WorldWideScience

Sample records for video feature tracking

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

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

  3. 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.

  4. GPS-Aided Video Tracking

    Directory of Open Access Journals (Sweden)

    Udo Feuerhake

    2015-08-01

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

  5. Video Tracking dalam Digital Compositing untuk Paska Produksi Video

    Directory of Open Access Journals (Sweden)

    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. 

  6. 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.

  7. Object Tracking by Oversampling Local Features.

    Science.gov (United States)

    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.

  8. 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

  9. 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....

  10. 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.

  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. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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),

  19. Discriminative feature selection for visual tracking

    Science.gov (United States)

    Ma, Junkai; Luo, Haibo; Zhou, Wei; Song, Yingchao; Hui, Bin; Chang, Zheng

    2017-06-01

    Visual tracking is an important role in computer vision tasks. The robustness of tracking algorithm is a challenge. Especially in complex scenarios such as clutter background, illumination variation and appearance changes etc. As an important component in tracking algorithm, the appropriateness of feature is closed related to the tracking precision. In this paper, an online discriminative feature selection is proposed to provide the tracker the most discriminative feature. Firstly, a feature pool which contains different information of the image such as gradient, gray value and edge is built. And when every frame is processed during tracking, all of these features will be extracted. Secondly, these features are ranked depend on their discrimination between target and background and the highest scored feature is chosen to represent the candidate image patch. Then, after obtaining the tracking result, the target model will be update to adapt the appearance variation. The experiment show that our method is robust when compared with other state-of-the-art algorithms.

  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. 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

  2. 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.

  3. 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.

  4. ‘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.

  5. 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.

  6. Detection and tracking of facial features

    Science.gov (United States)

    De Silva, Liyanage C.; Aizawa, Kiyoharu; Hatori, Mitsutoshi

    1995-04-01

    Detection and tracking of facial features without using any head mounted devices may become required in various future visual communication applications, such as teleconferencing, virtual reality etc. In this paper we propose an automatic method of face feature detection using a method called edge pixel counting. Instead of utilizing color or gray scale information of the facial image, the proposed edge pixel counting method utilized the edge information to estimate the face feature positions such as eyes, nose and mouth in the first frame of a moving facial image sequence, using a variable size face feature template. For the remaining frames, feature tracking is carried out alternatively using a method called deformable template matching and edge pixel counting. One main advantage of using edge pixel counting in feature tracking is that it does not require the condition of a high inter frame correlation around the feature areas as is required in template matching. Some experimental results are shown to demonstrate the effectiveness of the proposed method.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Chang Yao-Jen

    2002-01-01

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

  9. Video Stabilization Using Feature Point Matching

    Science.gov (United States)

    Kulkarni, Shamsundar; Bormane, D. S.; Nalbalwar, S. L.

    2017-01-01

    Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper an algorithm is proposed to stabilize jittery videos. A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video is identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.

  10. 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.

  11. Robust Feedback Zoom Tracking for Digital Video Surveillance

    Directory of Open Access Journals (Sweden)

    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.

  12. Semisupervised feature selection via spline regression for video semantic recognition.

    Science.gov (United States)

    Han, Yahong; Yang, Yi; Yan, Yan; Ma, Zhigang; Sebe, Nicu; Zhou, Xiaofang

    2015-02-01

    To improve both the efficiency and accuracy of video semantic recognition, we can perform feature selection on the extracted video features to select a subset of features from the high-dimensional feature set for a compact and accurate video data representation. Provided the number of labeled videos is small, supervised feature selection could fail to identify the relevant features that are discriminative to target classes. In many applications, abundant unlabeled videos are easily accessible. This motivates us to develop semisupervised feature selection algorithms to better identify the relevant video features, which are discriminative to target classes by effectively exploiting the information underlying the huge amount of unlabeled video data. In this paper, we propose a framework of video semantic recognition by semisupervised feature selection via spline regression (S(2)FS(2)R) . Two scatter matrices are combined to capture both the discriminative information and the local geometry structure of labeled and unlabeled training videos: A within-class scatter matrix encoding discriminative information of labeled training videos and a spline scatter output from a local spline regression encoding data distribution. An l2,1 -norm is imposed as a regularization term on the transformation matrix to ensure it is sparse in rows, making it particularly suitable for feature selection. To efficiently solve S(2)FS(2)R , we develop an iterative algorithm and prove its convergency. In the experiments, three typical tasks of video semantic recognition, such as video concept detection, video classification, and human action recognition, are used to demonstrate that the proposed S(2)FS(2)R achieves better performance compared with the state-of-the-art methods.

  13. Feature-aided multiple target tracking in the image plane

    Science.gov (United States)

    Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

    2006-05-01

    Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

  14. 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...

  15. 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...

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. Tracking facial feature points with Gabor wavelets and shape models

    NARCIS (Netherlands)

    McKenna, SJ; Gong, SG; Wurtz, RP; Tanner, J; Banin, D; Bigun, J; Chollet, G; Borgefors, G

    1997-01-01

    A feature-based approach to tracking rigid and non-rigid facial motion is described. Feature points are characterised using Gabor wavelets and can be individually tracked by phase-based displacement estimation. In order to achieve robust tracking a flexible shape model is used to impose global

  4. 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

  5. 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.

  6. Feature Weighting via Optimal Thresholding for Video Analysis (Open Access)

    Science.gov (United States)

    2014-03-03

    combine multiple descriptors. For example, STIP [10] feature combines HOG descriptor for shape information and HOF descriptor for motion informa- tion...Dense Trajectories feature [23] is an integration of de- scriptors of trajectory, HOG , HOF and Motion Boundary Histogram (MBH). In the video action...three features pro- vided by [5]: STIP features with 5,000 dimensional BoWs representation, SIFT features extracted every two seconds with 5,000

  7. 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...

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Evaluation of Different Features for Face Recognition in Video

    Science.gov (United States)

    2014-09-01

    15 4 Graph presents the performance comparison among different algorithms implemented in OpenCV (Fisherfaces, Eigenfaces and LBPH)- all use...for face recog- nition in video, in particular those available in the OpenCV library [13]. Comparative performance analysis of these algorithms is...videos. The first one used a generic class that exists in OpenCV (version 2.4.1), called FeatureDetector, which allowed the automatic extraction of

  13. Tracking image features with PCA-SURF descriptors

    CSIR Research Space (South Africa)

    Pancham, A

    2015-05-01

    Full Text Available The tracking of moving points in image sequences requires unique features that can be easily distinguished. However, traditional feature descriptors are of high dimension, leading to larger storage requirement and slower computation. In this paper...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. 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

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

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

  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. 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.

  1. Video Anomaly Detection with Compact Feature Sets for Online Performance.

    Science.gov (United States)

    Leyva, Roberto; Sanchez, Victor; Li, Chang-Tsun

    2017-04-18

    Over the past decade, video anomaly detection has been explored with remarkable results. However, research on methodologies suitable for online performance is still very limited. In this paper, we present an online framework for video anomaly detection. The key aspect of our framework is a compact set of highly descriptive features, which is extracted from a novel cell structure that helps to define support regions in a coarse-to-fine fashion. Based on the scene's activity, only a limited number of support regions are processed, thus limiting the size of the feature set. Specifically, we use foreground occupancy and optical flow features. The framework uses an inference mechanism that evaluates the compact feature set via Gaussian Mixture Models, Markov Chains and Bag-of-Words in order to detect abnormal events. Our framework also considers the joint response of the models in the local spatio-temporal neighborhood to increase detection accuracy. We test our framework on popular existing datasets and on a new dataset comprising a wide variety of realistic videos captured by surveillance cameras. This particular dataset includes surveillance videos depicting criminal activities, car accidents and other dangerous situations. Evaluation results show that our framework outperforms other online methods and attains a very competitive detection performance compared to state-of-the-art non-online methods.

  2. Improving the selection of feature points for tracking

    NARCIS (Netherlands)

    Zivkovic, Z.; van der Heijden, Ferdinand

    The problem considered in this paper is how to select the feature points (in practice, small image patches are used) in an image from an image sequence, such that they can be tracked adequately further through the sequence. Usually, the tracking is performed by some sort of local search method

  3. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

    Science.gov (United States)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  4. 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.

  5. 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.

  6. 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.

  7. On scale invariant features and sequential Monte Carlo sampling for bronchoscope tracking

    Science.gov (United States)

    Luó, Xióngbiao; Feuerstein, Marco; Kitasaka, Takayuki; Natori, Hiroshi; Takabatake, Hirotsugu; Hasegawa, Yoshinori; Mori, Kensaku

    2011-03-01

    This paper presents an improved bronchoscope tracking method for bronchoscopic navigation using scale invariant features and sequential Monte Carlo sampling. Although image-based methods are widely discussed in the community of bronchoscope tracking, they are still limited to characteristic information such as bronchial bifurcations or folds and cannot automatically resume the tracking procedure after failures, which result usually from problematic bronchoscopic video frames or airway deformation. To overcome these problems, we propose a new approach that integrates scale invariant feature-based camera motion estimation into sequential Monte Carlo sampling to achieve an accurate and robust tracking. In our approach, sequential Monte Carlo sampling is employed to recursively estimate the posterior probability densities of the bronchoscope camera motion parameters according to the observation model based on scale invariant feature-based camera motion recovery. We evaluate our proposed method on patient datasets. Experimental results illustrate that our proposed method can track a bronchoscope more accurate and robust than current state-of-the-art method, particularly increasing the tracking performance by 38.7% without using an additional position sensor.

  8. 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 ...

  9. New features in MADX thin-lens tracking module

    CERN Document Server

    Sun, Y; CERN. Geneva. BE Department

    2010-01-01

    In this note, we introduce several new features of the MADX thin-lens tracking module, which include the new element AC dipole, the new feature ‘NOISE’ attached to the class ‘multipole’, and the offset of the ‘aperture’ model. We also present simulation results for the benchmark between different codes, and some applications with examples.

  10. New features in MADX thin-lens tracking module

    CERN Document Server

    Sun, YP; CERN. Geneva. BE Department

    2010-01-01

    In this note, we introduce several new features of the MADX thin-lens tracking module, which include the new element AC dipole, the new feature ‘NOISE’attached to the class ‘multipole’, and the offset of the ‘aperture’ model. We also present simulation results for the benchmark between different codes, and some applications with examples.

  11. 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.

  12. Audio-video feature correlation: faces and speech

    Science.gov (United States)

    Durand, Gwenael; Montacie, Claude; Caraty, Marie-Jose; Faudemay, Pascal

    1999-08-01

    This paper presents a study of the correlation of features automatically extracted from the audio stream and the video stream of audiovisual documents. In particular, we were interested in finding out whether speech analysis tools could be combined with face detection methods, and to what extend they should be combined. A generic audio signal partitioning algorithm as first used to detect Silence/Noise/Music/Speech segments in a full length movie. A generic object detection method was applied to the keyframes extracted from the movie in order to detect the presence or absence of faces. The correlation between the presence of a face in the keyframes and of the corresponding voice in the audio stream was studied. A third stream, which is the script of the movie, is warped on the speech channel in order to automatically label faces appearing in the keyframes with the name of the corresponding character. We naturally found that extracted audio and video features were related in many cases, and that significant benefits can be obtained from the joint use of audio and video analysis methods.

  13. Psychogenic Tremor: A Video Guide to Its Distinguishing Features

    Directory of Open Access Journals (Sweden)

    Joseph Jankovic

    2014-08-01

    Full Text Available Background: Psychogenic tremor is the most common psychogenic movement disorder. It has characteristic clinical features that can help distinguish it from other tremor disorders. There is no diagnostic gold standard and the diagnosis is based primarily on clinical history and examination. Despite proposed diagnostic criteria, the diagnosis of psychogenic tremor can be challenging. While there are numerous studies evaluating psychogenic tremor in the literature, there are no publications that provide a video/visual guide that demonstrate the clinical characteristics of psychogenic tremor. Educating clinicians about psychogenic tremor will hopefully lead to earlier diagnosis and treatment. Methods: We selected videos from the database at the Parkinson's Disease Center and Movement Disorders Clinic at Baylor College of Medicine that illustrate classic findings supporting the diagnosis of psychogenic tremor.Results: We include 10 clinical vignettes with accompanying videos that highlight characteristic clinical signs of psychogenic tremor including distractibility, variability, entrainability, suggestibility, and coherence.Discussion: Psychogenic tremor should be considered in the differential diagnosis of patients presenting with tremor, particularly if it is of abrupt onset, intermittent, variable and not congruous with organic tremor. The diagnosis of psychogenic tremor, however, should not be simply based on exclusion of organic tremor, such as essential, parkinsonian, or cerebellar tremor, but on positive criteria demonstrating characteristic features. Early recognition and management are critical for good long-term outcome.

  14. 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...

  15. Robust feature tracking on the beating heart for a robotic-guided endoscope.

    Science.gov (United States)

    Elhawary, Haytham; Popovic, Aleksandra

    2011-12-01

    Visualization during minimally invasive bypass surgery on the beating heart can be enhanced by using a robotic-guided endoscope and visual servoing from the endoscopic images. In order to achieve these objectives, this work has focused on developing and testing algorithms for accurate, robust and real-time motion tracking of features on the beating heart, using marker-less approaches and an uncalibrated endoscope. Lucas-Kanade pyramidal optical flow-based algorithms and speeded-up robust features (SURF)-based methods have been extensively evaluated, using a range of developed metrics, in order to quantify accuracy, robustness and drift under a variety of circumstances. Three sets of experiments are reported: the first set compared the two tracking methods, using a beating-heart phantom and a static endoscope; the second set evaluated the methods when images were taken using a moving robotic-guided endoscope; and finally, the Lucas-Kanade optical flow algorithm was extensively tested in a visual servoing application, using a robotic endoscope. The combination of a Lucas-Kanade tracking algorithm and a SURF-based feature detection method gave the best performance in terms of accuracy and robustness of tracking, while preserving real-time computation requirements. The optimal parameters consist of a window size of 51 × 51 pixels and an interframe motion threshold of 20 pixels. Feature tracking was successfully integrated into uncalibrated visual servoing or a robotic-guided endoscope. Robust feature tracking on a beating heart with endoscopic video can be achieved in real-time and may facilitate robotically-assisted, minimally invasive bypass surgery and conventional laparoscopic surgery. Copyright © 2011 John Wiley & Sons, Ltd.

  16. Cell Phone Video Recording Feature as a Language Learning Tool: A Case Study

    Science.gov (United States)

    Gromik, Nicolas A.

    2012-01-01

    This paper reports on a case study conducted at a Japanese national university. Nine participants used the video recording feature on their cell phones to produce weekly video productions. The task required that participants produce one 30-second video on a teacher-selected topic. Observations revealed the process of video creation with a cell…

  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. 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.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Bahadır KARASULU

    2013-04-01

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

  1. 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

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  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 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.

  6. 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

  7. Robust feature tracking for endoscopic pose estimation and structure recovery

    Science.gov (United States)

    Speidel, S.; Krappe, S.; Röhl, S.; Bodenstedt, S.; Müller-Stich, B.; Dillmann, R.

    2013-03-01

    Minimally invasive surgery is a highly complex medical discipline with several difficulties for the surgeon. To alleviate these difficulties, augmented reality can be used for intraoperative assistance. For visualization, the endoscope pose must be known which can be acquired with a SLAM (Simultaneous Localization and Mapping) approach using the endoscopic images. In this paper we focus on feature tracking for SLAM in minimally invasive surgery. Robust feature tracking and minimization of false correspondences is crucial for localizing the endoscope. As sensory input we use a stereo endoscope and evaluate different feature types in a developed SLAM framework. The accuracy of the endoscope pose estimation is validated with synthetic and ex vivo data. Furthermore we test the approach with in vivo image sequences from da Vinci interventions.

  8. 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

  9. Feature Extraction in IR Images Via Synchronous Video Detection

    Science.gov (United States)

    Shepard, Steven M.; Sass, David T.

    1989-03-01

    IR video images acquired by scanning imaging radiometers are subject to several problems which make measurement of small temperature differences difficult. Among these problems are 1) aliasing, which occurs When events at frequencies higher than the video frame rate are observed, 2) limited temperature resolution imposed by the 3-bit digitization available in existing commercial systems, and 3) susceptibility to noise and background clutter. Bandwidth narrowing devices (e.g. lock-in amplifiers or boxcar averagers) are routinely used to achieve a high degree of signal to noise improvement for time-varying 1-dimensional signals. We will describe techniques which allow similar S/N improvement for 2-dimensional imagery acquired with an off the shelf scanning imaging radiometer system. These techniques are iplemented in near-real-time, utilizing a microcomputer and specially developed hardware and software . We will also discuss the application of the system to feature extraction in cluttered images, and to acquisition of events which vary faster than the frame rate.

  10. 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.

  11. 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.

  12. 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.

  13. Adaptive Compressive Tracking via Online Vector Boosting Feature Selection.

    Science.gov (United States)

    Liu, Qingshan; Yang, Jing; Zhang, Kaihua; Wu, Yi

    2017-12-01

    Recently, the compressive tracking (CT) method has attracted much attention due to its high efficiency, but it cannot well deal with the large scale target appearance variations due to its data-independent random projection matrix that results in less discriminative features. To address this issue, in this paper, we propose an adaptive CT approach, which selects the most discriminative features to design an effective appearance model. Our method significantly improves CT in three aspects. First, the most discriminative features are selected via an online vector boosting method. Second, the object representation is updated in an effective online manner, which preserves the stable features while filtering out the noisy ones. Furthermore, a simple and effective trajectory rectification approach is adopted that can make the estimated location more accurate. Finally, a multiple scale adaptation mechanism is explored to estimate object size, which helps to relieve interference from background information. Extensive experiments on the CVPR2013 tracking benchmark and the VOT2014 challenges demonstrate the superior performance of our method.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. 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.

