5. 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

  6. 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...... from a subjective quality study, where the test subjects have been choosing the preferred path from the lowest quality to the best quality, at each step making a choice in favor of higher frame rate or lower distortion. A comparison with other relevant objective metrics shows that the proposed metric...

  7. 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.

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

    OpenAIRE

    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 from a subjective quality study, where the test subjects have been choosing the preferred path from the lowest quality to the best quality, at each step making a choice in favor of higher frame rate o...

  9. 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.

  10. 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.

  11. 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

  12. 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.

  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

    2017-01-01

    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…

  14. 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.

  15. Space Object Detection and Tracking Within a Finite Set Statistics Framework

    Science.gov (United States)

    2017-04-13

    MM-YYYY)      21-04-2017 2. REPORT TYPE Final 3. DATES COVERED (From - To) 01 Feb 2015 to 31 Jan 2017 4. TITLE AND SUBTITLE Space Object Detection...description of the data sets used is provided. 3.1 CAMRa Radar Data sets Two types of data sets were obtained from CAMRa: raw and post-processed. For...astronomical images. It detects objects such as stars, satellites, galaxies from FITS images. Then it computes photometry1 from the detected objects and

  16. 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.

  17. 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 executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

  18. 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

  19. Object-adapted optical trapping and shape-tracking of energy-switching helical bacteria

    Science.gov (United States)

    Koch, Matthias; Rohrbach, Alexander

    2012-10-01

    Optical tweezers are a flexible manipulation tool used to grab micro-objects at a specific point, but a controlled manipulation of objects with more complex or changing shapes is hardly possible. Here, we demonstrate, by time-sharing optical forces, that it is possible to adapt the shape of the trapping potential to the shape of an elongated helical bacterium. In contrast to most other trapped objects, this structure can continuously change its helical shape (and therefore its mechanical energy), making trapping it much more difficult than trapping tiny non-living objects. The shape deformations of the only 200-nm-thin bacterium (Spiroplasma) are measured space-resolved at 800 Hz by exploiting local phase differences in coherently scattered trapping light. By localizing each slope of the bacterium we generate high-contrast, super-resolution movies in three dimensions, without any object staining. This approach will help in investigating the nanomechanics of single wall-less bacteria while reacting to external stimuli on a broad temporal bandwidth.

  20. Tracking Neptune’s Migration History through High-perihelion Resonant Trans-Neptunian Objects

    Science.gov (United States)

    Kaib, Nathan A.; Sheppard, Scott S.

    2016-11-01

    Recently, Sheppard et al. presented the discovery of seven new trans-Neptunian objects with moderate eccentricities, perihelia beyond 40 au, and semimajor axes beyond 50 au. Like the few previously known objects on similar orbits, these objects’ semimajor axes are just beyond the Kuiper Belt edge and clustered around Neptunian mean motion resonances (MMRs). These objects likely obtained their observed orbits while trapped within MMRs, when the Kozai-Lidov mechanism raised their perihelia and weakened Neptune’s dynamical influence. Using numerical simulations that model the production of this population, we find that high-perihelion objects near Neptunian MMRs can constrain the nature and timescale of Neptune’s past orbital migration. In particular, the population near the 3:1 MMR (near 62 au) is especially useful due to its large population and short dynamical evolution timescale. If Neptune finishes migrating within ˜100 Myr or less, we predict that over 90% of high-perihelion objects near the 3:1 MMR will have semimajor axes within 1 au of each other, very near the modern resonance’s center. On the other hand, if Neptune’s migration takes ˜300 Myr, we expect ˜50% of this population to reside in dynamically fossilized orbits over ˜1 au closer to the Sun than the modern resonance. We highlight 2015 KH162 as a likely member of this fossilized 3:1 population. Under any plausible migration scenario, nearly all high-perihelion objects in resonances beyond the 4:1 MMR (near 76 au) reach their orbits well after Neptune stops migrating and compose a recently generated, dynamically active population.

  1. 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.

  2. The social distraction of facial paralysis: Objective measurement of social attention using eye-tracking.

    Science.gov (United States)

    Ishii, Lisa; Dey, Jacob; Boahene, Kofi D O; Byrne, Patrick J; Ishii, Masaru

    2016-02-01

    To measure the attentional distraction to the facial paralysis deformity using eye-tracking, and to distinguish between attention paid to the upper and lower facial divisions in patients with complete paralysis. We hypothesized that features affected by the paralysis deformity would distract the casual observer, leading to an altered pattern of facial attention as compared to normals. Randomized controlled experiment. Sixty casual observers viewed images of paralyzed faces (House-Brackmann [HB] IV-VI) and normal faces smiling and in repose. The SMI iView X RED (SensoMotoric, Inc., Boston, MA) eye-gaze tracker recorded eye movements of observers gazing on the faces. Fixation durations for predefined areas of interest were analyzed using three separate multivariate analyses. Casual observers gazing on both paralyzed and normal faces directed the majority of their attention to the central triangle (CT) region. Significant differences occurred in the distribution of attention among individual features in the CT and to individual sides of the face. Observers directed more attention to the mouth of paralyzed faces, smiling (analysis of variance [ANOVA] > F 0.0001) and in repose (ANOVA > F 0.0000). Attention was asymmetrically distributed between the two halves of paralyzed faces (paralyzed smiling minus normal smiling P > |z| 0.000). Casual observers directed attention in a measurably different way when gazing on paralyzed faces as compared to normal faces, a finding exacerbated with smiling. These findings help explain society's perceptions of attractiveness and affect display that differ for paralyzed and normal faces and can be used to direct our reconstructive efforts. N/A. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  3. 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.

  4. Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

    Science.gov (United States)

    2014-09-01

    Vehicles Richard Rast and Waid Schlaegel AFRL, Directed Energy Vincent Schmidt AFRL, Human Effectiveness Directorate Stephen Gregory The Boeing...the data set collected with the RH 17-inch telescope, the night of 2014/10/02 UT, we evaluate the performance of RANSAC-MT by testing it using...calibration techniques. Moving object signatures of various intensities and angular velocities are tested . Figure 6 shows the results from one of the

  5. Do personally-tailored videos in a web-based physical activity intervention lead to higher attention and recall? – An eye-tracking study.