  17. 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.

  18. Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

    Directory of Open Access Journals (Sweden)

    Alireza Behrad

    2013-02-01

    Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

  19. 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.

  20. 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

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

    Directory of Open Access Journals (Sweden)

    Rik Van de Walle

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lerouge Sam

    2007-01-01

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

  3. 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.

  4. Graph clustering for weapon discharge event detection and tracking in infrared imagery using deep features

    Science.gov (United States)

    Bhattacharjee, Sreyasee Das; Talukder, Ashit

    2017-05-01

    This paper addresses the problem of detecting and tracking weapon discharge event in an Infrared Imagery collection. While most of the prior work in related domains exploits the vast amount of complementary in- formation available from both visible-band (EO) and Infrared (IR) image (or video sequences), we handle the problem of recognizing human pose and activity detection exclusively in thermal (IR) images or videos. The task is primarily two-fold: 1) locating the individual in the scene from IR imagery, and 2) identifying the correct pose of the human individual (i.e. presence or absence of weapon discharge activity or intent). An efficient graph-based shortlisting strategy for identifying candidate regions of interest in the IR image utilizes both image saliency and mutual similarities from the initial list of the top scored proposals of a given query frame, which ensures an improved performance for both detection and recognition simultaneously and reduced false alarms. The proposed search strategy offers an efficient feature extraction scheme that can capture the maximum amount of object structural information by defining a region- based deep shape descriptor representing each object of interest present in the scene. Therefore, our solution is capable of handling the fundamental incompleteness of the IR imageries for which the conventional deep features optimized on the natural color images in Imagenet are not quite suitable. Our preliminary experiments on the OSU weapon dataset demonstrates significant success in automated recognition of weapon discharge events from IR imagery.

  5. Classification of user performance in the Ruff Figural Fluency Test based on eye-tracking features

    Directory of Open Access Journals (Sweden)

    Borys Magdalena

    2017-01-01

    Full Text Available Cognitive assessment in neurological diseases represents a relevant topic due to its diagnostic significance in detecting disease, but also in assessing progress of the treatment. Computer-based tests provide objective and accurate cognitive skills and capacity measures. The Ruff Figural Fluency Test (RFFT provides information about non-verbal capacity for initiation, planning, and divergent reasoning. The traditional paper form of the test was transformed into a computer application and examined. The RFFT was applied in an experiment performed among 70 male students to assess their cognitive performance in the laboratory environment. Each student was examined in three sequential series. Besides the students’ performances measured by using in app keylogging, the eye-tracking data obtained by non-invasive video-based oculography were gathered, from which several features were extracted. Eye-tracking features combined with performance measures (a total number of designs and/or error ratio were applied in machine learning classification. Various classification algorithms were applied, and their accuracy, specificity, sensitivity and performance were compared.

  6. 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.

  7. 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.

  8. Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

    Directory of Open Access Journals (Sweden)

    Ji Ming

    2008-03-01

    Full Text Available We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

  9. A spatiotemporal feature-based approach for facial expression recognition from depth video

    Science.gov (United States)

    Uddin, Md. Zia

    2015-07-01

    In this paper, a novel spatiotemporal feature-based method is proposed to recognize facial expressions from depth video. Independent Component Analysis (ICA) spatial features of the depth faces of facial expressions are first augmented with the optical flow motion features. Then, the augmented features are enhanced by Fisher Linear Discriminant Analysis (FLDA) to make them robust. The features are then combined with on Hidden Markov Models (HMMs) to model different facial expressions that are later used to recognize appropriate expression from a test expression depth video. The experimental results show superior performance of the proposed approach over the conventional methods.

  10. 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 

  11. Real-time skin feature identification in a time-sequential video stream

    Science.gov (United States)

    Kramberger, Iztok

    2005-04-01

    Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.

  12. A Joint Compression Scheme of Video Feature Descriptors and Visual Content.

    Science.gov (United States)

    Zhang, Xiang; Ma, Siwei; Wang, Shiqi; Zhang, Xinfeng; Sun, Huifang; Gao, Wen

    2017-02-01

    High-efficiency compression of visual feature descriptors has recently emerged as an active topic due to the rapidly increasing demand in mobile visual retrieval over bandwidth-limited networks. However, transmitting only those feature descriptors may largely restrict its application scale due to the lack of necessary visual content. To facilitate the wide spread of feature descriptors, a hybrid framework of jointly compressing the feature descriptors and visual content is highly desirable. In this paper, such a content-plus-feature coding scheme is investigated, aiming to shape the next generation of video compression system toward visual retrieval, where the high-efficiency coding of both feature descriptors and visual content can be achieved by exploiting the interactions between each other. On the one hand, visual feature descriptors can achieve compact and efficient representation by taking advantages of the structure and motion information in the compressed video stream. To optimize the retrieval performance, a novel rate-accuracy optimization technique is proposed to accurately estimate the retrieval performance degradation in feature coding. On the other hand, the already compressed feature data can be utilized to further improve the video coding efficiency by applying feature matching-based affine motion compensation. Extensive simulations have shown that the proposed joint compression framework can offer significant bitrate reduction in representing both feature descriptors and video frames, while simultaneously maintaining the state-of-the-art visual retrieval performance.

  13. 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.

  14. 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.

  15. Forest Fire Smoke Video Detection Using Spatiotemporal and Dynamic Texture Features

    Directory of Open Access Journals (Sweden)

    Yaqin Zhao

    2015-01-01

    Full Text Available Smoke detection is a very key part of fire recognition in a forest fire surveillance video since the smoke produced by forest fires is visible much before the flames. The performance of smoke video detection algorithm is often influenced by some smoke-like objects such as heavy fog. This paper presents a novel forest fire smoke video detection based on spatiotemporal features and dynamic texture features. At first, Kalman filtering is used to segment candidate smoke regions. Then, candidate smoke region is divided into small blocks. Spatiotemporal energy feature of each block is extracted by computing the energy features of its 8-neighboring blocks in the current frame and its two adjacent frames. Flutter direction angle is computed by analyzing the centroid motion of the segmented regions in one candidate smoke video clip. Local Binary Motion Pattern (LBMP is used to define dynamic texture features of smoke videos. Finally, smoke video is recognized by Adaboost algorithm. The experimental results show that the proposed method can effectively detect smoke image recorded from different scenes.

  16. Cooperative vehicle control, feature tracking and ocean sampling

    Science.gov (United States)

    Fiorelli, Edward A.

    This dissertation concerns the development of a feedback control framework for coordinating multiple, sensor-equipped, autonomous vehicles into mobile sensing arrays to perform adaptive sampling of observed fields. The use of feedback is central; it maintains the array, i.e. regulates formation position, orientation, and shape, and directs the array to perform its sampling mission in response to measurements taken by each vehicle. Specifically, we address how to perform autonomous gradient tracking and feature detection in an unknown field such as temperature or salinity in the ocean. Artificial potentials and virtual bodies are used to coordinate the autonomous vehicles, modelled as point masses (with unit mass). The virtual bodies consist of linked, moving reference points called virtual leaders. Artificial potentials couple the dynamics of the vehicles and the virtual bodies. The dynamics of the virtual body are then prescribed allowing the virtual body, and thus the vehicle group, to perform maneuvers that include translation, rotation and contraction/expansion, while ensuring that the formation error remains bounded. This methodology is called the Virtual Body and Artificial Potential (VBAP) methodology. We then propose how to utilize these arrays to perform autonomous gradient climbing and front tracking in the presence of both correlated and uncorrelated noise. We implement various techniques for estimation of gradients (first-order and higher), including finite differencing, least squares error minimization, averaging, and Kalman filtering. Furthermore, we illustrate how the estimation error can be used to optimally choose the formation size. To complement our theoretical work, we present an account of sea trials performed with a fleet of autonomous underwater gliders in Monterey Bay during the Autonomous Ocean Sampling Network (AOSN) II project in August 2003. During these trials, Slocum autonomous underwater gliders were coordinated into triangle

  17. 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.

  18. Motion tracking and gait feature estimation for recognising Parkinson's disease using MS Kinect.

    Science.gov (United States)

    Ťupa, Ondřej; Procházka, Aleš; Vyšata, Oldřich; Schätz, Martin; Mareš, Jan; Vališ, Martin; Mařík, Vladimír

    2015-10-24

    Analysis of gait features provides important information during the treatment of neurological disorders, including Parkinson's disease. It is also used to observe the effects of medication and rehabilitation. The methodology presented in this paper enables the detection of selected gait attributes by Microsoft (MS) Kinect image and depth sensors to track movements in three-dimensional space. The experimental part of the paper is devoted to the study of three sets of individuals: 18 patients with Parkinson's disease, 18 healthy aged-matched individuals, and 15 students. The methodological part of the paper includes the use of digital signal-processing methods for rejecting gross data-acquisition errors, segmenting video frames, and extracting gait features. The proposed algorithm describes methods for estimating the leg length, normalised average stride length (SL), and gait velocity (GV) of the individuals in the given sets using MS Kinect data. The main objective of this work involves the recognition of selected gait disorders in both the clinical and everyday settings. The results obtained include an evaluation of leg lengths, with a mean difference of 0.004 m in the complete set of 51 individuals studied, and of the gait features of patients with Parkinson's disease (SL: 0.38 m, GV: 0.61 m/s) and an age-matched reference set (SL: 0.54 m, GV: 0.81 m/s). Combining both features allowed for the use of neural networks to classify and evaluate the selectivity, specificity, and accuracy. The achieved accuracy was 97.2 %, which suggests the potential use of MS Kinect image and depth sensors for these applications. Discussion points include the possibility of using the MS Kinect sensors as inexpensive replacements for complex multi-camera systems and treadmill walking in gait-feature detection for the recognition of selected gait disorders.

  19. 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

  20. Cardiac magnetic resonance feature tracking in Kawasaki disease convalescence.

    Science.gov (United States)

    Bratis, Konstantinos; Hachmann, Pauline; Child, Nicholas; Krasemann, Thomas; Hussain, Tarique; Mavrogeni, Sophie; Botnar, Rene; Razavi, Reza; Greil, Gerald

    2017-01-01

    The objective of this study was to determine whether left ventricular (LV) myocardial deformation indices can detect subclinical abnormalities in Kawasaki disease convalescence. We hypothesized that subclinical myocardial abnormalities due to inflammation represent an early manifestation of the disease that persists in convalescence. Myocardial inflammation has been described as a global finding in the acute phase of Kawasaki disease. Despite normal systolic function by routine functional measurements, reduced longitudinal strain and strain rate have been detected by echocardiography in the acute phase. Peak systolic LV myocardial longitudinal, radial, and circumferential strain and strain rate were examined in 29 Kawasaki disease convalescent patients (15 males; mean [standard deviation] age: 11 [6.6] years; median interval from disease onset: 5.8 [5.4] years) and 10 healthy volunteers (5 males; mean age: 14 [3.8] years) with the use of cardiac magnetic resonance (CMR) feature tracking. Routine indices of LV systolic function were normal in both groups. Comparisons were made between normal controls and (i) the entire Kawasaki disease group, (ii) Kawasaki disease subgroup divided by coronary artery involvement. Average longitudinal and circumferential strain at all levels was lower in patients compared to normal controls. In subgroup analysis, both Kawasaki disease patients with and without a history of coronary involvement had similar longitudinal and circumferential strain at all levels and lower when compared to controls. There were lower circumferential and longitudinal values in Kawasaki disease patients with persisting coronary artery lesions when compared to those with regressed ones. In this CMR study in Kawasaki disease convalescent patients with preserved routine functional indices, we detected lower circumferential and longitudinal strain values compared to normal controls, irrespective of the coronary artery status.

  1. 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.

  2. Real-time UAV trajectory generation using feature points matching between video image sequences

    Science.gov (United States)

    Byun, Younggi; Song, Jeongheon; Han, Dongyeob

    2017-09-01

    Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

  3. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks.

    Science.gov (United States)

    Jiang, Yu-Gang; Wu, Zuxuan; Wang, Jun; Xue, Xiangyang; Chang, Shih-Fu

    2018-02-01

    In this paper, we study the challenging problem of categorizing videos according to high-level semantics such as the existence of a particular human action or a complex event. Although extensive efforts have been devoted in recent years, most existing works combined multiple video features using simple fusion strategies and neglected the utilization of inter-class semantic relationships. This paper proposes a novel unified framework that jointly exploits the feature relationships and the class relationships for improved categorization performance. Specifically, these two types of relationships are estimated and utilized by imposing regularizations in the learning process of a deep neural network (DNN). Through arming the DNN with better capability of harnessing both the feature and the class relationships, the proposed regularized DNN (rDNN) is more suitable for modeling video semantics. We show that rDNN produces better performance over several state-of-the-art approaches. Competitive results are reported on the well-known Hollywood2 and Columbia Consumer Video benchmarks. In addition, to stimulate future research on large scale video categorization, we collect and release a new benchmark dataset, called FCVID, which contains 91,223 Internet videos and 239 manually annotated categories.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Game theory-based visual tracking approach focusing on color and texture features.

    Science.gov (United States)

    Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Chen, Chuanhua; Wang, Xin

    2017-07-20

    It is difficult for a single-feature tracking algorithm to achieve strong robustness under a complex environment. To solve this problem, we proposed a multifeature fusion tracking algorithm that is based on game theory. By focusing on color and texture features as two gamers, this algorithm accomplishes tracking by using a mean shift iterative formula to search for the Nash equilibrium of the game. The contribution of different features is always keeping the state of optical balance, so that the algorithm can fully take advantage of feature fusion. According to the experiment results, this algorithm proves to possess good performance, especially under the condition of scene variation, target occlusion, and similar interference.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

    Science.gov (United States)

    Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

    2017-09-01

    Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. Scientists feature their work in Arctic-focused short videos by FrontierScientists

    Science.gov (United States)

    Nielsen, L.; O'Connell, E.

    2013-12-01

    Whether they're guiding an unmanned aerial vehicle into a volcanic plume to sample aerosols, or documenting core drilling at a frozen lake in Siberia formed 3.6 million years ago by a massive meteorite impact, Arctic scientists are using video to enhance and expand their science and science outreach. FrontierScientists (FS), a forum for showcasing scientific work, produces and promotes radically different video blogs featuring Arctic scientists. Three- to seven- minute multimedia vlogs help deconstruct researcher's efforts and disseminate stories, communicating scientific discoveries to our increasingly connected world. The videos cover a wide range of current field work being performed in the Arctic. All videos are freely available to view or download from the FrontierScientists.com website, accessible via any internet browser or via the FrontierScientists app. FS' filming process fosters a close collaboration between the scientist and the media maker. Film creation helps scientists reach out to the public, communicate the relevance of their scientific findings, and craft a discussion. Videos keep audience tuned in; combining field footage, pictures, audio, and graphics with a verbal explanation helps illustrate ideas, allowing one video to reach people with different learning strategies. The scientists' stories are highlighted through social media platforms online. Vlogs grant scientists a voice, letting them illustrate their own work while ensuring accuracy. Each scientific topic on FS has its own project page where easy-to-navigate videos are featured prominently. Video sets focus on different aspects of a researcher's work or follow one of their projects into the field. We help the scientist slip the answers to their five most-asked questions into the casual script in layman's terms in order to free the viewers' minds to focus on new concepts. Videos are accompanied by written blogs intended to systematically demystify related facts so the scientists can focus

  17. Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

    Science.gov (United States)

    Kerr, Deirdre; Chung, Gregory K. W. K.

    2012-01-01

    The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

  18. Feature-based fast coding unit partition algorithm for high efficiency video coding

    Directory of Open Access Journals (Sweden)

    Yih-Chuan Lin

    2015-04-01

    Full Text Available High Efficiency Video Coding (HEVC, which is the newest video coding standard, has been developed for the efficient compression of ultra high definition videos. One of the important features in HEVC is the adoption of a quad-tree based video coding structure, in which each incoming frame is represented as a set of non-overlapped coding tree blocks (CTB by variable-block sized prediction and coding process. To do this, each CTB needs to be recursively partitioned into coding unit (CU, predict unit (PU and transform unit (TU during the coding process, leading to a huge computational load in the coding of each video frame. This paper proposes to extract visual features in a CTB and uses them to simplify the coding procedure by reducing the depth of quad-tree partition for each CTB in HEVC intra coding mode. A measure for the edge strength in a CTB, which is defined with simple Sobel edge detection, is used to constrain the possible maximum depth of quad-tree partition of the CTB. With the constrained partition depth, the proposed method can reduce a lot of encoding time. Experimental results by HM10.1 show that the average time-savings is about 13.4% under the increase of encoded BD-Rate by only 0.02%, which is a less performance degradation in comparison to other similar methods.

  19. Comparison of clustering methods for tracking features in RGB-D images

    CSIR Research Space (South Africa)

    Pancham, Ardhisha

    2016-10-01

    Full Text Available difficult to track individually over an image sequence. Clustering techniques have been recommended and used to cluster image features to improve tracking results. New and affordable RGB-D cameras, provide both color and depth information. This paper...

  20. 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.

  1. 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.

  2. Myocardial deformation assessment using cardiovascular magnetic resonance-feature tracking technique.

    Science.gov (United States)

    Almutairi, Haifa M; Boubertakh, Redha; Miquel, Marc E; Petersen, Steffen E

    2017-12-01

    Cardiovascular magnetic resonance (CMR) imaging is an important modality that allows the assessment of regional myocardial function by measuring myocardial deformation parameters, such as strain and strain rate throughout the cardiac cycle. Feature tracking is a promising quantitative post-processing technique that is increasingly used. It is commonly applied to cine images, in particular steady-state free precession, acquired during routine CMR examinations. To review the studies that have used feature tracking techniques in healthy subjects or patients with cardiovascular diseases. The article emphasizes the advantages and limitations of feature tracking when applied to regional deformation parameters. The challenges of applying the techniques in clinics and potential solutions are also reviewed. Research studies in healthy volunteers and/or patients either applied CMR-feature tracking alone to assess myocardial motion or compared it with either established CMR-tagging techniques or to speckle tracking echocardiography. These studies assessed the feasibility and reliability of calculating or determining global and regional myocardial deformation strain parameters. Regional deformation parameters are reviewed and compared. Better reproducibility for global deformation was observed compared with segmental parameters. Overall, studies demonstrated that circumferential was the most reproducible deformation parameter, usually followed by longitudinal strain; in contrast, radial strain showed high variability. Although feature tracking is a promising tool, there are still discrepancies in the results obtained using different software packages. This highlights a clear need for standardization of MRI acquisition parameters and feature tracking analysis methodologies. Validation, including physical and numerical phantoms, is still required to facilitate the use of feature tracking in routine clinical practice.

  3. 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.

  4. 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.

  5. A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Ahmad Jalal

    2017-08-01

    Full Text Available Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition.

  6. 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.

  7. EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

    Science.gov (United States)

    Kortelainen, Jukka; Seppänen, Tapio

    2013-01-01

    Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

  8. 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.

  9. 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.

  10. Feature Classification for Robust Shape-Based Collaborative Tracking and Model Updating

    Directory of Open Access Journals (Sweden)

    C. S. Regazzoni

    2008-09-01

    Full Text Available A new collaborative tracking approach is introduced which takes advantage of classified features. The core of this tracker is a single tracker that is able to detect occlusions and classify features contributing in localizing the object. Features are classified in four classes: good, suspicious, malicious, and neutral. Good features are estimated to be parts of the object with a high degree of confidence. Suspicious ones have a lower, yet significantly high, degree of confidence to be a part of the object. Malicious features are estimated to be generated by clutter, while neutral features are characterized with not a sufficient level of uncertainty to be assigned to the tracked object. When there is no occlusion, the single tracker acts alone, and the feature classification module helps it to overcome distracters such as still objects or little clutter in the scene. When more than one desired moving objects bounding boxes are close enough, the collaborative tracker is activated and it exploits the advantages of the classified features to localize each object precisely as well as updating the objects shape models more precisely by assigning again the classified features to the objects. The experimental results show successful tracking compared with the collaborative tracker that does not use the classified features. Moreover, more precise updated object shape models will be shown.

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

    Directory of Open Access Journals (Sweden)

    Sanjay Singh

    2017-05-01

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

  12. Exemplar-Based Image and Video Stylization Using Fully Convolutional Semantic Features.

    Science.gov (United States)

    Zhu, Feida; Yan, Zhicheng; Bu, Jiajun; Yu, Yizhou

    2017-05-10

    Color and tone stylization in images and videos strives to enhance unique themes with artistic color and tone adjustments. It has a broad range of applications from professional image postprocessing to photo sharing over social networks. Mainstream photo enhancement softwares, such as Adobe Lightroom and Instagram, provide users with predefined styles, which are often hand-crafted through a trial-and-error process. Such photo adjustment tools lack a semantic understanding of image contents and the resulting global color transform limits the range of artistic styles it can represent. On the other hand, stylistic enhancement needs to apply distinct adjustments to various semantic regions. Such an ability enables a broader range of visual styles. In this paper, we first propose a novel deep learning architecture for exemplar-based image stylization, which learns local enhancement styles from image pairs. Our deep learning architecture consists of fully convolutional networks (FCNs) for automatic semantics-aware feature extraction and fully connected neural layers for adjustment prediction. Image stylization can be efficiently accomplished with a single forward pass through our deep network. To extend our deep network from image stylization to video stylization, we exploit temporal superpixels (TSPs) to facilitate the transfer of artistic styles from image exemplars to videos. Experiments on a number of datasets for image stylization as well as a diverse set of video clips demonstrate the effectiveness of our deep learning architecture.

  13. Non-cooperative spacecraft pose tracking based on point cloud feature

    Science.gov (United States)

    He, Ying; Liang, Bin; He, Jin; Li, Shunzhi

    2017-10-01

    On-orbit services have been paid more and more attention for its role in spacecraft life-extension, capacity improvement and on-orbit debris removal. As most of on-orbit targets are non-cooperative, relatively accurate pose measurement is very essential for subsequent operations. However, with the rapid development of TriDAR, flash LIDAR and other laser scanning equipment in non-cooperative target measurement, it becomes more imperative to research methods for non-cooperative target pose tracking based on 3D point cloud feature. In this paper, a method for non-cooperative target pose tracking based on point cloud feature is proposed. Firstly, the target is identified using curvature, normal, density and other geometric features of the point cloud. Then the particle filter algorithm is used to recognize the position and orientation of the target being tracked by calculating the similarity of the point cloud features of two adjacent frames. Experimental results showed that the proposed method could effectively identify the features of non-cooperative targets and track their position and attitude.

  14. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    National Research Council Canada - National Science Library

    Chang, Yuchou; Lee, DJ; Hong, Yi; Archibald, James

    .... In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection...

  15. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Science.gov (United States)

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  16. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Directory of Open Access Journals (Sweden)

    Florian Eyben

    Full Text Available Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A feature point identification method for positron emission particle tracking with multiple tracers

    Energy Technology Data Exchange (ETDEWEB)

    Wiggins, Cody, E-mail: cwiggin2@vols.utk.edu [University of Tennessee-Knoxville, Department of Physics and Astronomy, 1408 Circle Drive, Knoxville, TN 37996 (United States); Santos, Roque [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States); Escuela Politécnica Nacional, Departamento de Ciencias Nucleares (Ecuador); Ruggles, Arthur [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States)

    2017-01-21

    A novel detection algorithm for Positron Emission Particle Tracking (PEPT) with multiple tracers based on optical feature point identification (FPI) methods is presented. This new method, the FPI method, is compared to a previous multiple PEPT method via analyses of experimental and simulated data. The FPI method outperforms the older method in cases of large particle numbers and fine time resolution. Simulated data show the FPI method to be capable of identifying 100 particles at 0.5 mm average spatial error. Detection error is seen to vary with the inverse square root of the number of lines of response (LORs) used for detection and increases as particle separation decreases. - Highlights: • A new approach to positron emission particle tracking is presented. • Using optical feature point identification analogs, multiple particle tracking is achieved. • Method is compared to previous multiple particle method. • Accuracy and applicability of method is explored.

  2. Mobile Augmented Reality Support for Architects based on feature Tracking Techniques

    DEFF Research Database (Denmark)

    Grønbæk, Kaj; Nielsen, Mikkel Bang; Kramp, Gunnar

    2004-01-01

    This paper presents a mobile Augmented Reality (AR) system called the SitePack supporting architects in visualizing 3D models in real-time on site. We describe how vision based feature tracking techniques can help architects making decisions on site concerning visual impact assessment. The AR...

  3. Using active contour models for feature extraction in camera-based seam tracking of arc welding

    DEFF Research Database (Denmark)

    Liu, Jinchao; Fan, Zhun; Olsen, Søren

    2009-01-01

    . It is highly desirable to extract groove features closer to the arc and thus facilitate for a nearly-closed-loop control situation. On the other hand, for performing seam tracking and nearly-closed-loop control it is not necessary to obtain very detailed information about the molten pool area as long as some...

  4. Fusion of visual and audio features for person identification in real video

    Science.gov (United States)

    Li, Dongge; Wei, Gang; Sethi, Ishwar K.; Dimitrova, Nevenka

    2001-01-01

    In this research, we studied the joint use of visual and audio information for the problem of identifying persons in real video. A person identification system, which is able to identify characters in TV shows by the fusion of audio and visual information, is constructed based on two different fusion strategies. In the first strategy, speaker identification is used to verify the face recognition result. The second strategy consists of using face recognition and tracking to supplement speaker identification results. To evaluate our system's performance, an information database was generated by manually labeling the speaker and the main person's face in every I-frame of a video segment of the TV show 'Seinfeld'. By comparing the output form our system with our information database, we evaluated the performance of each of the analysis channels and their fusion. The results show that while the first fusion strategy is suitable for applications where precision is much more critical than recall. The second fusion strategy, on the other hand, generates the best overall identification performance. It outperforms either of the analysis channels greatly in both precision an recall and is applicable to more general applications, such as, in our case, to identify persons in TV programs.

  5. Use of digital video for documentation of microscopic features of tissue samples.

    Science.gov (United States)

    Melín-Aldana, Héctor; Gasilionis, Valdas; Kapur, Umesh

    2008-05-01

    Digital photography is commonly used to document microscopic features of tissue samples, but it relies on the capture of arbitrarily selected representative areas. Current technologic advances permit the review of an entire sample, some even replicating the use of a microscope. To demonstrate the applicability of digital video to the documentation of histologic samples. A Canon Elura MC40 digital camcorder was mounted on a microscope, glass slide-mounted tissue sections were filmed, and the unedited movies were transferred to a Apple Mac Pro computer. Movies were edited using the software iMovie HD, including placement of a time counter and a voice recording. The finished movies can be viewed in computers, incorporated onto DVDs, or placed on a Web site after compression with Flash software. The final movies range, on average, between 2 and 8 minutes, depending on the size of the sample, and between 50 MB and 1.6 GB, depending on the intended means of distribution, with DVDs providing the best image quality. Digital video is a practical methodology for documentation of entire tissue samples. We propose an affordable method that uses easily available hardware and software and does not require significant computer knowledge. Pathology education can be enhanced by the implementation of digital video technology.

  6. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Hong Yi

    2008-01-01

    Full Text Available Abstract Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  7. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Yuchou Chang

    2008-02-01

    Full Text Available Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  8. Strain measurement by cardiovascular magnetic resonance in pediatric cancer survivors: validation of feature tracking against harmonic phase imaging

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Jimmy C. [C.S. Mott Children' s Hospital, University of Michigan Congenital Heart Center, Ann Arbor, MI (United States); University of Michigan, Department of Pediatrics and Communicable Diseases, Division of Pediatric Cardiology, Ann Arbor, MI (United States); University of Michigan, Department of Radiology, Section of Pediatric Radiology, Ann Arbor, MI (United States); Connelly, James A. [University of Michigan, Department of Pediatrics and Communicable Diseases, Division of Hematology-Oncology, Ann Arbor, MI (United States); Zhao, Lili [University of Michigan, Department of Biostatistics, Ann Arbor, MI (United States); Agarwal, Prachi P. [University of Michigan, Department of Radiology, Division of Cardiothoracic Radiology, Ann Arbor, MI (United States); Dorfman, Adam L. [University of Michigan, Department of Pediatrics and Communicable Diseases, Division of Pediatric Cardiology, Ann Arbor, MI (United States); University of Michigan, Department of Radiology, Section of Pediatric Radiology, Ann Arbor, MI (United States)

    2014-09-15

    Left ventricular strain may be a more sensitive marker of left ventricular dysfunction than ejection fraction in pediatric cancer survivors after anthracycline therapy, but there is limited validation of strain measurement by feature tracking on cardiovascular magnetic resonance (MR) images. To compare left ventricular circumferential and radial strain by feature tracking vs. harmonic phase imaging analysis (HARP) in pediatric cancer survivors. Twenty-six patients (20.2 ± 5.6 years old) underwent cardiovascular MR at least 5 years after completing anthracycline therapy. Circumferential and radial strain were measured at the base, midventricle and apex from short-axis myocardial tagged images by HARP, and from steady-state free precession images by feature tracking. Left ventricular ejection fraction more closely correlated with global circumferential strain by feature tracking (r = -0.63, P = 0.0005) than by HARP (r = -0.39, P = 0.05). Midventricular circumferential strain did not significantly differ by feature tracking or HARP (-20.8 ± 3.4 vs. -19.5 ± 2.5, P = 0.07), with acceptable limits of agreement. Midventricular circumferential strain by feature tracking strongly correlated with global circumferential strain by feature tracking (r = 0.87, P < 0.0001). Radial strain by feature tracking had poor agreement with HARP, particularly at higher values of radial strain. Intraobserver and interobserver reproducibility was excellent for feature tracking circumferential strain, but reproducibility was poor for feature tracking radial strain. Midventricular circumferential strain by feature tracking is a reliable and reproducible measure of myocardial deformation in patients status post anthracycline therapy, while radial strain measurements are unreliable. Further studies are necessary to evaluate potential relation to long-term outcomes. (orig.)

  9. 41 CFR 102-192.65 - What features must our finance systems have to keep track of mail costs?

    Science.gov (United States)

    2010-07-01

    ... What features must our finance systems have to keep track of mail costs? All agencies must have an... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What features must our finance systems have to keep track of mail costs? 102-192.65 Section 102-192.65 Public Contracts and...

  10. ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets.

    Directory of Open Access Journals (Sweden)

    Halfdan Rydbeck

    Full Text Available Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.

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

    Science.gov (United States)

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

    2011-05-01

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

  12. Extracting Road Features from Aerial Videos of Small Unmanned Aerial Vehicles

    Science.gov (United States)

    Rajamohan, D.; Rajan, K. S.

    2013-09-01

    With major aerospace companies showing interest in certifying UAV systems for civilian airspace, their use in commercial remote sensing applications like traffic monitoring, map refinement, agricultural data collection, etc., are on the rise. But ambitious requirements like real-time geo-referencing of data, support for multiple sensor angle-of-views, smaller UAV size and cheaper investment cost have lead to challenges in platform stability, sensor noise reduction and increased onboard processing. Especially in small UAVs the geo-referencing of data collected is only as good as the quality of their localization sensors. This drives a need for developing methods that pickup spatial features from the captured video/image and aid in geo-referencing. This paper presents one such method to identify road segments and intersections based on traffic flow and compares well with the accuracy of manual observation. Two test video datasets, one each from moving and stationary platforms were used. The results obtained show a promising average percentage difference of 7.01 % and 2.48 % for the road segment extraction process using moving and stationary platform respectively. For the intersection identification process, the moving platform shows an accuracy of 75 % where as the stationary platform data reaches an accuracy of 100 %.

  13. Motion tracking and gait feature estimation for recognising Parkinson’s disease using MS Kinect

    OpenAIRE

    Ondřej ŤUPA; Procházka, Aleš; Vyšata, Oldřich; Schätz, Martin; Mareš, Jan; Vališ, Martin; Mařík, Vladimír

    2015-01-01

    Background Analysis of gait features provides important information during the treatment of neurological disorders, including Parkinson’s disease. It is also used to observe the effects of medication and rehabilitation. The methodology presented in this paper enables the detection of selected gait attributes by Microsoft (MS) Kinect image and depth sensors to track movements in three-dimensional space. Methods The experimental part of the paper is devoted to the study of three sets of individ...

  14. Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

    Science.gov (United States)

    Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; van Huis, Jasper R.; Dijk, Judith; van Rest, Jeroen H. C.

    2014-10-01

    Proactive detection of incidents is required to decrease the cost of security incidents. This paper focusses on the automatic early detection of suspicious behavior of pickpockets with track-based features in a crowded shopping mall. Our method consists of several steps: pedestrian tracking, feature computation and pickpocket recognition. This is challenging because the environment is crowded, people move freely through areas which cannot be covered by a single camera, because the actual snatch is a subtle action, and because collaboration is complex social behavior. We carried out an experiment with more than 20 validated pickpocket incidents. We used a top-down approach to translate expert knowledge in features and rules, and a bottom-up approach to learn discriminating patterns with a classifier. The classifier was used to separate the pickpockets from normal passers-by who are shopping in the mall. We performed a cross validation to train and evaluate our system. In this paper, we describe our method, identify the most valuable features, and analyze the results that were obtained in the experiment. We estimate the quality of these features and the performance of automatic detection of (collaborating) pickpockets. The results show that many of the pickpockets can be detected at a low false alarm rate.

  15. Investigation on effectiveness of mid-level feature representation for semantic boundary detection in news video

    Science.gov (United States)

    Radhakrishan, Regunathan; Xiong, Ziyou; Divakaran, Ajay; Raj, Bhiksha

    2003-11-01

    In our past work, we have attempted to use a mid-level feature namely the state population histogram obtained from the Hidden Markov Model (HMM) of a general sound class, for speaker change detection so as to extract semantic boundaries in broadcast news. In this paper, we compare the performance of our previous approach with another approach based on video shot detection and speaker change detection using the Bayesian Information Criterion (BIC). Our experiments show that the latter approach performs significantly better than the former. This motivated us to examine the mid-level feature closely. We found that the component population histogram enabled discovery of broad phonetic categories such as vowels, nasals, fricatives etc, regardless of the number of distinct speakers in the test utterance. In order for it to be useful for speaker change detection, the individual components should model the phonetic sounds of each speaker separately. From our experiments, we conclude that state/component population histograms can only be useful for further clustering or semantic class discovery if the features are chosen carefully so that the individual states represent the semantic categories of interest.