    Directory of Open Access Journals (Sweden)

    Stephanie eAlley

    2014-02-01

    Full Text Available Over half of the Australian population does not meet physical activity guidelines and has an increased risk of chronic disease. Web-based physical activity interventions have the potential to reach large numbers of the population at low cost, however issues have been identified with usage and participant retention. Personalised (computer-tailored physical activity advice delivered through video has the potential to address low engagement, however it is unclear whether it is more effective in engaging participants when compared to text-delivered personalised advice. This study compared the attention and recall outcomes of tailored physical activity advice in video- versus text-format. Participants (n=41 were randomly assigned to receive either video- or text-tailored feedback with identical content. Outcome measures included attention to the feedback, measured through advanced eye-tracking technology (Tobii 120, and recall of the advice, measured through a post intervention interview. Between group ANOVA’s, Mann-Whitney U tests and Chi square analyses were applied. Participants in the video-group displayed greater attention to the physical activity feedback in terms of gaze-duration on the feedback (7.7 min vs. 3.6 min, p< 001, total fixation-duration on the feedback (6.0 min vs. 3.3 min, p< 001, and focusing on feedback (6.8 vs. 3.5 min, p< 001. Despite both groups having the same ability to navigate through the feedback, the video-group completed a significantly (p< .001 higher percentage of feedback sections (95% compared to the text-group (66%. The main messages were recalled in both groups, but many details were forgotten. No significant between group differences were found for message recall. These results suggest that video-tailored feedback leads to greater attention compared to text-tailored feedback. More research is needed to determine how message recall can be improved, and whether video-tailored advice can lead to greater health

  6. 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...

  7. Healthy older observers show equivalent perceptual-cognitive training benefits to young adults for multiple object tracking

    Directory of Open Access Journals (Sweden)

    Isabelle eLegault

    2013-06-01

    Full Text Available The capacity to process complex dynamic scenes is of critical importance in real life. For instance, travelling through a crowd while avoiding collisions and maintaining orientation and good motor control requires fluent and continuous perceptual-cognitive processing. It is well documented that effects of healthy aging can influence perceptual-cognitive processes (Faubert, 2002 and that the efficiency of such processes can improve with training even for older adults (Richards et al., 2006. Here we assess the capacity of older observers to learn complex dynamic visual scenes by using the 3D-multiple object tracking speed threshold protocol (Faubert & Sidebottom, 2012. Results show that this capacity is significantly affected by healthy aging but that perceptual-cognitive training can significantly reduce age-related effects in older individuals, who show an identical learning function to younger healthy adults. Data support the notion that plasticity in healthy older persons is maintained for processing complex dynamic scenes.

  8. BLOCK-BASED TRACKING WITH TWO WAY SEARCH

    Directory of Open Access Journals (Sweden)

    J. Shajeena

    2014-11-01

    Full Text Available Tracking is essentially a matching problem. This paper proposes a tracking scheme for video objects on compressed domain. This method mainly focuses on locating the object region and evolving the detection of movement, which improves tracking precision. Motion Vectors (MVs are used for block matching. At each frame, the decision of whether a particular block belongs to the object being tracked is made with the help of histogram matching. During the process of matching and evolving the direction of movement, similarities of target region are compared to ensure that there is no overlapping and tracking performed in a right way. Experiments using the proposed tracker on videos demonstrate that the method can reliably locate the object of interest effectively.

  9. 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)

  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

    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.

  12. Privacy-protecting video surveillance

    Science.gov (United States)

    Wickramasuriya, Jehan; Alhazzazi, Mohanned; Datt, Mahesh; Mehrotra, Sharad; Venkatasubramanian, Nalini

    2005-02-01

    Forms of surveillance are very quickly becoming an integral part of crime control policy, crisis management, social control theory and community consciousness. In turn, it has been used as a simple and effective solution to many of these problems. However, privacy-related concerns have been expressed over the development and deployment of this technology. Used properly, video cameras help expose wrongdoing but typically come at the cost of privacy to those not involved in any maleficent activity. This work describes the design and implementation of a real-time, privacy-protecting video surveillance infrastructure that fuses additional sensor information (e.g. Radio-frequency Identification) with video streams and an access control framework in order to make decisions about how and when to display the individuals under surveillance. This video surveillance system is a particular instance of a more general paradigm of privacy-protecting data collection. In this paper we describe in detail the video processing techniques used in order to achieve real-time tracking of users in pervasive spaces while utilizing the additional sensor data provided by various instrumented sensors. In particular, we discuss background modeling techniques, object tracking and implementation techniques that pertain to the overall development of this system.

  13. A New Distance Measure Based on Generalized Image Normalized Cross-Correlation for Robust Video Tracking and Image Recognition.

    Science.gov (United States)

    Nakhmani, Arie; Tannenbaum, Allen

    2013-02-01

    We propose two novel distance measures, normalized between 0 and 1, and based on normalized cross-correlation for image matching. These distance measures explicitly utilize the fact that for natural images there is a high correlation between spatially close pixels. Image matching is used in various computer vision tasks, and the requirements to the distance measure are application dependent. Image recognition applications require more shift and rotation robust measures. In contrast, registration and tracking applications require better localization and noise tolerance. In this paper, we explore different advantages of our distance measures, and compare them to other popular measures, including Normalized Cross-Correlation (NCC) and Image Euclidean Distance (IMED). We show which of the proposed measures is more appropriate for tracking, and which is appropriate for image recognition tasks.

  14. Multi-hypothesis tracking of the tongue surface in ultrasound video recordings of normal and impaired speech.

    Science.gov (United States)

    Laporte, Catherine; Ménard, Lucie

    2018-02-01

    Characterizing tongue shape and motion, as they appear in real-time ultrasound (US) images, is of interest to the study of healthy and impaired speech production. Quantitative anlaysis of tongue shape and motion requires that the tongue surface be extracted in each frame of US speech recordings. While the literature proposes several automated methods for this purpose, these either require large or very well matched training sets, or lack robustness in the presence of rapid tongue motion. This paper presents a new robust method for tongue tracking in US images that combines simple tongue shape and motion models derived from a small training data set with a highly flexible active contour (snake) representation and maintains multiple possible hypotheses as to the correct tongue contour via a particle filtering algorithm. The method was tested on a database of large free speech recordings from healthy and impaired speakers and its accuracy was measured against the manual segmentations obtained for every image in the database. The proposed method achieved mean sum of distances errors of 1.69 ± 1.10 mm, and its accuracy was not highly sensitive to training set composition. Furthermore, the proposed method showed improved accuracy, both in terms of mean sum of distances error and in terms of linguistically meaningful shape indices, compared to the three publicly available tongue tracking software packages Edgetrak, TongueTrack and Autotrace. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Top-Down and Bottom-Up Cues Based Moving Object Detection for Varied Background Video Sequences

    Directory of Open Access Journals (Sweden)

    Chirag I. Patel

    2014-01-01

    there is no need for background formulation and updates as it is background independent. Many bottom-up approaches and one combination of bottom-up and top-down approaches are proposed in the present paper. The proposed approaches seem more efficient due to inessential requirement of learning background model and due to being independent of previous video frames. Results indicate that the proposed approach works even against slight movements in the background and in various outdoor conditions.