  16. Clinical features and axis I comorbidity of Australian adolescent pathological Internet and video game users.

    Science.gov (United States)

    King, Daniel L; Delfabbro, Paul H; Zwaans, Tara; Kaptsis, Dean

    2013-11-01

    Although there is growing international recognition of pathological technology use (PTU) in adolescence, there has been a paucity of empirical research conducted in Australia. This study was designed to assess the clinical features of pathological video gaming (PVG) and pathological Internet use (PIU) in a normative Australian adolescent population. A secondary objective was to investigate the axis I comorbidities associated with PIU and video gaming. A total of 1287 South Australian secondary school students aged 12-18 years were recruited. Participants were assessed using the PTU checklist, Revised Children's Anxiety and Depression Scale, Social Anxiety Scale for Adolescents, revised UCLA Loneliness Scale, and Teenage Inventory of Social Skills. Adolescents who met the criteria for PVG or PIU or both were compared to normal adolescents in terms of axis I comorbidity. The prevalence rates of PIU and PVG were 6.4% and 1.8%, respectively. A subgroup with co-occurring PIU and PVG was identified (3.3%). The most distinguishing clinical features of PTU were withdrawal, tolerance, lies and secrecy, and conflict. Symptoms of preoccupation, inability to self-limit, and using technology as an escape were commonly reported by adolescents without PTU, and therefore may be less useful as clinical indicators. Depression, panic disorder, and separation anxiety were most prevalent among adolescents with PIU. PTU among Australian adolescents remains an issue warranting clinical concern. These results suggest an emerging trend towards the greater uptake and use of the Internet among female adolescents, with associated PIU. Although there exists an overlap of PTU disorders, adolescents with PIU appear to be at greater risk of axis I comorbidity than adolescents with PVG alone. Further research with an emphasis on validation techniques, such as verified identification of harm, may enable an informed consensus on the definition and diagnosis of PTU.

  17. Detection, tracking and event localization of jet stream features in 4-D atmospheric data

    Directory of Open Access Journals (Sweden)

    S. Limbach

    2012-04-01

    Full Text Available We introduce a novel algorithm for the efficient detection and tracking of features in spatiotemporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm works on data given on a four-dimensional structured grid. Feature selection and clustering are based on adjustable local and global criteria, feature tracking is predominantly based on spatial overlaps of the feature's full volumes. The resulting 3-D features and the identified correspondences between features of consecutive time steps are represented as the nodes and edges of a directed acyclic graph, the event graph. Merging and splitting events appear in the event graph as nodes with multiple incoming or outgoing edges, respectively. The precise localization of the splitting events is based on a search for all grid points inside the initial 3-D feature that have a similar distance to two successive 3-D features of the next time step. The merging event is localized analogously, operating backward in time. As a first application of our method we present a climatology of upper-tropospheric jet streams and their events, based on four-dimensional wind speed data from European Centre for Medium-Range Weather Forecasts (ECMWF analyses. We compare our results with a climatology from a previous study, investigate the statistical distribution of the merging and splitting events, and illustrate the meteorological significance of the jet splitting events with a case study. A brief outlook is given on additional potential applications of the 4-D data segmentation technique.

  18. 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…

  19. 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

  20. Human Body Parts Tracking and Kinematic Features Assessment Based on RSSI and Inertial Sensor Measurements

    Directory of Open Access Journals (Sweden)

    Gaddi Blumrosen

    2013-08-01

    Full Text Available Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI measurements in a Body Area Network (BAN, capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts’ displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs.

  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. 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

  3. 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.

  4. Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos

    NARCIS (Netherlands)

    Zivkovic, Z.; van der Heijden, Ferdinand; Petkovic, M.; Jonker, Willem; Langendijk, R.L.; Heijnsdijk, J.W.J.; Pimentel, A.D.; Wilkinson, M.H.F.

    This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed for real video data. Further, we introduce a number of novel

  5. Gaussian Process Regression-Based Video Anomaly Detection and Localization With Hierarchical Feature Representation.

    Science.gov (United States)

    Cheng, Kai-Wen; Chen, Yie-Tarng; Fang, Wen-Hsien

    2015-12-01

    This paper presents a hierarchical framework for detecting local and global anomalies via hierarchical feature representation and Gaussian process regression (GPR) which is fully non-parametric and robust to the noisy training data, and supports sparse features. While most research on anomaly detection has focused more on detecting local anomalies, we are more interested in global anomalies that involve multiple normal events interacting in an unusual manner, such as car accidents. To simultaneously detect local and global anomalies, we cast the extraction of normal interactions from the training videos as a problem of finding the frequent geometric relations of the nearby sparse spatio-temporal interest points (STIPs). A codebook of interaction templates is then constructed and modeled using the GPR, based on which a novel inference method for computing the likelihood of an observed interaction is also developed. Thereafter, these local likelihood scores are integrated into globally consistent anomaly masks, from which anomalies can be succinctly identified. To the best of our knowledge, it is the first time GPR is employed to model the relationship of the nearby STIPs for anomaly detection. Simulations based on four widespread datasets show that the new method outperforms the main state-of-the-art methods with lower computational burden.

  6. Feature Tracking and Visualization of Madden-Julian Osciallation in Climate Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Teng-Yok; Tong, Xin; Shen, Han-Wei; Wong, Pak C.; Hagos, Samson M.; Leung, Lai-Yung R.

    2013-06-20

    Madden-Julian Oscillation (MJO) is one of the less understood aspects of tropical meteorology, which plays a significant role in tropical intra-seasonal variations in rain, temperature and winds over the Indian and Pacific Oceans. In this paper, we present an integrated analysis and visualization framework for MJO episodes simulated by a high resolution regional model. To distinguish MJOs from other weather phenomena, our framework utilizes domain knowledge to track MJOs as finding the globally optimized properties in the data. In addition to enhancing the animation with feature tracking, our visualization system also integrates different visualization components such as Virtual Globe and Hovmoller Diagrams to visualize large scale events both in space and time. By linking all of these visualization components on a web-based interface, scientists can identify cloud and environmental processes associated with the initiation and eastward propagation of MJO more easily.

  7. Wireless capsule endoscopy video segmentation using an unsupervised learning approach based on probabilistic latent semantic analysis with scale invariant features.

    Science.gov (United States)

    Shen, Yao; Guturu, Parthasarathy Partha; Buckles, Bill P

    2012-01-01

    Since wireless capsule endoscopy (WCE) is a novel technology for recording the videos of the digestive tract of a patient, the problem of segmenting the WCE video of the digestive tract into subvideos corresponding to the entrance, stomach, small intestine, and large intestine regions is not well addressed in the literature. A selected few papers addressing this problem follow supervised leaning approaches that presume availability of a large database of correctly labeled training samples. Considering the difficulties in procuring sizable WCE training data sets needed for achieving high classification accuracy, we introduce in this paper an unsupervised learning approach that employs Scale Invariant Feature Transform (SIFT) for extraction of local image features and the probabilistic latent semantic analysis (pLSA) model used in the linguistic content analysis for data clustering. Results of experimentation indicate that this method compares well in classification accuracy with the state-of-the-art supervised classification approaches to WCE video segmentation.

  8. Classifier-based offline feature selection and evaluation for visual tracking of sea-surface and aerial targets

    Science.gov (United States)

    Çakır, Serdar; Aytaç, Tayfun; Yıldırım, Alper; Gerek, Ö. Nezih

    2011-10-01

    An offline feature selection and evaluation mechanism is used in order to develop a robust visual tracking scheme for sea-surface and aerial targets. The covariance descriptors, known to constitute an efficient signature set in object detection and classification problems, are used in the feature extraction phase of the proposed scheme. The performance of feature sets are compared using support vector machines, and those resulting in the highest detection performance are used in the covariance based tracker. The tracking performance is evaluated in different scenarios using different performance measures with respect to ground truth target positions. The proposed tracking scheme is observed to track sea-surface and aerial targets with plausible accuracies, and the results show that gradient-based features, together with the pixel locations and intensity values, provide robust target tracking in both surveillance scenarios. The performance of the proposed tracking strategy is also compared with some well-known trackers including correlation, Kanade-Lucas-Tomasi feature, and scale invariant feature transform-based trackers. Experimental results and observations show that the proposed target tracking scheme outperforms other trackers in both air and sea surveillance scenarios.

  9. 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

  10. Part-based Pedestrian Detection and Feature-based Tracking for Driver Assistance

    DEFF Research Database (Denmark)

    Prioletti, Antonio; Møgelmose, Andreas; Grislieri, Paolo

    2013-01-01

    Detecting pedestrians is still a challenging task for automotive vision systems due to the extreme variability of targets, lighting conditions, occlusion, and high-speed vehicle motion. Much research has been focused on this problem in the last ten years and detectors based on classifiers have...... on a prototype vehicle and offers high performance in terms of several metrics, such as detection rate, false positives per hour, and frame rate. The novelty of this system relies on the combination of a HOG part-based approach, tracking based on a specific optimized feature, and porting on a real prototype....

  11. RST-Resilient Video Watermarking Using Scene-Based Feature Extraction

    OpenAIRE

    Jung Han-Seung; Lee Young-Yoon; Lee Sang Uk

    2004-01-01

    Watermarking for video sequences should consider additional attacks, such as frame averaging, frame-rate change, frame shuffling or collusion attacks, as well as those of still images. Also, since video is a sequence of analogous images, video watermarking is subject to interframe collusion. In order to cope with these attacks, we propose a scene-based temporal watermarking algorithm. In each scene, segmented by scene-change detection schemes, a watermark is embedded temporally to one-dimens...

  12. The Effect of Typographical Features of Subtitles on Nonnative English Viewers’ Retention and Recall of Lyrics in English Music Videos

    OpenAIRE

    Farshid Tayari Ashtiani

    2017-01-01

    The goal of this study was to test the effect of typographical features of subtitles including size, color and position on nonnative English viewers’ retention and recall of lyrics in music videos. To do so, the researcher played a simple subtitled music video for the participants at the beginning of their classes, and administered a 31-blank cloze test from the lyrics at the end of the classes. In the second test, the control group went through the same procedure but experimental group watch...

  13. Identification and tracking of vertebrae in ultrasound using deep networks with unsupervised feature learning

    Science.gov (United States)

    Hetherington, Jorden; Pesteie, Mehran; Lessoway, Victoria A.; Abolmaesumi, Purang; Rohling, Robert N.

    2017-03-01

    Percutaneous needle insertion procedures on the spine often require proper identification of the vertebral level in order to effectively deliver anesthetics and analgesic agents to achieve adequate block. For example, in obstetric epidurals, the target is at the L3-L4 intervertebral space. The current clinical method involves "blind" identification of the vertebral level through manual palpation of the spine, which has only 30% accuracy. This implies the need for better anatomical identification prior to needle insertion. A system is proposed to identify the vertebrae, assigning them to their respective levels, and track them in a standard sequence of ultrasound images, when imaged in the paramedian plane. Machine learning techniques are developed to identify discriminative features of the laminae. In particular, a deep network is trained to automatically learn the anatomical features of the lamina peaks, and classify image patches, for pixel-level classification. The chosen network utilizes multiple connected auto-encoders to learn the anatomy. Pre-processing with ultrasound bone enhancement techniques is done to aid the pixel-level classification performance. Once the lamina are identified, vertebrae are assigned levels and tracked in sequential frames. Experimental results were evaluated against an expert sonographer. Based on data acquired from 15 subjects, vertebrae identification with sensitivity of 95% and precision of 95% was achieved within each frame. Between pairs of subsequently analyzed frames, matches of predicted vertebral level labels were correct in 94% of cases, when compared to matches of manually selected labels

  14. 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.

  15. Human Amygdala Tracks a Feature-Based Valence Signal Embedded within the Facial Expression of Surprise.

    Science.gov (United States)

    Kim, M Justin; Mattek, Alison M; Bennett, Randi H; Solomon, Kimberly M; Shin, Jin; Whalen, Paul J

    2017-09-27

    Human amygdala function has been traditionally associated with processing the affective valence (negative vs positive) of an emotionally charged event, especially those that signal fear or threat. However, this account of human amygdala function can be explained by alternative views, which posit that the amygdala might be tuned to either (1) general emotional arousal (activation vs deactivation) or (2) specific emotion categories (fear vs happy). Delineating the pure effects of valence independent of arousal or emotion category is a challenging task, given that these variables naturally covary under many circumstances. To circumvent this issue and test the sensitivity of the human amygdala to valence values specifically, we measured the dimension of valence within the single facial expression category of surprise. Given the inherent valence ambiguity of this category, we show that surprised expression exemplars are attributed valence and arousal values that are uniquely and naturally uncorrelated. We then present fMRI data from both sexes, showing that the amygdala tracks these consensus valence values. Finally, we provide evidence that these valence values are linked to specific visual features of the mouth region, isolating the signal by which the amygdala detects this valence information. SIGNIFICANCE STATEMENT There is an open question as to whether human amygdala function tracks the valence value of cues in the environment, as opposed to either a more general emotional arousal value or a more specific emotion category distinction. Here, we demonstrate the utility of surprised facial expressions because exemplars within this emotion category take on valence values spanning the dimension of bipolar valence (positive to negative) at a consistent level of emotional arousal. Functional neuroimaging data showed that amygdala responses tracked the valence of surprised facial expressions, unconfounded by arousal. Furthermore, a machine learning classifier identified

  16. 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…

  17. Context-specific selection of algorithms for recursive feature tracking in endoscopic image using a new methodology.

    Science.gov (United States)

    Selka, F; Nicolau, S; Agnus, V; Bessaid, A; Marescaux, J; Soler, L

    2015-03-01

    In minimally invasive surgery, the tracking of deformable tissue is a critical component for image-guided applications. Deformation of the tissue can be recovered by tracking features using tissue surface information (texture, color,...). Recent work in this field has shown success in acquiring tissue motion. However, the performance evaluation of detection and tracking algorithms on such images are still difficult and are not standardized. This is mainly due to the lack of ground truth data on real data. Moreover, in order to avoid supplementary techniques to remove outliers, no quantitative work has been undertaken to evaluate the benefit of a pre-process based on image filtering, which can improve feature tracking robustness. In this paper, we propose a methodology to validate detection and feature tracking algorithms, using a trick based on forward-backward tracking that provides an artificial ground truth data. We describe a clear and complete methodology to evaluate and compare different detection and tracking algorithms. In addition, we extend our framework to propose a strategy to identify the best combinations from a set of detector, tracker and pre-process algorithms, according to the live intra-operative data. Experimental results have been performed on in vivo datasets and show that pre-process can have a strong influence on tracking performance and that our strategy to find the best combinations is relevant for a reasonable computation cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    Physical exercise may result in muscle tiredness which is known as muscle fatigue. This occurs when the muscles cannot exert normal force, or when more than normal effort is required. Fatigue is a vital sign, for example, for therapists to assess their patient’s progress or to change...... their exercises when the level of the fatigue might be dangerous for the patients. The current technology for measuring tiredness, like Electromyography (EMG), requires installing some sensors on the body. In some applications, like remote patient monitoring, this however might not be possible. To deal...... that the proposed system can properly find the temporal point of tiredness of the muscles when the test subjects are doing physical exercises....

  19. 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.

  20. WE-D-BRF-01: FEATURED PRESENTATION - Investigating Particle Track Structures Using Fluorescent Nuclear Track Detectors and Monte Carlo Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Dowdell, S; Paganetti, H; Schuemann, J [Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Greilich, S [Division of Medical Physics in Radiation Oncology, DKFZ - German Cancer Research Center, Heidelberg (Germany); Zimmerman, F [Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Division of Medical Physics in Radiation Oncology, DKFZ - German Cancer Research Center, Heidelberg (Germany); Evans, C [Wellman Center for Photomedicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2014-06-15

    Purpose: To report on the efforts funded by the AAPM seed funding grant to develop the basis for fluorescent nuclear track detector (FNTD) based radiobiological experiments in combination with dedicated Monte Carlo simulations (MCS) on the nanometer scale. Methods: Two confocal microscopes were utilized in this study. Two FNTD samples were used to find the optimal microscope settings, one FNTD irradiated with 11.1 MeV/u Gold ions and one irradiated with 428.77 MeV/u Carbon ions. The first sample provided a brightly luminescent central track while the latter is used to test the capabilities to observe secondary electrons. MCS were performed using TOPAS beta9 version, layered on top of Geant4.9.6p02. Two sets of simulations were performed, one with the Geant4-DNA physics list and approximating the FNTDs by water, a second set using the Penelope physics list in a water-approximated FNTD and a aluminum-oxide FNTD. Results: Within the first half of the funding period, we have successfully established readout capabilities of FNTDs at our institute. Due to technical limitations, our microscope setup is significantly different from the approach implemented at the DKFZ, Germany. However, we can clearly reconstruct Carbon tracks in 3D with electron track resolution of 200 nm. A second microscope with superior readout capabilities will be tested in the second half of the funding period, we expect an improvement in signal to background ratio with the same the resolution.We have successfully simulated tracks in FNTDs. The more accurate Geant4-DNA track simulations can be used to reconstruct the track energy from the size and brightness of the observed tracks. Conclusion: We have achieved the goals set in the seed funding proposal: the setup of FNTD readout and simulation capabilities. We will work on improving the readout resolution to validate our MCS track structures down to the nanometer scales.

  1. Fast Mode Decision in the HEVC Video Coding Standard by Exploiting Region with Dominated Motion and Saliency Features.

    Science.gov (United States)

    Podder, Pallab Kanti; Paul, Manoranjan; Murshed, Manzur

    2016-01-01

    The emerging High Efficiency Video Coding (HEVC) standard introduces a number of innovative and powerful coding tools to acquire better compression efficiency compared to its predecessor H.264. The encoding time complexities have also increased multiple times that is not suitable for realtime video coding applications. To address this limitation, this paper employs a novel coding strategy to reduce the time complexity in HEVC encoder by efficient selection of appropriate block-partitioning modes based on human visual features (HVF). The HVF in the proposed technique comprise with human visual attention modelling-based saliency feature and phase correlation-based motion features. The features are innovatively combined through a fusion process by developing a content-based adaptive weighted cost function to determine the region with dominated motion/saliency (RDMS)- based binary pattern for the current block. The generated binary pattern is then compared with a codebook of predefined binary pattern templates aligned to the HEVC recommended block-paritioning to estimate a subset of inter-prediction modes. Without exhaustive exploration of all modes available in the HEVC standard, only the selected subset of modes are motion estimated and motion compensated for a particular coding unit. The experimental evaluation reveals that the proposed technique notably down-scales the average computational time of the latest HEVC reference encoder by 34% while providing similar rate-distortion (RD) performance for a wide range of video sequences.

  2. 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...

  3. 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.

  4. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features.

    Science.gov (United States)

    Billah, Mustain; Waheed, Sajjad; Rahman, Mohammad Motiur

    2017-01-01

    Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM). Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.

  5. High-quality and small-capacity e-learning video featuring lecturer-superimposing PC screen images

    Science.gov (United States)

    Nomura, Yoshihiko; Murakami, Michinobu; Sakamoto, Ryota; Sugiura, Tokuhiro; Matsui, Hirokazu; Kato, Norihiko

    2006-10-01

    Information processing and communication technology are progressing quickly, and are prevailing throughout various technological fields. Therefore, the development of such technology should respond to the needs for improvement of quality in the e-learning education system. The authors propose a new video-image compression processing system that ingeniously employs the features of the lecturing scene. While dynamic lecturing scene is shot by a digital video camera, screen images are electronically stored by a PC screen image capturing software in relatively long period at a practical class. Then, a lecturer and a lecture stick are extracted from the digital video images by pattern recognition techniques, and the extracted images are superimposed on the appropriate PC screen images by off-line processing. Thus, we have succeeded to create a high-quality and small-capacity (HQ/SC) video-on-demand educational content featuring the advantages: the high quality of image sharpness, the small electronic file capacity, and the realistic lecturer motion.

  6. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features

    Science.gov (United States)

    Waheed, Sajjad; Rahman, Mohammad Motiur

    2017-01-01

    Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM). Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%. PMID:28894460

  7. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features

    Directory of Open Access Journals (Sweden)

    Mustain Billah

    2017-01-01

    Full Text Available Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW features and convolutional neural network (CNN features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM. Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.

  8. Motion Entropy Feature and Its Applications to Event-Based Segmentation of Sports Video

    Science.gov (United States)

    Chen, Chen-Yu; Wang, Jia-Ching; Wang, Jhing-Fa; Hu, Yu-Hen

    2008-12-01

    An entropy-based criterion is proposed to characterize the pattern and intensity of object motion in a video sequence as a function of time. By applying a homoscedastic error model-based time series change point detection algorithm to this motion entropy curve, one is able to segment the corresponding video sequence into individual sections, each consisting of a semantically relevant event. The proposed method is tested on six hours of sports videos including basketball, soccer, and tennis. Excellent experimental results are observed.

  9. Proposed patient motion monitoring system using feature point tracking with a web camera.

    Science.gov (United States)

    Miura, Hideharu; Ozawa, Shuichi; Matsuura, Takaaki; Yamada, Kiyoshi; Nagata, Yasushi

    2017-12-01

    Patient motion monitoring systems play an important role in providing accurate treatment dose delivery. We propose a system that utilizes a web camera (frame rate up to 30 fps, maximum resolution of 640 × 480 pixels) and an in-house image processing software (developed using Microsoft Visual C++ and OpenCV). This system is simple to use and convenient to set up. The pyramidal Lucas-Kanade method was applied to calculate motions for each feature point by analysing two consecutive frames. The image processing software employs a color scheme where the defined feature points are blue under stable (no movement) conditions and turn red along with a warning message and an audio signal (beeping alarm) for large patient movements. The initial position of the marker was used by the program to determine the marker positions in all the frames. The software generates a text file that contains the calculated motion for each frame and saves it as a compressed audio video interleave (AVI) file. We proposed a patient motion monitoring system using a web camera, which is simple and convenient to set up, to increase the safety of treatment delivery.

  10. Multivariate EEG analyses support high-resolution tracking of feature-based attentional selection.

    Science.gov (United States)

    Fahrenfort, Johannes Jacobus; Grubert, Anna; Olivers, Christian N L; Eimer, Martin

    2017-05-15

    The primary electrophysiological marker of feature-based selection is the N2pc, a lateralized posterior negativity emerging around 180-200 ms. As it relies on hemispheric differences, its ability to discriminate the locus of focal attention is severely limited. Here we demonstrate that multivariate analyses of raw EEG data provide a much more fine-grained spatial profile of feature-based target selection. When training a pattern classifier to determine target position from EEG, we were able to decode target positions on the vertical midline, which cannot be achieved using standard N2pc methodology. Next, we used a forward encoding model to construct a channel tuning function that describes the continuous relationship between target position and multivariate EEG in an eight-position display. This model can spatially discriminate individual target positions in these displays and is fully invertible, enabling us to construct hypothetical topographic activation maps for target positions that were never used. When tested against the real pattern of neural activity obtained from a different group of subjects, the constructed maps from the forward model turned out statistically indistinguishable, thus providing independent validation of our model. Our findings demonstrate the power of multivariate EEG analysis to track feature-based target selection with high spatial and temporal precision.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. Registration Combining Wide and Narrow Baseline Feature Tracking Techniques for Markerless AR Systems

    Directory of Open Access Journals (Sweden)

    Bo Yang

    2009-12-01

    Full Text Available Augmented reality (AR is a field of computer research which deals with the combination of real world and computer generated data. Registration is one of the most difficult problems currently limiting the usability of AR systems. In this paper, we propose a novel natural feature tracking based registration method for AR applications. The proposed method has following advantages: (1 it is simple and efficient, as no man-made markers are needed for both indoor and outdoor AR applications; moreover, it can work with arbitrary geometric shapes including planar, near planar and non planar structures which really enhance the usability of AR systems. (2 Thanks to the reduced SIFT based augmented optical flow tracker, the virtual scene can still be augmented on the specified areas even under the circumstances of occlusion and large changes in viewpoint during the entire process. (3 It is easy to use, because the adaptive classification tree based matching strategy can give us fast and accurate initialization, even when the initial camera is different from the reference image to a large degree. Experimental evaluations validate the performance of the proposed method for online pose tracking and augmentation.

  16. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction

    National Research Council Canada - National Science Library

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    .... Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer...

  17. Online evaluation of tracking algorithm performance

    OpenAIRE

    Chau, Duc Phu; Bremond, François; Thonnat, Monique

    2009-01-01

    In the 3rd International Conference on Imaging for Crime Detection and Prevention 2009 (ICDP), Kingston University, London, UK; International audience; This paper presents a method to evaluate online the performance of tracking algorithms in surveillance videos. We use a set of features to compute the confidence of trajectories and also the precision of tracking results. A global score is computed online based on these features and is used to estimate the performance of tracking algorithms. T...

  18. 6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.

    Science.gov (United States)

    Ye, Cang; Hong, Soonhac; Tamjidi, Amirhossein

    2015-10-01

    This paper presents a 6-DOF Pose Estimation (PE) method for a Robotic Navigation Aid (RNA) for the visually impaired. The RNA uses a single 3D camera for PE and object detection. The proposed method processes the camera's intensity and range data to estimates the camera's egomotion that is then used by an Extended Kalman Filter (EKF) as the motion model to track a set of visual features for PE. A RANSAC process is employed in the EKF to identify inliers from the visual feature correspondences between two image frames. Only the inliers are used to update the EKF's state. The EKF integrates the egomotion into the camera's pose in the world coordinate system. To retain the EKF's consistency, the distance between the camera and the floor plane (extracted from the range data) is used by the EKF as the observation of the camera's z coordinate. Experimental results demonstrate that the proposed method results in accurate pose estimates for positioning the RNA in indoor environments. Based on the PE method, a wayfinding system is developed for localization of the RNA in a home environment. The system uses the estimated pose and the floorplan to locate the RNA user in the home environment and announces the points of interest and navigational commands to the user through a speech interface. This work was motivated by the limitations of the existing navigation technology for the visually impaired. Most of the existing methods use a point/line measurement sensor for indoor object detection. Therefore, they lack capability in detecting 3D objects and positioning a blind traveler. Stereovision has been used in recent research. However, it cannot provide reliable depth data for object detection. Also, it tends to produce a lower localization accuracy because its depth measurement error quadratically increases with the true distance. This paper suggests a new approach for navigating a blind traveler. The method uses a single 3D time-of-flight camera for both 6-DOF PE and 3D object

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

    Directory of Open Access Journals (Sweden)

    Christophe Bobda

    2006-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Mühlbauer Felix

    2006-01-01

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

  1. 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...

  2. A GPU-Accelerated Approach for Feature Tracking in Time-Varying Imagery Datasets.

    Science.gov (United States)

    Peng, Chao; Sahani, Sandip; Rushing, John

    2017-10-01

    We propose a novel parallel connected component labeling (CCL) algorithm along with efficient out-of-core data management to detect and track feature regions of large time-varying imagery datasets. Our approach contributes to the big data field with parallel algorithms tailored for GPU architectures. We remove the data dependency between frames and achieve pixel-level parallelism. Due to the large size, the entire dataset cannot fit into cached memory. Frames have to be streamed through the memory hierarchy (disk to CPU main memory and then to GPU memory), partitioned, and processed as batches, where each batch is small enough to fit into the GPU. To reconnect the feature regions that are separated due to data partitioning, we present a novel batch merging algorithm to extract the region connection information across multiple batches in a parallel fashion. The information is organized in a memory-efficient structure and supports fast indexing on the GPU. Our experiment uses a commodity workstation equipped with a single GPU. The results show that our approach can efficiently process a weather dataset composed of terabytes of time-varying radar images. The advantages of our approach are demonstrated by comparing to the performance of an efficient CPU cluster implementation which is being used by the weather scientists.

  3. The Effect of Typographical Features of Subtitles on Nonnative English Viewers’ Retention and Recall of Lyrics in English Music Videos

    Directory of Open Access Journals (Sweden)

    Farshid Tayari Ashtiani

    2017-10-01

    Full Text Available The goal of this study was to test the effect of typographical features of subtitles including size, color and position on nonnative English viewers’ retention and recall of lyrics in music videos. To do so, the researcher played a simple subtitled music video for the participants at the beginning of their classes, and administered a 31-blank cloze test from the lyrics at the end of the classes. In the second test, the control group went through the same procedure but experimental group watched the customized subtitled version of the music video. The results demonstrated no significant difference between the two groups in the first test but in the second, the scores remarkably increased in the experimental group and proved better retention and recall. This study has implications for English language teachers and material developers to benefit customized bimodal subtitles as a mnemonic tool for better comprehension, retention and recall of aural contents in videos via Computer Assisted Language Teaching approach.

  4. 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.

  5. Word2VisualVec: Image and Video to Sentence Matching by Visual Feature Prediction

    OpenAIRE

    Dong, Jianfeng; Li, Xirong; Snoek, Cees G. M.

    2016-01-01

    This paper strives to find the sentence best describing the content of an image or video. Different from existing works, which rely on a joint subspace for image / video to sentence matching, we propose to do so in a visual space only. We contribute Word2VisualVec, a deep neural network architecture that learns to predict a deep visual encoding of textual input based on sentence vectorization and a multi-layer perceptron. We thoroughly analyze its architectural design, by varying the sentence...

  6. 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.

  7. Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

    Directory of Open Access Journals (Sweden)

    Heng Yao

    2017-12-01

    Full Text Available Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs and the skip macroblocks (S-MBs for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.

  8. Repurposing Video Documentaries as Features of a Flipped-Classroom Approach to Community-Centered Development

    Science.gov (United States)

    Arbogast, Douglas; Eades, Daniel; Plein, L. Christopher

    2017-01-01

    Online and off-site educational programming is increasingly incorporated by Extension educators to reach their clientele. Models such as the flipped classroom combine online content and in-person learning, allowing clients to both gain information and build peer learning communities. We demonstrate how video documentaries used in traditional…

  9. Quantification of global myocardial function by cine MRI deformable registration-based analysis: Comparison with MR feature tracking and speckle-tracking echocardiography.

    Science.gov (United States)

    Lamacie, Mariana M; Thavendiranathan, Paaladinesh; Hanneman, Kate; Greiser, Andreas; Jolly, Marie-Pierre; Ward, Richard; Wintersperger, Bernd J

    2017-04-01

    To evaluate deformable registration algorithms (DRA)-based quantification of cine steady-state free-precession (SSFP) for myocardial strain assessment in comparison with feature-tracking (FT) and speckle-tracking echocardiography (STE). Data sets of 28 patients/10 volunteers, undergoing same-day 1.5T cardiac MRI and echocardiography were included. LV global longitudinal (GLS), circumferential (GCS) and radial (GRS) peak systolic strain were assessed on cine SSFP data using commercially available FT algorithms and prototype DRA-based algorithms. STE was applied as standard of reference for accuracy, precision and intra-/interobserver reproducibility testing. DRA showed narrower limits of agreement compared to STE for GLS (-4.0 [-0.9,-7.9]) and GCS (-5.1 [1.1,-11.2]) than FT (3.2 [11.2,-4.9]; 3.8 [13.9,-6.3], respectively). While both DRA and FT demonstrated significant differences to STE for GLS and GCS (all pcine MRI. • Inverse DRA demonstrated superior reproducibility compared to feature-tracking (FT) methods. • Cine MR DRA and FT analysis demonstrate differences to speckle-tracking echocardiography • DRA demonstrated better correlation with STE than FT for MR-derived global strain data.

  10. 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.

  11. Robust Real-Time Gradient-based Eye Detection and Tracking Using Transform Domain and PSO-Based Feature Selection

    OpenAIRE

    Salehi, Nasrin.

    2017-01-01

    Despite numerous research on eye detection and tracking, this field of study remains challenging due to the individuality of eyes, occlusion, and variability in scale, location, and light conditions. This paper combines a techniques of feature extraction and a feature selection method to achieve a significant increase in eye recognition. Subspace methods may improve detection efficiency and accuracy of eye centers detection using dimensionality reduction. In this study, HoG descriptor is used...

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

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. Proliferative and necrotising otitis externa in a cat without pinnal involvement: video-otoscopic features.

    Science.gov (United States)

    Borio, Stefano; Massari, Federico; Abramo, Francesca; Colombo, Silvia

    2013-04-01

    Proliferative and necrotising otitis externa is a rare and recently described disease affecting the ear canals and concave pinnae of kittens. This article describes a case of proliferative and necrotising otits externa in a young adult cat. In this case, the lesions did not affected the pinnae, but both ear canals were severely involved. Video-otoscopy revealed a digitally proliferative lesion, growing at 360° all around the ear canals for their entire length, without involvement of the middle ear. Histopathological examination confirmed the diagnosis, and the cat responded completely to a once-daily application of 0.1% tacrolimus ointment diluted in mineral oil in the ear canals. Video-otoscopy findings, not described previously, were very peculiar and may help clinicians to diagnose this rare disease.

  15. Using Extracted Behavioral Features to Improve Privacy for Shared Route Tracks

    DEFF Research Database (Denmark)

    Andersen, Mads Schaarup; Kjærgaard, Mikkel Baun; Grønbæk, Kaj

    2012-01-01

    Track-based services, such as road pricing, usage-based insurance, and sports trackers, require users to share entire tracks of locations, however this may seriously violate users’ privacy. Existing privacy methods suffer from the fact that they degrade service quality when adding privacy...... and implementing TracM, a track-based community service for runners to share and compare their running performance. We show how such a service can be implemented by substituting location tracks with less privacy invasive behavioral data. Furthermore, we discuss the lessons learned from building TracM and discuss....... In this paper, we present the concept of privacy by substitution that addresses the problem without degrading service quality by substituting location tracks with less privacy invasive behavioral data extracted from raw tracks of location data or other sensing data. We explore this concept by designing...

  16. Feature tracking for automated volume of interest stabilization on 4D-OCT images

    Science.gov (United States)

    Laves, Max-Heinrich; Schoob, Andreas; Kahrs, Lüder A.; Pfeiffer, Tom; Huber, Robert; Ortmaier, Tobias

    2017-03-01

    A common representation of volumetric medical image data is the triplanar view (TV), in which the surgeon manually selects slices showing the anatomical structure of interest. In addition to common medical imaging such as MRI or computed tomography, recent advances in the field of optical coherence tomography (OCT) have enabled live processing and volumetric rendering of four-dimensional images of the human body. Due to the region of interest undergoing motion, it is challenging for the surgeon to simultaneously keep track of an object by continuously adjusting the TV to desired slices. To select these slices in subsequent frames automatically, it is necessary to track movements of the volume of interest (VOI). This has not been addressed with respect to 4DOCT images yet. Therefore, this paper evaluates motion tracking by applying state-of-the-art tracking schemes on maximum intensity projections (MIP) of 4D-OCT images. Estimated VOI location is used to conveniently show corresponding slices and to improve the MIPs by calculating thin-slab MIPs. Tracking performances are evaluated on an in-vivo sequence of human skin, captured at 26 volumes per second. Among investigated tracking schemes, our recently presented tracking scheme for soft tissue motion provides highest accuracy with an error of under 2.2 voxels for the first 80 volumes. Object tracking on 4D-OCT images enables its use for sub-epithelial tracking of microvessels for image-guidance.