  16. How Do Teachers Appropriate Learning Objects Through Critical Experiences? A Study of a Pilot In-School Collaborative Video Learning Lab

    Directory of Open Access Journals (Sweden)

    Valérie Lussi Borer

    2014-06-01

    Full Text Available This two-year longitudinal study examined the collective and individual effects of a collaborative video learning lab (CVLL in a French lower-secondary high-poverty school. The CVLL was designed to: i determine the learning objects shared by the in-service teachers based on their actual teaching activities and ii encourage them to participate in a collaborative inquiry on their filmed activity regarding the selected shared learning object, with the goal of supporting them as they appropriate more efficient teaching practices..The participants were novice in-service teachers (n=2 and experienced teacher-facilitators (n=2. Data consisted of cross-analysis of video recordings (n=37 from i classroom teaching activity (n=11, ii CVLL sessions (n=6, and iii teachers’ observations and comments on both (n=20. The results revealed that novice and experienced teachers lived critical experiences in the CVLL regarding the shared learning object and show how they transformed their activity as teachers, mentors or facilitators. Questo studio longitudinale di due anni esamina gli effetti collettivi e individuali di un laboratorio di apprendimento collaborativo con video (CVLL in una scuola secondaria inferiore francese con alto grado di povertà. Il CVLL è stato progettato per: i determinare i learning object condivisi dai docenti in servizio in base alle loro reali attività di insegnamento e ii incoraggiarli a partecipare ad un’indagine collaborativa sulle attività videoregistrate concernenti il learning object condiviso selezionato, con l’obiettivo di sostenerli nel fare proprie pratiche di insegnamento più efficaci. I partecipanti sono insegnanti novizi in servizio (n=2 e insegnanti facilitatori esperti (n=2. I dati raccolti consistono in un’analisi incrociata delle registrazioni video (n=37, da i attività didattica in aula (n=11, ii sessioni CVLL (n=6, iii osservazioni e commenti degli insegnanti su entrambi (n=20. I risultati mostrano che gli

  17. A feasibility study on the implementation of satellite-to-satellite tracking around a small near-Earth object

    Science.gov (United States)

    Church, Christopher J.

    Near-earth objects (NEOs) are asteroids and comets that have a perihelion distance of less than 1.3 astronomical units (AU). There are currently more than 10,000 known NEOs. The majority of these objects are less than 1 km in diameter. Despite the number of NEOs, little is known about most of them. Characterizing these objects is a crucial component in developing a thorough understanding of solar system evolution, human exploration, exploitation of asteroid resources, and threat mitigation. Of particular interest is characterizing the internal structure of NEOs. While ground-based methods exist for characterizing the internal structure of NEOs, the information that can be gleaned from such studies is limited and often accompanied by large uncertainty. An alternative is to use in situ studies to examine an NEO's shape and gravity field, which can be used to assess its internal structure. This thesis investigates the use of satellite-to-satellite tracking (SST) to map the gravity field of a small NEO on the order of 500 m or less. An analysis of the mission requirements of two previously flown SST missions, GRACE and GRAIL, is conducted. Additionally, a simulation is developed to investigate the dynamics of SST in the vicinity of a small NEO. This simulation is then used to simulate range and range-rate data in the strongly perturbed environment of the small NEO. These data are used in conjunction with the analysis of the GRACE and GRAIL missions to establish a range of orbital parameters that can be used to execute a SST mission around a small NEO. Preliminary mission requirements for data collection and orbital correction maneuvers are also established. Additionally, the data are used to determine whether or not proven technology can be used to resolve the expected range and range-rate measurements. It is determined that the orbit semi-major axis for each spacecraft should be approximately 100% to 200% of the NEO's mean diameter and the two spacecraft should be in

  18. Gemini South Multi-Object Spectrograph (GMOS-S) detector Video boards upgrade: improved performance for the Hamamatsu CCDs.

    Science.gov (United States)

    Gimeno, German; Boucher, Luc; Chiboucas, Kristin; Hibon, Pascale; Lazo, Manuel; Murowinski, Richard; Rippa, Matthew; Rogers, Rolando; Rojas, Roberto; Roth, Katherine; White, John

    2016-01-01

    GMOS-S was upgraded with new Hamamatsu CCDs on June 2014, featuring an improved red sensitivity with respect to the previous detectors and significantly less fringing. Early after the commissioning, an issue was identified when observing in any of the binned readout modes, namely that saturated pixels produced a decrease of counts with respect to the bias level in neighboring pixels. This effect, also known as 'banding', spanned the entire width of the amplifier, and while it did not destroy information, it rendered data reduction very cumbersome. Making matters worse, due to the saturation of a bad column on amplifier number 5 (on CCD2, near the middle of the focal plane), it ended up affecting the entire amplifier for almost all exposures longer than a minute. A team of Gemini instrument scientists and engineers investigated the issue and identified the root cause of the problem as originated in the ARC controller video boards. After significant lab testing, it was verified that a newly available revision of the video boards would solve the problem, though modification of the software was required in order to be compatible with them. This work was performed during the last semester of 2014 and the first semester of 2015. The new video boards were installed and commissioned during August 2015. As of September 1st, the new boards are fully installed and integrated, and the 'banding' effect has been completely eliminated. A short period of time was devoted to the recharacterization of the detector system and the new values for the gains, read noise and full well capacity have been derived. As an added benefit, the full well was increased by ~ 10 percent with respect to the previous value. The GMOS-S new detectors are now operating normally in the Gemini observing queue, and performing at full capacity.

  19. Customizing Multiprocessor Implementation of an Automated Video Surveillance System

    Directory of Open Access Journals (Sweden)

    Morteza Biglari-Abhari

    2006-09-01

    Full Text Available This paper reports on the development of an automated embedded video surveillance system using two customized embedded RISC processors. The application is partitioned into object tracking and video stream encoding subsystems. The real-time object tracker is able to detect and track moving objects by video images of scenes taken by stationary cameras. It is based on the block-matching algorithm. The video stream encoding involves the optimization of an international telecommunications union (ITU-T H.263 baseline video encoder for quarter common intermediate format (QCIF and common intermediate format (CIF resolution images. The two subsystems running on two processor cores were integrated and a simple protocol was added to realize the automated video surveillance system. The experimental results show that the system is capable of detecting, tracking, and encoding QCIF and CIF resolution images with object movements in them in real-time. With low cycle-count, low-transistor count, and low-power consumption requirements, the system is ideal for deployment in remote locations.

  20. Enhancing digital video analysis of bar kinematics in weightlifting: a case study

    OpenAIRE

    Dæhlin, Torstein Eriksen; Krosshaug, Tron; Chiu, Loren Z.F.

    2017-01-01

    Weightlifting technique can be objectively assessed from two-dimensional video recordings. Despite its importance, participants’ bar trajectories in research involving the snatch or clean exercises are often not reported, potentially due to the time required to digitize video. The purpose of this investigation was to evaluate the use of an LED-based marker, digital video and open source software to automatically track the bar end during weightlifting exercises. A former national-level weightl...

  1. Tracking Students' Eye-Movements When Reading Learning Objects on Mobile Phones: A Discourse Analysis of Luganda Language Teacher-Trainees' Reflective Observations

    Science.gov (United States)

    Kabugo, David; Muyinda, Paul B.; Masagazi, Fred. M.; Mugagga, Anthony M.; Mulumba, Mathias B.

    2016-01-01

    Although eye-tracking technologies such as Tobii-T120/TX and Eye-Tribe are steadily becoming ubiquitous, and while their appropriation in education can aid teachers to collect robust information on how students move their eyes when reading and engaging with different learning objects, many teachers of Luganda language are yet to gain experiences…

  2. More Evidence for Three Types of Cognitive Style: Validating the Object?Spatial Imagery and Verbal Questionnaire Using Eye Tracking when Learning with Texts and Pictures

    OpenAIRE

    H?ffler, Tim N.; Ko??Januchta, Marta; Leutner, Detlev

    2016-01-01

    Summary There is some indication that people differ regarding their visual and verbal cognitive style. The Object?Spatial Imagery and Verbal Questionnaire (OSIVQ) assumes a three?dimensional cognitive style model, which distinguishes between object imagery, spatial imagery and verbal dimensions. Using eye tracking as a means to observe actual gaze behaviours when learning with text?picture combinations, the current study aims to validate this three?dimensional assumption by linking the OSIVQ ...

  3. Moving Shadow Detection in Video Using Cepstrum Regular Paper

    OpenAIRE

    Cogun, Fuat; Cetin, Ahmet Enis

    2013-01-01

    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 ...

  4. A constellation of SmallSats with synthetic tracking cameras to search for 90% of potentially hazardous near-Earth objects

    Science.gov (United States)

    Shao, Michael; Turyshev, Slava G.; Spangelo, Sara; Werne, Thomas; Zhai, Chengxing

    2017-07-01

    We present a new space mission concept that is capable of finding, detecting, and tracking 90% of near-Earth objects (NEO) with H magnitude of H ≤ 22 (i.e., 140 m in size) that are potentially hazardous to the Earth. The new mission concept relies on two emerging technologies: the technique of synthetic tracking and the new generation of small and capable interplanetary spacecraft. Synthetic tracking is a technique that de-streaks asteroid images by taking multiple fast exposures. With synthetic tracking, an 800 s observation with a 10 cm telescope in space can detect a moving object with apparent magnitude of 20.5 without losing sensitivity from streaking. We refer to NEOs with a minimum orbit intersection distance of constellation of six SmallSats (comparable in size to 9U CubeSats) equipped with 10 cm synthetic tracking cameras and evenly-distributed in 1.0 au heliocentric orbit could detect 90% of EGs with H ≤ 22 mag in 3.8 yr of observing time. A more advanced constellation of nine 20 cm telescopes could detect 90% of H = 24.2 mag (i.e., 50 m in size) EGs in less than 5 yr.

  5. 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.

  6. Autonomous search and tracking of objects using model predictive control of unmanned aerial vehicle and gimbal: Hardware-in-the-loop simulation of payload and avionics

    OpenAIRE

    Skjong, Espen; Nundal, Stian Aa.; Leira, Frederik Stendahl; JOHANSEN, Tor Arne

    2015-01-01

    This paper describes the design of model predictive control (MPC) for an unmanned aerial vehicle (UAV) used to track objects of interest identified by a real-time camera vision (CV) module in a search and track (SAT) autonomous system. A fully functional UAV payload is introduced, which includes an infra-red (IR) camera installed in a two-axis gimbal system. Hardware-in-loop (HIL) simulations are performed to test the MPC's performance in the SAT system, where the gimbal attitude and the UAV'...

  7. Feasibility of a cost-effective, video analysis software-based mobility protocol for objective spine kinematics and gait metrics: a proof of concept study.

    Science.gov (United States)

    Paul, Justin C; Petrizzo, Anthony; Rizzo, John-Ross; Bianco, Kristina; Maier, Stephen; Errico, Thomas J; Lafage, Virginie

    2015-03-01

    The purpose of this study was to investigate the potential of a high-throughput, easily implemented, cost-effective, video analysis software-based mobility protocol to quantify spine kinematics. This prospective cohort study of clinical biomechanics implemented 2-dimensional (2D) image processing at a tertiary-care academic institution. Ten healthy, able-bodied volunteers were recruited for 2D videography of gait and functional motion. The reliability of a 2D video analysis software program for gait and range of motion metrics was evaluated over 2 independent experimental sessions, assessing for inter-trial, inter-session, and inter-rater reliability. Healthy volunteers were evaluated for simple forward and side bending, rotation, treadmill stride length, and more complex seated-to-standing tasks. Based on established intraclass correlation coefficients, results indicated that reliability was considered good to excellent for simple forward and side bending, rotation, stride length, and more complex sit-to-standing tasks. In conclusion, a cost-effective, 2D, video analysis software-based mobility protocol represents a feasible and clinically useful approach for objective spine kinematics and gait metrics. As the complication rate of operative management in the setting of spinal deformity is weighed against functional performance and quality of life measures, an objective analysis tool in combination with an appropriate protocol will aid in clinical assessments and lead to an increased evidence base for management options and decision algorithms. Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring

    Science.gov (United States)

    2015-10-02

    tiled regions over the object of interest. In 2011, [34] modeled objects as a collection of patches with a separate layer of global properties/motions...handle near passes and similar objects. Many good nonrigid object trackers such as [34] use tiled patches with color histogram features to model objects...Chatterjee. Classification of textures using gaussian markov random fields. Acoustics , Speech and Signal Processing, IEEE Transactions on, 33(4):959–963

  13. Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast-to-noise objects.