  17. 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.

  18. 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.

  19. Feature-tracking myocardial strain analysis in acute myocarditis. Diagnostic value and association with myocardial oedema

    Energy Technology Data Exchange (ETDEWEB)

    Luetkens, Julian A.; Schlesinger-Irsch, Ulrike; Kuetting, Daniel L.; Dabir, Darius; Homsi, Rami; Schmeel, Frederic C.; Sprinkart, Alois M.; Naehle, Claas P.; Schild, Hans H.; Thomas, Daniel [University of Bonn, Department of Radiology, Bonn (Germany); Doerner, Jonas [University Hospital Cologne, Department of Radiology, Cologne (Germany); Fimmers, Rolf [University of Bonn, Department of Medical Biometry, Informatics, and Epidemiology, Bonn (Germany)

    2017-11-15

    To investigate the diagnostic value of cardiac magnetic resonance (CMR) feature-tracking (FT) myocardial strain analysis in patients with suspected acute myocarditis and its association with myocardial oedema. Forty-eight patients with suspected acute myocarditis and 35 control subjects underwent CMR. FT CMR analysis of systolic longitudinal (LS), circumferential (CS) and radial strain (RS) was performed. Additionally, the protocol allowed for the assessment of T1 and T2 relaxation times. When compared with healthy controls, myocarditis patients demonstrated reduced LS, CS and RS values (LS: -19.5 ± 4.4% vs. -23.6 ± 3.1%, CS: -23.0 ± 5.8% vs. -27.4 ± 3.4%, RS: 28.9 ± 8.5% vs. 32.4 ± 7.4%; P < 0.05, respectively). LS (T1: r = 0.462, P < 0.001; T2: r = 0.436, P < 0.001) and CS (T1: r = 0.429, P < 0.001; T2: r = 0.467, P < 0.001) showed the strongest correlations with T1 and T2 relaxations times. Area under the curve of LS (0.79) was higher compared with those of CS (0.75; P = 0.478) and RS (0.62; P = 0.008). FT CMR myocardial strain analysis might serve as a new tool for assessment of myocardial dysfunction in the diagnostic work-up of patients suspected of having acute myocarditis. Especially, LS and CS show a sufficient diagnostic performance and were most closely correlated with CMR parameters of myocardial oedema. (orig.)

  20. Feature-tracking myocardial strain analysis in acute myocarditis: diagnostic value and association with myocardial oedema.

    Science.gov (United States)

    Luetkens, Julian A; Schlesinger-Irsch, Ulrike; Kuetting, Daniel L; Dabir, Darius; Homsi, Rami; Doerner, Jonas; Schmeel, Frederic C; Fimmers, Rolf; Sprinkart, Alois M; Naehle, Claas P; Schild, Hans H; Thomas, Daniel

    2017-05-12

    To investigate the diagnostic value of cardiac magnetic resonance (CMR) feature-tracking (FT) myocardial strain analysis in patients with suspected acute myocarditis and its association with myocardial oedema. Forty-eight patients with suspected acute myocarditis and 35 control subjects underwent CMR. FT CMR analysis of systolic longitudinal (LS), circumferential (CS) and radial strain (RS) was performed. Additionally, the protocol allowed for the assessment of T1 and T2 relaxation times. When compared with healthy controls, myocarditis patients demonstrated reduced LS, CS and RS values (LS: -19.5 ± 4.4% vs. -23.6 ± 3.1%, CS: -23.0 ± 5.8% vs. -27.4 ± 3.4%, RS: 28.9 ± 8.5% vs. 32.4 ± 7.4%; P T1: r = 0.462, P T1: r = 0.429, P T1 and T2 relaxations times. Area under the curve of LS (0.79) was higher compared with those of CS (0.75; P = 0.478) and RS (0.62; P = 0.008). FT CMR myocardial strain analysis might serve as a new tool for assessment of myocardial dysfunction in the diagnostic work-up of patients suspected of having acute myocarditis. Especially, LS and CS show a sufficient diagnostic performance and were most closely correlated with CMR parameters of myocardial oedema. • Myocardial strain measures are considerably reduced in patients with suspected myocarditis. • Myocardial strain measures can sufficiently discriminate between diseased and healthy patients. • Myocardial strain measures show basic associations with the extent of myocardial oedema/inflammation.

  1. Myocardial feature tracking reduces observer-dependence in low-dose dobutamine stress cardiovascular magnetic resonance.

    Directory of Open Access Journals (Sweden)

    Andreas Schuster

    Full Text Available To determine whether quantitative wall motion assessment by CMR myocardial feature tracking (CMR-FT would reduce the impact of observer experience as compared to visual analysis in patients with ischemic cardiomyopathy (ICM.15 consecutive patients with ICM referred for assessment of hibernating myocardium were studied at 3 Tesla using SSFP cine images at rest and during low dose dobutamine stress (5 and 10 μg/kg/min of dobutamine. Conventional visual, qualitative analysis was performed independently and blinded by an experienced and an inexperienced reader, followed by post-processing of the same images by CMR-FT to quantify subendocardial and subepicardial circumferential (Eccendo and Eccepi and radial (Err strain. Receiver operator characteristics (ROC were assessed for each strain parameter and operator to detect the presence of inotropic reserve as visually defined by the experienced observer.141 segments with wall motion abnormalities at rest were eligible for the analysis. Visual scoring of wall motion at rest and during dobutamine was significantly different between the experienced and the inexperienced observer (p0.05. Eccendo was the most accurate (AUC of 0.76, 10 μg/kg/min of dobutamine parameter. Diagnostic accuracy was worse for resting strain with differences between operators for Eccendo and Eccepi (p0.05.Whilst visual analysis remains highly dependent on operator experience, quantitative CMR-FT analysis of myocardial wall mechanics during DS-CMR provides diagnostic accuracy for the detection of inotropic reserve regardless of operator experience and hence may improve diagnostic robustness of low-dose DS-CMR in clinical practice.

  2. Can interface features affect aggression resulting from violent video game play? An examination of realistic controller and large screen size.

    Science.gov (United States)

    Kim, Ki Joon; Sundar, S Shyam

    2013-05-01

    Aggressiveness attributed to violent video game play is typically studied as a function of the content features of the game. However, can interface features of the game also affect aggression? Guided by the General Aggression Model (GAM), we examine the controller type (gun replica vs. mouse) and screen size (large vs. small) as key technological aspects that may affect the state aggression of gamers, with spatial presence and arousal as potential mediators. Results from a between-subjects experiment showed that a realistic controller and a large screen display induced greater aggression, presence, and arousal than a conventional mouse and a small screen display, respectively, and confirmed that trait aggression was a significant predictor of gamers' state aggression. Contrary to GAM, however, arousal showed no effects on aggression; instead, presence emerged as a significant mediator.

  3. Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

    Science.gov (United States)

    Lorenz, David A.; Olds, Ryan; May, Alexander; Mario, Courtney; Perry, Mark E.; Palmer, Eric E.; Daly, Michael

    2017-01-01

    The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development

  4. 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

  5. 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...

  6. 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.

  7. Quantification of Left Ventricular Torsion and Diastolic Recoil Using Cardiovascular Magnetic Resonance Myocardial Feature Tracking

    Science.gov (United States)

    Hussain, Shazia T.; Kutty, Shelby; Steinmetz, Michael; Sohns, Jan M.; Fasshauer, Martin; Staab, Wieland; Unterberg-Buchwald, Christina; Bigalke, Boris; Lotz, Joachim; Hasenfuß, Gerd; Schuster, Andreas

    2014-01-01

    Objectives Cardiovascular magnetic resonance feature tracking (CMR-FT) offers quantification of myocardial deformation from routine cine images. However, data using CMR-FT to quantify left ventricular (LV) torsion and diastolic recoil are not yet available. We therefore sought to evaluate the feasibility and reproducibility of CMR-FT to quantify LV torsion and peak recoil rate using an optimal anatomical approach. Methods Short-axis cine stacks were acquired at rest and during dobutamine stimulation (10 and 20 µg·kg−1·min−1) in 10 healthy volunteers. Rotational displacement was analysed for all slices. A complete 3D-LV rotational model was developed using linear interpolation between adjacent slices. Torsion was defined as the difference between apical and basal rotation, divided by slice distance. Depending on the distance between the most apical (defined as 0% LV distance) and basal (defined as 100% LV distance) slices, four different models for the calculation of torsion were examined: Model-1 (25–75%), Model-2 (0–100%), Model-3 (25–100%) and Model-4 (0–75%). Analysis included subendocardial, subepicardial and global torsion and recoil rate (mean of subendocardial and subepicardial values). Results Quantification of torsion and recoil rate was feasible in all subjects. There was no significant difference between the different models at rest. However, only Model-1 (25–75%) discriminated between rest and stress (Global Torsion: 2.7±1.5°cm−1, 3.6±2.0°cm−1, 5.1±2.2°cm−1, p<0.01; Global Recoil Rate: −30.1±11.1°cm−1s−1,−46.9±15.0°cm−1s−1,−68.9±32.3°cm−1s−1, p<0.01; for rest, 10 and 20 µg·kg−1·min−1 of dobutamine, respectively). Reproducibility was sufficient for all parameters as determined by Bland-Altman analysis, intraclass correlation coefficients and coefficient of variation. Conclusions CMR-FT based derivation of myocardial torsion and recoil rate is feasible and reproducible at rest and with dobutamine

  8. Quantification of left ventricular torsion and diastolic recoil using cardiovascular magnetic resonance myocardial feature tracking.

    Directory of Open Access Journals (Sweden)

    Johannes T Kowallick

    Full Text Available Cardiovascular magnetic resonance feature tracking (CMR-FT offers quantification of myocardial deformation from routine cine images. However, data using CMR-FT to quantify left ventricular (LV torsion and diastolic recoil are not yet available. We therefore sought to evaluate the feasibility and reproducibility of CMR-FT to quantify LV torsion and peak recoil rate using an optimal anatomical approach.Short-axis cine stacks were acquired at rest and during dobutamine stimulation (10 and 20 µg · kg(-1 · min(-1 in 10 healthy volunteers. Rotational displacement was analysed for all slices. A complete 3D-LV rotational model was developed using linear interpolation between adjacent slices. Torsion was defined as the difference between apical and basal rotation, divided by slice distance. Depending on the distance between the most apical (defined as 0% LV distance and basal (defined as 100% LV distance slices, four different models for the calculation of torsion were examined: Model-1 (25-75%, Model-2 (0-100%, Model-3 (25-100% and Model-4 (0-75%. Analysis included subendocardial, subepicardial and global torsion and recoil rate (mean of subendocardial and subepicardial values.Quantification of torsion and recoil rate was feasible in all subjects. There was no significant difference between the different models at rest. However, only Model-1 (25-75% discriminated between rest and stress (Global Torsion: 2.7 ± 1.5° cm(-1, 3.6 ± 2.0° cm(-1, 5.1 ± 2.2° cm(-1, p<0.01; Global Recoil Rate: -30.1 ± 11.1° cm(-1 s(-1,-46.9 ± 15.0° cm(-1 s(-1,-68.9 ± 32.3° cm(-1 s(-1, p<0.01; for rest, 10 and 20 µg · kg(-1 · min(-1 of dobutamine, respectively. Reproducibility was sufficient for all parameters as determined by Bland-Altman analysis, intraclass correlation coefficients and coefficient of variation.CMR-FT based derivation of myocardial torsion and recoil rate is feasible and reproducible at rest and with dobutamine stress. Using an optimal

  9. PROCESS FEATURES OF FLUCTUATIONS PROPAGATION AT STRESS-STRAIN WORK OF THE RAILWAY TRACK

    Directory of Open Access Journals (Sweden)

    I. O. Bondarenko

    2015-12-01

    Full Text Available Purpose. Scientific work aims at the determination the basic laws of fluctuations propagation process from exitation of rolling stock in the design system of permanent way and substructures of the railway lines for studing the deformation processes as the basis for a regulatory framework of the track operation in the conditions of ensuring the reliability of railways. Methodology. To achieve the aim the principles of elasticity theories and wave propagation process in describing the interaction track and rolling stock were applied. Findings. The kinds of fluctuations and system which should be used when considering the fluctuations in the deformation process of rail track were established. The general view of the displacement function was determined. Originality. The theoretical concepts and principles to consider fluctuations of a structures system of permanent way and substructures of the railway track, energised by rolling stock were grounded. This will allow studing the process of deformation work of the mentioned system, which changes its state. That in turn will allow us to determine the parameters of the trains functional reliability, as part of the security passes of rolling stock on the track section with regard to its technical condition. Practical value. Usually for safe crossing of rolling stock parameters of fluctuation process in the system «vehicle-track» are determined. Existing models or carefully consider fluctuations of rolling stock in generalized characteristics of the structures of permanent way and substructures of the railway tracks or view of quasi-dynamic fluctuations rails with general characteristics of under rail base. This review process of oscillations, energised by rolling stock and delivered to all the elements of the permanent way and substructures of the railway track do not allow determining both the reliability parameters of elements in the system of track construction and parameters of functional

  10. Coding Local and Global Binary Visual Features Extracted From Video Sequences.

    Science.gov (United States)

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

    2015-11-01

    Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

  11. 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.

  12. 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.

  13. Preserved Myocardial Deformation after Successful Coarctation Repair: A CMR Feature-Tracking Study.

    Science.gov (United States)

    Dijkema, Elles J; Slieker, Martijn G; Breur, Johannes M P J; Leiner, Tim; Grotenhuis, Heynric B

    2017-12-05

    Arterial vasculopathy and residual aortic obstruction can lead to left ventricular (LV) dysfunction in patients with coarctation of the aorta (CoA) related to adverse ventriculo-arterial coupling. This study aimed to investigate potential differences in LV myocardial deformation indices between repaired CoA patients and healthy controls. Twenty-two CoA patients (age 30 ± 10.6 years) after surgical repair (n = 12) or balloon angioplasty (BA) (n = 10) without residual stenosis, between 3 months and 16 years of age with > 10 years follow-up were compared to 22 healthy age- and gender-matched controls (age 30 ± 3.8 years). Cardiac magnetic resonance feature tracking (CMR-FT) was used for LV longitudinal-, circumferential-, and rotational deformation indices. Global systolic LV function was preserved in CoA patients (LV ejection fraction 58 ± 4.8 vs. 60 ± 6.8%, p = 0.56) when compared to controls, with normal LV dimensions and mass (p > 0.05). Twelve CoA patients (55%) were hypertensive, of whom 4 were on anti-hypertensive medication. LV global longitudinal strain was preserved in the four-chamber (- 18 ± 4.4 vs. - 16 ± 4.7%, p = 0.06) and two-chamber (- 22 ± 5.1 vs. - 20 ± 6.0%, p = 0.22) orientations in CoA patients. Global circumferential strain was preserved at basal (- 29 ± 4.1 vs. - 28 ± 4.8%, p = 0.43), mid-ventricular (- 27 ± 4.2 vs. - 25 ± 3.0%, p = 0.09), and apical levels (- 35 ± 7.8 vs. - 32 ± 34.9%, p = 0.32). No differences were found in global torsion (2.4 ± 1.3° vs. 2.0 ± 1.4°/cm, p = 0.28), twist (14 ± 5.8° vs. 12 ± 6.3°, p = 0.34), and recoil rate (- 17 ± 9.7° vs. - 17 ± 7.1°/cm s, p = 0.97). Analysis of intra-observer variability demonstrated good reproducibility for all CMR deformation indices. Global and rotational myocardial deformation indices are preserved in Co

  14. Can Late L2 Learners Acquire New Grammatical Features? Evidence from ERPs and Eye-Tracking

    Science.gov (United States)

    Foucart, Alice; Frenck-Mestre, Cheryl

    2012-01-01

    We report a series of ERP and eye-tracking experiments investigating, (a) whether English-French learners can process grammatical gender online, (b) whether cross-linguistic similarities influence this ability, and (c) whether the syntactic distance between elements affects agreement processing. To address these questions we visually presented…

  15. A transition radiation detector for RHIC featuring accurate tracking and dE/dx particle identification

    Energy Technology Data Exchange (ETDEWEB)

    O`Brien, E.; Lissauer, D.; McCorkle, S.; Polychronakos, V.; Takai, H. [Brookhaven National Lab., Upton, NY (United States); Chi, C.Y.; Nagamiya, S.; Sippach, W.; Toy, M.; Wang, D.; Wang, Y.F.; Wiggins, C.; Willis, W. [Columbia Univ., New York, NY (United States); Cherniatin, V.; Dolgoshein, B. [Moscow Institute of Physics and Engineering, (Russian Federation); Bennett, M.; Chikanian, A.; Kumar, S.; Mitchell, J.T.; Pope, K. [Yale Univ., New Haven, CT (United States)

    1991-12-31

    We describe the results of a test ran involving a Transition Radiation Detector that can both distinguish electrons from pions which momenta greater titan 0.7 GeV/c and simultaneously track particles passing through the detector. The particle identification is accomplished through a combination of the detection of Transition Radiation from the electron and the differences in electron and pion energy loss (dE/dx) in the detector. The dE/dx particle separation is most, efficient below 2 GeV/c while particle ID utilizing Transition Radiation effective above 1.5 GeV/c. Combined, the electron-pion separation is-better than 5 {times} 10{sup 2}. The single-wire, track-position resolution for the TRD is {approximately}230 {mu}m.