    Science.gov (United States)

    Yip, Stephen S F; Rottmann, Joerg; Chen, Haijian; Morf, Daniel; Füglistaller, Rony; Star-Lack, Josh; Zentai, George; Berbeco, Ross

    2017-09-01

    We hypothesized that combining multiple amorphous silicon flat panel layers increases photon detection efficiency in an electronic portal imaging device (EPID), improving image quality and tracking accuracy of low-contrast targets during radiotherapy. The prototype imager evaluated in this study contained four individually programmable layers each with a copper converter layer, Gd 2 O 2 S scintillator, and active-matrix flat panel imager (AMFPI). The imager was placed on a Varian TrueBeam linac and a Las Vegas phantom programmed with sinusoidal motion (peak-to-peak amplitude = 20 mm, period = 3.5 s) was imaged at a frame rate of 10 Hz with one to four layers activated. Number of visible circles and CNR of least visible circle (depth = 0.5 mm, diameter = 7 mm) was computed to assess the image quality of single and multiple layers. A previously validated tracking algorithm was employed for auto-tracking. Tracking error was defined as the difference between the programmed and tracked positions of the circle. Pearson correlation coefficient (R) of CNR and tracking errors was computed. Motion-induced blurring significantly reduced circle visibility. During four cycles of phantom motion, the number of visible circles varied from 11-23, 13-24, 15-25, and 16-26 for one-, two-, three-, and four-layer imagers, respectively. Compared with using only a single layer, combining two, three, and four layers increased the median CNR by factors of 1.19, 1.42, and 1.71, respectively and reduced the average tracking error from 3.32 mm to 1.67 mm to 1.47 mm, and 0.74 mm, respectively. Significant correlations (P~10 -9 ) were found between the tracking error and CNR. Combination of four conventional EPID layers significantly improves the EPID image quality and tracking accuracy for a poorly visible object which is moving with a frequency and amplitude similar to respiratory motion. © 2017 American Association of Physicists in Medicine.

  14. 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.

  15. 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 video demonstration for teaching VE on a pelvic model.

  16. Ionospheric errors at L-band for satellite and re-entry object tracking in the new equatorial-anomaly region

    Energy Technology Data Exchange (ETDEWEB)

    Pakula, W.A.; Klobuchar, J.A.; Anderson, D.N.; Doherty, P.H.

    1990-05-03

    The ionosphere can significantly limit the accuracy of precise tracking of satellites and re-entry objects, especially in the equatorial anomaly region of the world where the electron density is the highest. The determine typical changes induced by the ionosphere, the Fully Analytic Ionospheric Model, (FAIM), was used to model range and range-rate errors over Kwajalein Island, located near the equatorial anomaly region in the Pacific. Model results show that range-rate errors of up to one foot per second can occur at L-band for certain, near-vertical re-entry object trajectories during high solar activity daytime conditions.

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

    Science.gov (United States)

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

    2017-03-24

    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 visual-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-games habits, participants were divided into Action Video Game Player and Non Action Video Game Player groups and underwent cognitive tests. The results confirm previous findings of studies of Action Video Game Players, 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 Action Video Game Player compared with the Non Action Video Game Player group. This result is consistent with our hypothesis and demonstrates a negative effect of playing action video games.

  18. DeTeCt 3.0: A software tool to detect impacts of small objects in video observations of Jupiter obtained by amateur astronomers

    Science.gov (United States)

    Juaristi, J.; Delcroix, M.; Hueso, R.; Sánchez-Lavega, A.

    2017-09-01

    Impacts of small size objects (10-20 m in diameter) with Jupiter atmosphere result in luminous superbolides that can be observed from the Earth with small size telescopes. Impacts of this kind have been observed four times by amateur astronomers since July 2010. The probability of observing one of these events is very small. Amateur astronomers observe Jupiter using fast video cameras that record thousands of frames during a few minutes which combine into a single image that generally results in a high-resolution image. Flashes are brief, faint and often lost by image reconstruction software. We present major upgrades in a software tool DeTeCt initially developed by amateur astronomer Marc Delcroix and our current project to maximize the chances of detecting more of these impacts in Jupiter.

  19. Knowledge-based understanding of aerial surveillance video

    Science.gov (United States)

    Cheng, Hui; Butler, Darren

    2006-05-01

    Aerial surveillance has long been used by the military to locate, monitor and track the enemy. Recently, its scope has expanded to include law enforcement activities, disaster management and commercial applications. With the ever-growing amount of aerial surveillance video acquired daily, there is an urgent need for extracting actionable intelligence in a timely manner. Furthermore, to support high-level video understanding, this analysis needs to go beyond current approaches and consider the relationships, motivations and intentions of the objects in the scene. In this paper we propose a system for interpreting aerial surveillance videos that automatically generates a succinct but meaningful description of the observed regions, objects and events. For a given video, the semantics of important regions and objects, and the relationships between them, are summarised into a semantic concept graph. From this, a textual description is derived that provides new search and indexing options for aerial video and enables the fusion of aerial video with other information modalities, such as human intelligence, reports and signal intelligence. Using a Mixture-of-Experts video segmentation algorithm an aerial video is first decomposed into regions and objects with predefined semantic meanings. The objects are then tracked and coerced into a semantic concept graph and the graph is summarized spatially, temporally and semantically using ontology guided sub-graph matching and re-writing. The system exploits domain specific knowledge and uses a reasoning engine to verify and correct the classes, identities and semantic relationships between the objects. This approach is advantageous because misclassifications lead to knowledge contradictions and hence they can be easily detected and intelligently corrected. In addition, the graph representation highlights events and anomalies that a low-level analysis would overlook.

  20. 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.

  1. 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.

  2. 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)

  3. More Evidence for Three Types of Cognitive Style: Validating the Object-Spatial Imagery and Verbal Questionnaire Using Eye Tracking when Learning with Texts and Pictures.

    Science.gov (United States)

    Höffler, Tim N; Koć-Januchta, Marta; Leutner, Detlev

    2017-01-01

    There is some indication that people differ regarding their visual and verbal cognitive style. The Object-Spatial Imagery and Verbal Questionnaire (OSIVQ) assumes a three-dimensional cognitive style model, which distinguishes between object imagery, spatial imagery and verbal dimensions. Using eye tracking as a means to observe actual gaze behaviours when learning with text-picture combinations, the current study aims to validate this three-dimensional assumption by linking the OSIVQ to learning behaviour. The results largely confirm the model in that they show the expected correlations between results on the OSIVQ, visuo-spatial ability and learning behaviour. Distinct differences between object visualizers, spatial visualizers and verbalizers could be demonstrated. © 2016 The Authors Published by John Wiley & Sons Ltd.

  4. Smart sensing surveillance video system

    Science.gov (United States)

    Hsu, Charles; Szu, Harold

    2016-05-01

    An intelligent video surveillance system is able to detect and identify abnormal and alarming situations by analyzing object movement. The Smart Sensing Surveillance Video (S3V) System is proposed to minimize video processing and transmission, thus allowing a fixed number of cameras to be connected on the system, and making it suitable for its applications in remote battlefield, tactical, and civilian applications including border surveillance, special force operations, airfield protection, perimeter and building protection, and etc. The S3V System would be more effective if equipped with visual understanding capabilities to detect, analyze, and recognize objects, track motions, and predict intentions. In addition, alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. The S3V System capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

  5. 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.

  6. 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.

  7. Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: an objective quantitative approach.

    Science.gov (United States)

    Bond, R R; Zhu, T; Finlay, D D; Drew, B; Kligfield, P D; Guldenring, D; Breen, C; Gallagher, A G; Daly, M J; Clifford, G D

    2014-01-01

    It is well known that accurate interpretation of the 12-lead electrocardiogram (ECG) requires a high degree of skill. There is also a moderate degree of variability among those who interpret the ECG. While this is the case, there are no best practice guidelines for the actual ECG interpretation process. Hence, this study adopts computerized eye tracking technology to investigate whether eye-gaze can be used to gain a deeper insight into how expert annotators interpret the ECG. Annotators were recruited in San Jose, California at the 2013 International Society of Computerised Electrocardiology (ISCE). Each annotator was recruited to interpret a number of 12-lead ECGs (N=12) while their eye gaze was recorded using a Tobii X60 eye tracker. The device is based on corneal reflection and is non-intrusive. With a sampling rate of 60Hz, eye gaze coordinates were acquired every 16.7ms. Fixations were determined using a predefined computerized classification algorithm, which was then used to generate heat maps of where the annotators looked. The ECGs used in this study form four groups (3=ST elevation myocardial infarction [STEMI], 3=hypertrophy, 3=arrhythmias and 3=exhibiting unique artefacts). There was also an equal distribution of difficulty levels (3=easy to interpret, 3=average and 3=difficult). ECGs were displayed using the 4x3+1 display format and computerized annotations were concealed. Precisely 252 expert ECG interpretations (21 annotators×12 ECGs) were recorded. Average duration for ECG interpretation was 58s (SD=23). Fleiss' generalized kappa coefficient (Pa=0.56) indicated a moderate inter-rater reliability among the annotators. There was a 79% inter-rater agreement for STEMI cases, 71% agreement for arrhythmia cases, 65% for the lead misplacement and dextrocardia cases and only 37% agreement for the hypertrophy cases. In analyzing the total fixation duration, it was found that on average annotators study lead V1 the most (4.29s), followed by leads V2 (3.83s

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

    Science.gov (United States)

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

    2017-06-01

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

  9. Development of an autonomous target tracking system

    Science.gov (United States)

    Gidda, Venkata Ramaiah

    In recent years, surveillance and border patrol have become one of the key research areas in UAV research. Increase in the computational capability of the computers and embedded electronics, coupled with compatibility of various commercial vision algorithms and commercial off the shelf (COTS) embedded electronics, and has further fuelled the research. The basic task in these applications is perception of environment through the available visual sensors like camera. Visual tracking, as the name implies, is tracking of objects using a camera. The process of autonomous target tracking starts with the selection of the target in a sequence of video frames transmitted from the on-board camera. We use an improved fast dynamic template matching algorithm coupled with Kalman Filter to track the selected target in consecutive video frames. The selected target is saved as a reference template. On the ground station computer, the reference template is overlaid on the live streaming video from the on-board system, starting from the upper left corner of the video frame. The template is slid pixel by pixel over the entire source image. A comparison of the pixels is performed between the template and source image. A confidence value R of the match is calculated at each pixel. Based on the method used to perform the template matching, the best match pixel location is found according to the highest or lowest confidence value R. The best match pixel location is communicated to the on-board gimbal controller over the wireless Xbee network. The software on the controller actuates the pan-tilt servos to continuously to hold the selected target at the center of the video frame. The complete system is a portable control system assembled from commercial off the shelf parts. The tracking system is tested on a target having several motion patterns.

  10. Development and Application of an Objective Tracking Algorithm for Tropical Cyclones over the North-West Pacific purely based on Wind Speeds

    Science.gov (United States)

    Befort, Daniel J.; Kruschke, Tim; Leckebusch, Gregor C.

    2017-04-01

    Tropical Cyclones over East Asia have huge socio-economic impacts due to their strong wind fields and large rainfall amounts. Especially, the most severe events are associated with huge economic losses, e.g. Typhoon Herb in 1996 is related to overall losses exceeding 5 billion US (Munich Re, 2016). In this study, an objective tracking algorithm is applied to JRA55 reanalysis data from 1979 to 2014 over the Western North Pacific. For this purpose, a purely wind based algorithm, formerly used to identify extra-tropical wind storms, has been further developed. The algorithm is based on the exceedance of the local 98th percentile to define strong wind fields in gridded climate data. To be detected as a tropical cyclone candidate, the following criteria must be fulfilled: 1) the wind storm must exist for at least eight 6-hourly time steps and 2) the wind field must exceed a minimum size of 130.000km2 for each time step. The usage of wind information is motivated to focus on damage related events, however, a pre-selection based on the affected region is necessary to remove events of extra-tropical nature. Using IBTrACS Best Tracks for validation, it is found that about 62% of all detected tropical cyclone events in JRA55 reanalysis can be matched to an observed best track. As expected the relative amount of matched tracks increases with the wind intensity of the event, with a hit rate of about 98% for Violent Typhoons, above 90% for Very Strong Typhoons and about 75% for Typhoons. Overall these results are encouraging as the parameters used to detect tropical cyclones in JRA55, e.g. minimum area, are also suitable to detect TCs in most CMIP5 simulations and will thus allow estimates of potential future changes.