  16. Automatic detection and tracking of filaments for a solar feature database

    Directory of Open Access Journals (Sweden)

    J. Aboudarham

    2008-02-01

    Full Text Available A new method for the automatic detection and tracking of solar filaments is presented. The method addresses the problems facing existing catalogs, such as the one developed recently in the frame of the European Grid of Solar Observations (EGSO project. In particular, it takes into account the structural and temporal evolution of filaments, differences in intensity as seen from one observation to the next, and the possibility of sudden disappearance followed by reappearance. In this study, the problem of tracking is solved by plotting all detected filaments during each solar rotation on a Carrington map and then by applying region growing techniques on those plots. Using this approach, the "fixed" positions of the envelopes in the Carrington system can be deduced. This is followed by a backward tracking of each filament by considering one full solar rotation. The resulting shifted Carrington map then enables one to follow any filament from one rotation to the next. Such maps should prove valuable for studies of the role of filaments in solar activity, notably coronal mass ejections (CMEs.

  17. Driver face tracking using semantics-based feature of eyes on single FPGA

    Science.gov (United States)

    Yu, Ying-Hao; Chen, Ji-An; Ting, Yi-Siang; Kwok, Ngaiming

    2017-06-01

    Tracking driver's face is one of the essentialities for driving safety control. This kind of system is usually designed with complicated algorithms to recognize driver's face by means of powerful computers. The design problem is not only about detecting rate but also from parts damages under rigorous environments by vibration, heat, and humidity. A feasible strategy to counteract these damages is to integrate entire system into a single chip in order to achieve minimum installation dimension, weight, power consumption, and exposure to air. Meanwhile, an extraordinary methodology is also indispensable to overcome the dilemma of low-computing capability and real-time performance on a low-end chip. In this paper, a novel driver face tracking system is proposed by employing semantics-based vague image representation (SVIR) for minimum hardware resource usages on a FPGA, and the real-time performance is also guaranteed at the same time. Our experimental results have indicated that the proposed face tracking system is viable and promising for the smart car design in the future.

  18. Endoscopic feature tracking for augmented-reality assisted prosthesis selection in mitral valve repair

    Science.gov (United States)

    Engelhardt, Sandy; Kolb, Silvio; De Simone, Raffaele; Karck, Matthias; Meinzer, Hans-Peter; Wolf, Ivo

    2016-03-01

    Mitral valve annuloplasty describes a surgical procedure where an artificial prosthesis is sutured onto the anatomical structure of the mitral annulus to re-establish the valve's functionality. Choosing an appropriate commercially available ring size and shape is a difficult decision the surgeon has to make intraoperatively according to his experience. In our augmented-reality framework, digitalized ring models are superimposed onto endoscopic image streams without using any additional hardware. To place the ring model on the proper position within the endoscopic image plane, a pose estimation is performed that depends on the localization of sutures placed by the surgeon around the leaflet origins and punctured through the stiffer structure of the annulus. In this work, the tissue penetration points are tracked by the real-time capable Lucas Kanade optical flow algorithm. The accuracy and robustness of this tracking algorithm is investigated with respect to the question whether outliers influence the subsequent pose estimation. Our results suggest that optical flow is very stable for a variety of different endoscopic scenes and tracking errors do not affect the position of the superimposed virtual objects in the scene, making this approach a viable candidate for annuloplasty augmented reality-enhanced decision support.

  19. The 15 March 2007 paroxysm of Stromboli: video-image analysis, and textural and compositional features of the erupted deposit

    Science.gov (United States)

    Andronico, Daniele; Taddeucci, Jacopo; Cristaldi, Antonio; Miraglia, Lucia; Scarlato, Piergiorgio; Gaeta, Mario

    2013-07-01

    On 15 March 2007, a paroxysmal event occurred within the crater terrace of Stromboli, in the Aeolian Islands (Italy). Infrared and visible video recordings from the monitoring network reveal that there was a succession of highly explosive pulses, lasting about 5 min, from at least four eruptive vents. Initially, brief jets with low apparent temperature were simultaneously erupted from the three main vent regions, becoming hotter and transitioning to bomb-rich fountaining that lasted for 14 s. Field surveys estimate the corresponding fallout deposit to have a mass of ˜1.9 × 107 kg that, coupled with the video information on eruption duration, provides a mean mass eruption rate of ˜5.4 × 105 kg/s. Textural and chemical analyses of the erupted tephra reveal unexpected complexity, with grain-size bimodality in the samples associated with the different percentages of ash types (juvenile, lithics, and crystals) that reflects almost simultaneous deposition from multiple and evolving plumes. Juvenile glass chemistry ranges from a gas-rich, low porphyricity end member (typical of other paroxysmal events) to a gas-poor high porphyricity one usually associated with low-intensity Strombolian explosions. Integration of our diverse data sets reveals that (1) the 2007 event was a paroxysmal explosion driven by a magma sharing common features with large-scale paroxysms as well as with "ordinary" Strombolian explosions; (2) initial vent opening by the release of a pressurized gas slug and subsequent rapid magma vesiculation and ejection, which were recorded both by the infrared camera and in the texture of fallout products; and (3) lesser paroxysmal events can be highly dynamic and produce surprisingly complex fallout deposits, which would be difficult to interpret from the geological record alone.

  20. FEATURES OF PERCEPTION OF LOADING ELEMENTS OF THE RAILWAY TRACK AT HIGH SPEEDS OF THE MOVEMENT

    Directory of Open Access Journals (Sweden)

    D. M. Kurhan

    2015-03-01

    Full Text Available Purpose. Increase the train speeds movements requires not only the appropriate technical solutions, but also methodological-calculated. Most of the models and methodologies used for solving problems of stress-strain state of the railroad tracks, are based on assumptions and hypotheses adequate only for certain speeds. In the framework of this work will be discussed theoretical background of the changing nature of perceptual load elements of the railway track at high speeds and investigated the numeric parameters of the processes by means of mathematical modeling. As a practical purposes is expected to provide the levels of train speed, the boundaries of which can reasonably exclude the possibility of occurrence of the considered effects. Methodology. To achieve these objectives was used principal new model of railway track based on wave propagation theory stresses in the elastic system to study the impact of the movable load, take into account that the deflection in a particular section of the road starts even while the wheels at some distance, and moving the wheels farther from the selected section of the wave front elastic strain continues to spread. According to the results of simulations explores the changing shape of the wave front voltages in time for the foundation under the rail. If the train speeds substantially less than the velocity propagation of elastic waves, the wheel remains in the area implemented deformations. Findings. Alternative calculations for various parameters of the railway track (especially for different soil conditions determined the levels of train speed, the boundaries of which can reasonably exclude the possibility of occurrence of the considered effects. Originality. The proposed theoretical study and implementation in the form of mathematical models for processes that occur in the perception of load elements of the railway track at high speeds. Practical value. According to simulation results obtained levels of

  1. Electronic evaluation for video commercials by impression index.

    Science.gov (United States)

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

    2013-12-01

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

  2. 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

  3. Image motion compensation by area correlation and centroid tracking of solar surface features

    Science.gov (United States)

    Nein, M. E.; Mcintosh, W. R.; Cumings, N. P.

    1983-01-01

    An experimental solar correlation tracker was tested and evaluated on a ground-based solar magnetograph. Using sunspots as fixed targets, tracking error signals were derived by which the telescope image was stabilized against wind induced perturbations. Two methods of stabilization were investigated; mechanical stabilization of the image by controlled two-axes motion of an active optical element in the telescope beam, and electronic stabilization by biasing of the electron scan in the recording camera. Both approaches have demonstrated telescope stability of about 0.6 arc sec under random perturbations which can cause the unstabilized image to move up to 120 arc sec at frequencies up to 30 Hz.

  4. 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.

  5. Feature Extraction from MEMS Accelerometer and Motion Tracking Measurements in Comparison with Smart Bands during Running

    Directory of Open Access Journals (Sweden)

    Andy Stamm

    2018-02-01

    Full Text Available Athlete monitoring is a major field of interest for professional and recreational runners as well as for coaches to improve performance and reduce injury risk. The development of inertial sensors in recent years offers the opportunity to improve the number of monitored training sessions significantly. This research used a self-developed inertial sensor in conjunction with a motion tracking system and four smart bands to record the runner’s movement and extract parameters such as step numbers and frequencies. The data recorded were calibrated before it was high-pass filtered to remove gravity components from the signal. A peak detection algorithm was developed to find the number of steps, which have been further used to compare the different systems (IMU, motion capture, smart bands and find their agreement. The results showed a very strong correlation between the IMU and the motion tracking system of r2 = 0.998, and an r2 = 0.996 between the IMU and one smart band.

  6. Multiple Feature Fusion Based on Co-Training Approach and Time Regularization for Place Classification in Wearable Video

    Directory of Open Access Journals (Sweden)

    Vladislavs Dovgalecs

    2013-01-01

    Full Text Available The analysis of video acquired with a wearable camera is a challenge that multimedia community is facing with the proliferation of such sensors in various applications. In this paper, we focus on the problem of automatic visual place recognition in a weakly constrained environment, targeting the indexing of video streams by topological place recognition. We propose to combine several machine learning approaches in a time regularized framework for image-based place recognition indoors. The framework combines the power of multiple visual cues and integrates the temporal continuity information of video. We extend it with computationally efficient semisupervised method leveraging unlabeled video sequences for an improved indexing performance. The proposed approach was applied on challenging video corpora. Experiments on a public and a real-world video sequence databases show the gain brought by the different stages of the method.

  7. 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

  8. Tissue segmentation from head MRI: a ground truth validation for feature-enhanced tracking

    Directory of Open Access Journals (Sweden)

    Wissel Tobias

    2015-09-01

    Full Text Available Accuracy is essential for optical head-tracking in cranial radiotherapy. Recently, the exploitation of local patterns of tissue information was proposed to achieve a more robust registration. Here, we validate a ground truth for this information obtained from high resolution MRI scans. In five subjects we compared the segmentation accuracy of a semi-automatic algorithm with five human experts. While the algorithm segments the skin and bone surface with an average accuracy of less than 0.1 mm and 0.2 mm, respectively, the mean error on the tissue thickness was 0.17 mm. We conclude that this accuracy is a reasonable basis for extracting reliable cutaneous structures to support surface registration.

  9. High-Frame-Rate Deformation Imaging in Two Dimensions Using Continuous Speckle-Feature Tracking.

    Science.gov (United States)

    Andersen, Martin V; Moore, Cooper; Arges, Kristine; Søgaard, Peter; Østergaard, Lasse R; Schmidt, Samuel E; Kisslo, Joseph; Von Ramm, Olaf T

    2016-11-01

    The study describes a novel algorithm for deriving myocardial strain from an entire cardiac cycle using high-frame-rate ultrasound images. Validation of the tracking algorithm was conducted in vitro prior to the application to patient images. High-frame-rate ultrasound images were acquired in vivo from 10 patients, and strain curves were derived in six myocardial regions around the left ventricle from the apical four-chamber view. Strain curves derived from high-frame-rate images had a higher frequency content than those derived using conventional methods, reflecting improved temporal sampling. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  10. Quantification of global myocardial function by cine MRI deformable registration-based analysis: Comparison with MR feature tracking and speckle-tracking echocardiography

    Energy Technology Data Exchange (ETDEWEB)

    Lamacie, Mariana M. [University Health Network, Department of Medical Imaging, Toronto, Ontario (Canada); Thavendiranathan, Paaladinesh [University Health Network, Department of Medical Imaging, Toronto, Ontario (Canada); University of Toronto, Department of Medicine, Division of Cardiology, Toronto, Ontario (Canada); Hanneman, Kate [University Health Network, Department of Medical Imaging, Toronto, Ontario (Canada); University of Toronto, Department of Medical Imaging, Toronto, Ontario (Canada); Greiser, Andreas [Siemens Healthcare, Erlangen (Germany); Jolly, Marie-Pierre [Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ (United States); Ward, Richard [University of Toronto, Department of Medicine, Division of Cardiology, Toronto, Ontario (Canada); Wintersperger, Bernd J. [University Health Network, Department of Medical Imaging, Toronto, Ontario (Canada); University of Toronto, Department of Medical Imaging, Toronto, Ontario (Canada); Toronto General Hospital, Department of Medical Imaging, Toronto, Ontario (Canada)

    2017-04-15

    To evaluate deformable registration algorithms (DRA)-based quantification of cine steady-state free-precession (SSFP) for myocardial strain assessment in comparison with feature-tracking (FT) and speckle-tracking echocardiography (STE). Data sets of 28 patients/10 volunteers, undergoing same-day 1.5T cardiac MRI and echocardiography were included. LV global longitudinal (GLS), circumferential (GCS) and radial (GRS) peak systolic strain were assessed on cine SSFP data using commercially available FT algorithms and prototype DRA-based algorithms. STE was applied as standard of reference for accuracy, precision and intra-/interobserver reproducibility testing. DRA showed narrower limits of agreement compared to STE for GLS (-4.0 [-0.9,-7.9]) and GCS (-5.1 [1.1,-11.2]) than FT (3.2 [11.2,-4.9]; 3.8 [13.9,-6.3], respectively). While both DRA and FT demonstrated significant differences to STE for GLS and GCS (all p<0.001), only DRA correlated significantly to STE for GLS (r=0.47; p=0.006). However, good correlation was demonstrated between MR techniques (GLS:r=0.74; GCS:r=0.80; GRS:r=0.45, all p<0.05). Comparing DRA with FT, intra-/interobserver coefficient of variance was lower (1.6 %/3.2 % vs. 6.4 %/5.7 %) and intraclass-correlation coefficient was higher. DRA GCS and GRS data presented zero variability for repeated observations. DRA is an automated method that allows myocardial deformation assessment with superior reproducibility compared to FT. (orig.)

  11. Based On Intrinsic Mode Function Energy Tracking Method of Circuit Breaker Vibration Signal Feature Extraction Studies

    Directory of Open Access Journals (Sweden)

    Sun Yi-Hang

    2017-01-01

    Full Text Available In order to detect a mechanical type of structural failure of the circuit breaker, the characteristics of the circuit breaker mechanical vibration signal is analyzed in this paper. A combination of medium voltage circuit breaker based on empirical mode decomposition (EMD amount of energy and support vector machine (SVM theory vibration signal feature vector extraction and analysis of fault classification method is proposed. First, the vibration signal of the circuit breaker is decomposed by EMD, then intrinsic mode function (IMF is obtain. The major fault feature information intrinsic mode functions the amount of energy of the component is obtained by discrete sampling points and the amount of energy. Using the amount of energy of IMF component as a feature vector, the failure of the test sample signal as input feature vector into trained “BT-SVM” support vector machine classification mechanism for fault classification. The differences and fault type of vibration signals can be identified by this method through the experimental analysis.

  12. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

  13. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-03-01

    Full Text Available Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT, speed-up robust feature (SURF, local binary patterns (LBP, histogram of oriented gradients (HOG, and weighted HOG. Recently, the convolutional neural network (CNN method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  14. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-03-20

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  15. 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

  16. Tracking subtle stereotypes of children with trisomy 21: from facial-feature-based to implicit stereotyping.

    Directory of Open Access Journals (Sweden)

    Claire Enea-Drapeau

    Full Text Available BACKGROUND: Stigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome, the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping. METHODOLOGY/PRINCIPAL FINDINGS: The participants were 165 adults including 55 young adult students, 55 non-student adults, and 55 professional caregivers working with intellectually disabled persons. They were faced with implicit association tests (IAT, a well-known technique whereby response latency is used to capture the relative strength with which some groups of people--here photographed faces of typically developing children and children with T21--are automatically (without conscious awareness associated with positive versus negative attributes in memory. Each participant also rated the same photographed faces (consciously accessible evaluations. We provide the first evidence that the positive bias typically found in explicit judgments of children with T21 is smaller for those whose facial features are highly characteristic of this disorder, compared to their counterparts with less distinctive features and to typically developing children. We also show that this bias can coexist with negative evaluations at the implicit level (with large effect sizes, even among professional caregivers. CONCLUSION: These findings support recent models of feature-based stereotyping, and more importantly show how crucial it is to go beyond explicit evaluations to estimate the true extent of stigmatization of intellectually disabled people.

  17. 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.

  18. A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.

    Directory of Open Access Journals (Sweden)

    Zhiling Hong

    Full Text Available Based on the traditional Fast Retina Keypoint (FREAK feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment.

  19. A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.

    Science.gov (United States)

    Hong, Zhiling; Lin, Fan; Xiao, Bin

    2017-01-01

    Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment.

  20. 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...

  1. 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.

  2. Cardiac magnetic resonance feature tracking: a novel method to assess myocardial strain. Comparison with echocardiographic speckle tracking in healthy volunteers and in patients with left ventricular hypertrophy.