  11. 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.

  12. Eye-Tracking

    Directory of Open Access Journals (Sweden)

    Gabriela GROSSECK

    2006-01-01

    Full Text Available Eye-tracking: one of the newest and most efficient methods of improving on-line marketing communication is called eye-tracking. Marketers have borrowed this technique, usually used in psychological and medical research, in order to study web users with the help of a video camera incorporated in the monitor.

  13. 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.

  14. Object Individuation or Object Movement as Attractor? A Replication of the Wide-Screen/Narrow-Screen Study by Means of (a Standard Looking Time Methodology and (b Eye Tracking

    Directory of Open Access Journals (Sweden)

    Peter Krøjgaard

    2013-01-01

    Full Text Available We report a replication experiment of a mechanized version of the seminal wide-screen/narrow-screen design of Wilcox and Baillargeon (1998 with 9.5-month-old infants (N=80. Two different methodologies were employed simultaneously: (a the standard looking time paradigm and (b eye tracking. Across conditions with three different screen sizes, the results from both methodologies revealed a clear and interesting pattern: the looking times increased as a significantly linear function of reduced screen sizes, that is, independently of the number of different objects involved. There was no indication in the data that the infants made use of the featural differences between the different-looking objects involved. The results suggest a simple, novel, and thought-provoking interpretation of the infants’ looking behavior in the wide-screen/narrow-screen design: moving objects are attractors, and the more space left for visible object movement in the visual field, the longer are infants’ looks. Consequently, no cognitive interpretation may be needed.

  15. 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.

  16. Using Bounding-Surrounding Boxes Method for Fish Tracking in Real World Underwater Observation

    Directory of Open Access Journals (Sweden)

    Yi-Haur Shiau

    2013-07-01

    Full Text Available The purpose of this paper is to present a rapid and efficient fish tracking method suitable for real world automatic underwater fish observation. Based on fish tracking, biologists are able to observe fish and their ecological environment. A distributed real-time underwater video stream system has been developed in Taiwan for large-scale, long-term ecological observation. In addition, not only does the system archive video data, but also incorporates data analysis. However, it is difficult to discriminate moving fish from drift water plants due to the severe drift of water plants caused by the water flow in real world underwater environments. Thus, fish tracking is complicated in unconstrained water. In order to overcome this problem, we propose a bounding-surrounding boxes method, which enables integration with state-of-the-art tracking methods for fish tracking in this paper. According to the method, fixing cameras must be used so that the moving fish are classified as foreground objects and are tracked, whereas the drifting water plants are classified as the background objects and are removed from the tracked objects. It enables the efficient, rapid removal of irrelevant information (non-fish objects from large-scale fish video data. Experimental results show that the proposed method is able to achieve high accuracy.

  17. 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...

  18. Robust visual tracking with contiguous occlusion constraint

    Science.gov (United States)

    Wang, Pengcheng; Qian, Weixian; Chen, Qian

    2016-02-01

    Visual tracking plays a fundamental role in video surveillance, robot vision and many other computer vision applications. In this paper, a robust visual tracking method that is motivated by the regularized ℓ1 tracker is proposed. We focus on investigating the case that the object target is occluded. Generally, occlusion can be treated as some kind of contiguous outlier with the target object as background. However, the penalty function of the ℓ1 tracker is not robust for relatively dense error distributed in the contiguous regions. Thus, we exploit a nonconvex penalty function and MRFs for outlier modeling, which is more probable to detect the contiguous occluded regions and recover the target appearance. For long-term tracking, a particle filter framework along with a dynamic model update mechanism is developed. Both qualitative and quantitative evaluations demonstrate a robust and precise performance.

  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. The posture-based motion planning framework: new findings related to object manipulation, moving around obstacles, moving in three spatial dimensions, and haptic tracking.

    Science.gov (United States)

    Rosenbaum, David A; Cohen, Rajal G; Dawson, Amanda M; Jax, Steven A; Meulenbroek, Ruud G; van der Wel, Robrecht; Vaughan, Jonathan

    2009-01-01

    We describe the results of recent studies inspired by the posture-based motion planning theory (Rosenbaum et al., 2001). The research concerns analyses of human object manipulation, obstacle avoidance, three-dimensional movement generation, and haptic tracking, the findings of which are discussed in relation to whether they support or fail to support the premises of the theory. Each of the aforementioned topics potentially challenges the theory's claim that, in motion, goal postures are planned before the selection of movements towards those postures. However, even the quasi-continuous phenomena under study show features that comply with prospective, end-state-based motion planning. We conclude that progress in motor control should not be frustrated by the view that no model is, or will ever be, optimal. Instead, it should find promise in the steady growth of insights afforded by challenges to existing theories.

  2. 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...

  3. An object-oriented modeling and simulation framework for bearings-only multi-target tracking using an unattended acoustic sensor network

    Science.gov (United States)

    Aslan, Murat Šamil

    2013-10-01

    Tracking ground targets using low cost ground-based sensors is a challenging field because of the limited capabilities of such sensors. Among the several candidates, including seismic and magnetic sensors, the acoustic sensors based on microphone arrays have a potential of being useful: They can provide a direction to the sound source, they can have a relatively better range, and the sound characteristics can provide a basis for target classification. However, there are still many problems. One of them is the difficulty to resolve multiple sound sources, another is that they do not provide distance, a third is the presence of background noise from wind, sea, rain, distant air and land traffic, people, etc., and a fourth is that the same target can sound very differently depending on factors like terrain type, topography, speed, gear, distance, etc. Use of sophisticated signal processing and data fusion algorithms is the key for compensating (to an extend) the limited capabilities and mentioned problems of these sensors. It is hard, if not impossible, to evaluate the performance of such complex algorithms analytically. For an effective evaluation, before performing expensive field trials, well-designed laboratory experiments and computer simulations are necessary. Along this line, in this paper, we present an object-oriented modeling and simulation framework which can be used to generate simulated data for the data fusion algorithms for tracking multiple on-road targets in an unattended acoustic sensor network. Each sensor node in the network is a circular microphone array which produces the direction of arrival (DOA) (or bearing) measurements of the targets and sends this information to a fusion center. We present the models for road networks, targets (motion and acoustic power) and acoustic sensors in an object-oriented fashion where different and possibly time-varying sampling periods for each sensor node is possible. Moreover, the sensor's signal processing and

  4. Enhancing Digital Video Analysis of Bar Kinematics in Weightlifting: A Case Study.

    Science.gov (United States)

    Dæhlin, Torstein E; Krosshaug, Tron; Chiu, Loren Z F

    2017-06-01

    Weightlifting technique can be objectively assessed from two-dimensional video recordings. Despite its importance, participants' bar trajectories in research involving the snatch or clean exercises are often not reported, potentially due to the time required to digitize video. The purpose of this investigation was to evaluate the use of a light-emitting diode (LED)-based marker, digital video, and open-source software to automatically track the bar end during weightlifting exercises. A former national-level weightlifter was recorded with a digital video camera performing the snatch, clean and jerk, and squat exercises. An LED-based marker was placed on the right end of the bar. This marker was automatically tracked using 2 open-source software programs to obtain vertical and horizontal position coordinates. The LED-based marker was successfully auto-tracked for all videos over a variety of camera settings. Furthermore, the vertical and horizontal bar displacements and vertical bar velocity were consistent between the 2 software programs. This study demonstrates that an LED-based marker can be automatically tracked using open-source software. This combination of an LED-based marker, consumer camera, and open-source software is an accessible, low-cost method to objectively evaluate weightlifting technique.

  5. Object Tracking Through Adaptive Correlation

    Science.gov (United States)

    1992-12-17

    images used were those utilized by Capt. Law (10) which were provided by the Model-Based Vision Laboratory, WL/ AARA , Wright-Patterson AFB, Ohio. These...kilometers to 1 kilometer distance. The FLIR images were provided by the Model-Based Vision Laboratory (WL/ AARA ). The images provided were 499x320 pixels in...MONITORING Mr. Jim Leonard AGENCY REPORT NUMBER WL/ AARA , WPAFB, OH 45433 11. SUPPLEMENTARY NOTES 12a. DISTRIBUTION /AVAILABILITY STATEMENT 12b

  6. Reactivity effects in video-based classroom research: : an investigation using teacher and student questionnaires as well as teacher eye-tracking.

    OpenAIRE

    Praetorius, Anna; McIntyre, Nora Ann; Klassen, Robert Mark

    2017-01-01

    One prominent problem of conducting observational assessments of teaching quality is the possibility of reactivity effects. To date, the issue of reactivity has received limited empirical attention. The present study, therefore, investigated reactivity in 447 students from 24 classes as well as their 12 teachers. We compared reactivity during lessons that were video-recorded with those that were not: according to t‑test analyses of teacher ratings and MIMIC analyses of student ratings, no sig...

  7. 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.

  8. Automatic detection and tracking of multiple interacting targets from a moving platform

    Science.gov (United States)

    Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

    2014-01-01

    In real-world scenarios, a target tracking system could be severely compromised by interactions, i.e., influences from the proximity and/or behavior of other targets or background objects. Closely spaced targets are difficult to distinguish, and targets may be partially or totally invisible for uncontrolled durations when occluded by other objects. These situations are very likely to degrade the performance or cause the tracker to fail because the system may use invalid target observations to update the tracks. To address these issues, we propose an integrated multitarget tracking system. A background-subtraction-based method is used to automatically detect moving objects in video frames captured by a moving camera. The data association method evaluates the overlap rates between newly detected objects (observations) and already-tracked targets and makes decisions pertaining to whether a target is interacting with other targets and whether it has a valid observation. According to the association results, distinct strategies are employed to update and manage the tracks of interacting versus well-isolated targets. This system has been tested with real-world airborne videos from the DARPA Video Verification of Identity program database and demonstrated excellent track continuity in the presence of occlusions and multiple target interactions, very low false alarm rate, and real-time operation on an ordinary general-purpose computer.

  9. Doppler tracking

    Science.gov (United States)

    Thomas, Christopher Jacob

    This study addresses the development of a methodology using the Doppler Effect for high-resolution, short-range tracking of small projectiles and vehicles. Minimal impact on the design of the moving object is achieved by incorporating only a transmitter in it and using ground stations for all other components. This is particularly useful for tracking objects such as sports balls that have configurations and materials that are not conducive to housing onboard instrumentation. The methodology developed here uses four or more receivers to monitor a constant frequency signal emitted by the object. Efficient and accurate schemes for filtering the raw signals, determining the instantaneous frequencies, time synching the frequencies from each receiver, smoothing the synced frequencies, determining the relative velocity and radius of the object and solving the nonlinear system of equations for object position in three dimensions as a function of time are developed and described here.

  10. 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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Adam C Oei

    Full Text Available 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

  13. 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.

  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. Objective evaluation of methods to track motion from clinical cardiac-gated tagged MRI without the use of a gold standard

    Science.gov (United States)

    Parages, Felipe M.; Denney, Thomas S.; Brankov, Jovan G.

    2015-03-01

    Cardiac-gated MRI is widely used for the task of measuring parameters related to heart motion. More specifically, gated tagged MRI is the preferred modality to estimate local deformation (strain) and rotational motion (twist) of myocardial tissue. Many methods have been proposed to estimate cardiac motion from gated MRI sequences. However, when dealing with clinical data, evaluation of these methods is problematic due to the absence of gold-standards for cardiac motion. To overcome that, a linear regression scheme known as regression-without-truth (RWT) was proposed in the past. RWT uses priors to model the distribution of true values, thus enabling us to assess image-analysis algorithms without knowledge of the ground-truth. Furthermore, it allows one to rank methods by means of an objective figure-of-merit γ (i.e. precision). In this work we apply RWT to compare the performance of several gated MRI motion-tracking methods (e.g. non-rigid registration, feature based, harmonic phase) at the task of estimating myocardial strain and left-ventricle (LV) twist, from a population of 18 clinical human cardiac-gated tagged MRI studies.

  16. 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

  17. Feature Quantization and Pooling for Videos

    Science.gov (United States)

    2014-05-01

    similar. 1.2 Context Video has become a very popular media for communication, entertainment , and science. Videos are widely used in educational...The same approach applied to action classification from YouTube videos of sport events shows that BoW approaches on real world data sets need further...dog videos, where the camera also tracks the people and animals . In Figure 4.38 we compare across action classes how well each segmentation

  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. 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.

  20. 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.