    Science.gov (United States)

    Orwat, Stefan; Kempny, Aleksander; Diller, Gerhard-Paul; Bauerschmitz, Pia; Bunck, Alexander Ch; Maintz, David; Radke, Robert M; Baumgartner, Helmut

    2014-01-01

    Left ventricular longitudinal strain (LV-LS) and strain rate (SR) are sensitive markers of early systolic dysfunction. To evaluate the feasibility of a novel, cardiac magnetic resonance (CMR) based method known as feature tracking (FT) for the assessment of strain and SR, and to compare the CMR based results to those obtained on standard transthoracic echocardiography (TTE) in healthy volunteers and in patients with left ventricular hypertrophy cardiomyopathy (HCM). Overall, 20 healthy volunteers (ten male, mean age 24 ± 3 years) and 20 consecutive patients with HCM (12 male, mean age 47 ± 19 years) were included. Longitudinal and circumferential strain and SR of the left ventricle were measured on CMR at 1.5 Tesla and TTE and interobserver variability was assessed. FT measurements were feasible in all subjects. A good agreement between global LV-LS measured on CMR (controls: 20.8 ± 3.0; HCM: 17.6 ± 3.8) and TTE (controls: 19.4 ± 2.1; HCM: 16.6 ± 2.9) was found, while the agreement was worse for circumferential strain and all SR measurements. For the left and right ventricles, interobserver reproducibility was higher for strain measurements compared to SR. Coefficients of variation were lowest for LV-LS (13.2%) by CMR. FT analysis is a novel CMR based method for the analysis of myocardial strain and SR that is simple and correlates well with the echocardiographic measurements. Since CMR is unaffected by inadequate acoustic windows, FT may represent an attractive alternative to echocardiography in assessing the increasingly important parameters of myocardial deformation.

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

    Science.gov (United States)

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

    2017-05-01

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

  4. 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.

  5. 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.

  6. 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.

  7. The Effect of Theme Preference on Academic Word List Use: A Case for Smartphone Video Recording Feature

    Science.gov (United States)

    Gromik, Nicolas A.

    2017-01-01

    Sixty-seven Japanese English as a Second Language undergraduate learners completed one smartphone video production per week for 12 weeks, based on a teacher-selected theme. Designed as a case study for this specific context, data from students' oral performances was analyzed on a weekly basis for their use of the Academic Word List (AWL). A…

  8. Selectively De-animating and Stabilizing Videos

    Science.gov (United States)

    2014-12-11

    welcoming me into their classes. I have learnt so much from them. My graduate life has been wonderful due to the great friends and lab mates I have...techniques for interactive control of video stabilization. The first step in current video stabilization methods is to track feature points that esti- mate ...Transactions on 18.11 (2012), pp. 1868–1879. [103] Gregory P. Sutton and Malcolm Burrows. “Biomechanics of jumping in the flea ”. In: J Exp Biol 214.5

  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. On the comparison of visual discomfort generated by S3D and 2D content based on eye-tracking features

    Science.gov (United States)

    Iatsun, Iana; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine

    2014-03-01

    The changing of TV systems from 2D to 3D mode is the next expected step in the telecommunication world. Some works have already been done to perform this progress technically, but interaction of the third dimension with humans is not yet clear. Previously, it was found that any increased load of visual system can create visual fatigue, like prolonged TV watching, computer work or video gaming. But watching S3D can cause another nature of visual fatigue, since all S3D technologies creates illusion of the third dimension based on characteristics of binocular vision. In this work we propose to evaluate and compare the visual fatigue from watching 2D and S3D content. This work shows the difference in accumulation of visual fatigue and its assessment for two types of content. In order to perform this comparison eye-tracking experiments using six commercially available movies were conducted. Healthy naive participants took part into the test and gave their answers feeling the subjective evaluation. It was found that watching stereo 3D content induce stronger feeling of visual fatigue than conventional 2D, and the nature of video has an important effect on its increase. Visual characteristics obtained by using eye-tracking were investigated regarding their relation with visual fatigue.

  11. Utility of optical facial feature and arm movement tracking systems to enable text communication in critically ill patients who cannot otherwise communicate.

    Science.gov (United States)

    Muthuswamy, M B; Thomas, B N; Williams, D; Dingley, J

    2014-09-01

    Patients recovering from critical illness especially those with critical illness related neuropathy, myopathy, or burns to face, arms and hands are often unable to communicate by writing, speech (due to tracheostomy) or lip reading. This may frustrate both patient and staff. Two low cost movement tracking systems based around a laptop webcam and a laser/optical gaming system sensor were utilised as control inputs for on-screen text creation software and both were evaluated as communication tools in volunteers. Two methods were used to control an on-screen cursor to create short sentences via an on-screen keyboard: (i) webcam-based facial feature tracking, (ii) arm movement tracking by laser/camera gaming sensor and modified software. 16 volunteers with simulated tracheostomy and bandaged arms to simulate communication via gross movements of a burned limb, communicated 3 standard messages using each system (total 48 per system) in random sequence. Ten and 13 minor typographical errors occurred with each system respectively, however all messages were comprehensible. Speed of sentence formation ranged from 58 to 120s with the facial feature tracking system, and 60-160s with the arm movement tracking system. The average speed of sentence formation was 81s (range 58-120) and 104s (range 60-160) for facial feature and arm tracking systems respectively, (Pcommunication aids in patients in general and burns critical care units who cannot communicate by conventional means, due to the nature of their injuries. Copyright © 2014 Elsevier Ltd and ISBI. All rights reserved.

  12. 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

  13. 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.

  14. Prognostic value of biventricular mechanical parameters assessed using cardiac magnetic resonance feature-tracking analysis to predict future cardiac events.

    Science.gov (United States)

    Yang, Li Tan; Yamashita, Eiji; Nagata, Yasufumi; Kado, Yuichiro; Oshima, Shigeru; Otsuji, Yutaka; Takeuchi, Masaaki

    2017-04-01

    To study and compare the prognostic value of cardiac magnetic resonance feature tracking (MR-FT) of biventricular strain parameters with a conventional method. We retrospectively enrolled 364 patients undergoing clinically indicated cardiac MR examinations (1.5 or 3T scanner). Standard steady-state free precession (SSFP) images were used for analysis. Left ventricular (LV) and right ventricular (RV) ejection fraction (EF) were measured using conventional disk-area summation methods. Biventricular strain parameters were measured using MR-FT. All patients were followed to record major adverse cardiac events (MACEs). The correlations between LV volumes and LVEF using both methods were excellent (r = 0.87-0.98). RV strain parameters were modestly correlated with RVEF (r = 0.44-0.63). During a median follow-up of 15 months, 36 patients developed MACEs. All MR-FT-derived parameters except for RV global longitudinal strain were significantly associated with future MACEs (P global radial strain (RVGRS) provided incremental prognostic value in models adjusted for age, gender, conventional LVEF (hazard ratio 0.93; P = 0.029) or RVEF (hazard ratio 0.93; P = 0.038). LV global transverse strain (LVGTS) also offered additional value over age, gender, conventional LVEF (hazard ratio 0.94; P = 0.041), or RVEF (hazard ratio 0.94; P = 0.004). Kaplan-Meier analysis showed significant survival differences in subgroups stratified by the median value of LVGTS, RVGRS, and LVEF using MR-FT (all log-rank P power similar to parameters obtained using conventional methods. MR-FT is a promising alternative both for ventricular chamber quantification and for providing information of future cardiac events. 3 J. Magn. Reson. Imaging 2017;45:1034-1045. © 2016 International Society for Magnetic Resonance in Medicine.

  15. NucliTrack: an integrated nuclei tracking application.

    Science.gov (United States)

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

    2017-10-15

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

  16. An improved likelihood model for eye tracking

    DEFF Research Database (Denmark)

    Hammoud, Riad I.; Hansen, Dan Witzner

    2007-01-01

    While existing eye detection and tracking algorithms can work reasonably well in a controlled environment, they tend to perform poorly under real world imaging conditions where the lighting produces shadows and the person's eyes can be occluded by e.g. glasses or makeup. As a result, pixel clusters...... associated with the eyes tend to be grouped together with background-features. This problem occurs both for eye detection and eye tracking. Problems that especially plague eye tracking include head movement, eye blinking and light changes, all of which can cause the eyes to suddenly disappear. The usual...... approach in such cases is to abandon the tracking routine and re-initialize eye detection. Of course this may be a difficult process due to missed data problem. Accordingly, what is needed is an efficient method of reliably tracking a person's eyes between successively produced video image frames, even...

  17. Communications via the radio artificial earth satellite: Design of the tracking diagram and features for conducting QSO

    Science.gov (United States)

    Dobrozhanskiy, V.; Rybkin, V.

    1980-01-01

    A detailed examination is made of the operation of a transmitting artifical Earth satellite. A tracking diagram for the satellite is constructed. The zone of radio visibility can be determined based on the techniques proposed.

  18. Video display terminal workstation improvement program: I. Baseline associations between musculoskeletal discomfort and ergonomic features of workstations.

    Science.gov (United States)

    Demure, B; Luippold, R S; Bigelow, C; Ali, D; Mundt, K A; Liese, B

    2000-08-01

    Associations between selected sites of musculoskeletal discomfort and ergonomic characteristics of the video display terminal (VDT) workstation were assessed in analyses controlling for demographic, psychosocial stress, and VDT use factors in 273 VDT users from a large administrative department. Significant associations with wrist/hand discomfort were seen for female gender; working 7+ hours at a VDT; low job satisfaction; poor keyboard position; use of new, adjustable furniture; and layout of the workstation. Significantly increased odds ratios for neck/shoulder discomfort were observed for 7+ hours at a VDT, less than complete job control, older age (40 to 49 years), and never/infrequent breaks. Lower back discomfort was related marginally to working 7+ hours at a VDT. These results demonstrate that some characteristics of VDT workstations, after accounting for psychosocial stress, can be correlated with musculoskeletal discomfort.

  19. 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.

  20. Target tracking with GIS data using a fusion-based approach

    Science.gov (United States)

    Bradford, Brian; Dixon, Eric M.; Sisskind, Joshua; Reynolds, William D., Jr.

    2011-06-01

    Military forces and law enforcement agencies are facing new challenges for persistent surveillance as the area of interest shifts towards urban environments. Some of the challenges include tracking vehicles and dismounts within complex road networks, traffic patterns and building structures. Under these conditions, conventional video tracking algorithms suffer from target occlusion, lost tracks and stop-and-start. Furthermore, these algorithms typically depend solely on pixel-based features to detect and locate potential targets, which are computationally intensive and time consuming. This research paper investigates the fusion of geographic information into video-based target tracking algorithms for persistent surveillance. A geographic information system (GIS) has the capability to store attributes about a target's surroundings - such as road direction and boundaries, intersections and speed limit - and can be used as a decision-making tool in prediction and analysis. Fusing this prediction capability into conventional video-centric target tracking algorithms provides geographical context to the target feature space improves occlusion of targets and reduces the search area for tracking. The GIS component specifically improves the performance of target tracking by minimizing the search area a target is likely to be located. We present the results from our simulations to demonstrate the feasibility of the proposed technique with video collected from a prototype persistent surveillance system. Our approach maintains compatibility with existing GIS databases and provides an integrated solution for multi-source target tracking algorithms.

  1. The research and application of visual saliency and adaptive support vector machine in target tracking field.

    Science.gov (United States)

    Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

    2013-01-01

    The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

  2. Feature-based respiratory motion tracking in native fluoroscopic sequences for dynamic roadmaps during minimally invasive procedures in the thorax and abdomen

    Science.gov (United States)

    Wagner, Martin G.; Laeseke, Paul F.; Schubert, Tilman; Slagowski, Jordan M.; Speidel, Michael A.; Mistretta, Charles A.

    2017-03-01

    Fluoroscopic image guidance for minimally invasive procedures in the thorax and abdomen suffers from respiratory and cardiac motion, which can cause severe subtraction artifacts and inaccurate image guidance. This work proposes novel techniques for respiratory motion tracking in native fluoroscopic images as well as a model based estimation of vessel deformation. This would allow compensation for respiratory motion during the procedure and therefore simplify the workflow for minimally invasive procedures such as liver embolization. The method first establishes dynamic motion models for both the contrast-enhanced vasculature and curvilinear background features based on a native (non-contrast) and a contrast-enhanced image sequence acquired prior to device manipulation, under free breathing conditions. The model of vascular motion is generated by applying the diffeomorphic demons algorithm to an automatic segmentation of the subtraction sequence. The model of curvilinear background features is based on feature tracking in the native sequence. The two models establish the relationship between the respiratory state, which is inferred from curvilinear background features, and the vascular morphology during that same respiratory state. During subsequent fluoroscopy, curvilinear feature detection is applied to determine the appropriate vessel mask to display. The result is a dynamic motioncompensated vessel mask superimposed on the fluoroscopic image. Quantitative evaluation of the proposed methods was performed using a digital 4D CT-phantom (XCAT), which provides realistic human anatomy including sophisticated respiratory and cardiac motion models. Four groups of datasets were generated, where different parameters (cycle length, maximum diaphragm motion and maximum chest expansion) were modified within each image sequence. Each group contains 4 datasets consisting of the initial native and contrast enhanced sequences as well as a sequence, where the respiratory motion is

  3. Algorithm combination of deblurring and denoising on video frames using the method search of local features on image

    Directory of Open Access Journals (Sweden)

    Semenishchev Evgeny

    2017-01-01

    Full Text Available In this paper, we propose an approach that allows us to perform an operation to reduce error in the form of noise and lubrication. To improve the processing speed and the possibility of parallelization of the process, we use the approach is based on the search for local features on the image.

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

    Energy Technology Data Exchange (ETDEWEB)

    Nakamura, M; Matsuo, Y; Mukumoto, N; Iizuka, Y; Yokota, K; Mizowaki, T; Hiraoka, M [Kyoto University, Graduate School of Medicine, Kyoto (Japan); Nakao, M [Kyoto University, Graduate School of Informatics, Kyoto (Japan)

    2016-06-15

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

  5. Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature tracking and pattern matching

    Science.gov (United States)

    Muckenhuber, Stefan; Sandven, Stein

    2017-08-01

    An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature tracking and pattern matching. Feature tracking produces an initial drift estimate and limits the search area for the consecutive pattern matching, which provides small- to medium-scale drift adjustments and normalised cross-correlation values. The algorithm is designed to combine the two approaches in order to benefit from the respective advantages. The considered feature-tracking method allows for an efficient computation of the drift field and the resulting vectors show a high degree of independence in terms of position, length, direction and rotation. The considered pattern-matching method, on the other hand, allows better control over vector positioning and resolution. The preprocessing of the Sentinel-1 data has been adjusted to retrieve a feature distribution that depends less on SAR backscatter peak values. Applying the algorithm with the recommended parameter setting, sea ice drift retrieval with a vector spacing of 4 km on Sentinel-1 images covering 400 km × 400 km, takes about 4 min on a standard 2.7 GHz processor with 8 GB memory. The corresponding recommended patch size for the pattern-matching step that defines the final resolution of each drift vector is 34 × 34 pixels (2.7 × 2.7 km). To assess the potential performance after finding suitable search restrictions, calculated drift results from 246 Sentinel-1 image pairs have been compared to buoy GPS data, collected in 2015 between 15 January and 22 April and covering an area from 80.5 to 83.5° N and 12 to 27° E. We found a logarithmic normal distribution of the displacement difference with a median at 352.9 m using HV polarisation and 535.7 m using HH polarisation. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.

  6. Advanced video coding systems

    CERN Document Server

    Gao, Wen

    2015-01-01

    This comprehensive and accessible text/reference presents an overview of the state of the art in video coding technology. Specifically, the book introduces the tools of the AVS2 standard, describing how AVS2 can help to achieve a significant improvement in coding efficiency for future video networks and applications by incorporating smarter coding tools such as scene video coding. Topics and features: introduces the basic concepts in video coding, and presents a short history of video coding technology and standards; reviews the coding framework, main coding tools, and syntax structure of AV

  7. 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.

  8. Videos & Tools: MedlinePlus

    Science.gov (United States)

    ... of this page: https://medlineplus.gov/videosandcooltools.html Videos & Tools To use the sharing features on this page, please enable JavaScript. Watch health videos on topics such as anatomy, body systems, and ...

  9. Health Videos: MedlinePlus

    Science.gov (United States)

    ... page: //medlineplus.gov/ency/anatomyvideos.html.htm Health Videos To use the sharing features on this page, please enable JavaScript. These animated videos show the anatomy of body parts and organ ...

  10. An unsupervised meta-graph clustering based prototype-specific feature quantification for human re-identification in video surveillance

    Directory of Open Access Journals (Sweden)

    Aparajita Nanda

    2017-06-01

    Full Text Available Human re-identification is an emerging research area in the field of visual surveillance. It refers to the task of associating the images of the persons captured by one camera (probe set with the images captured by another camera (gallery set at different locations in different time instances. The performance of these systems are often challenged by some factors—variation in articulated human pose and clothing, frequent occlusion with various objects, change in light illumination, and the cluttered background are to name a few. Besides, the ambiguity in recognition increases between individuals with similar appearance. In this paper, we present a novel framework for human re-identification that finds the correspondence image pair across non-overlapping camera views in the presence of the above challenging scenarios. The proposed framework handles the visual ambiguity having similar appearance by first segmenting the gallery instances into disjoint prototypes (groups, where each prototype represents the images with high commonality. Then, a weighing scheme is formulated that quantifies the selective and distinct information about the features concerning the level of contribution against each prototype. Finally, the prototype specific weights are utilized in the similarity measure and fused with the existing generic weighing to facilitates improvement in the re-identification. Exhaustive simulation on three benchmark datasets alongside the CMC (Cumulative Matching Characteristics plot enumerate the efficacy of our proposed framework over the counterparts.

  11. Video Quality Prediction over Wireless 4G

    KAUST Repository

    Lau, Chun Pong

    2013-04-14

    In this paper, we study the problem of video quality prediction over the wireless 4G network. Video transmission data is collected from a real 4G SCM testbed for investigating factors that affect video quality. After feature transformation and selection on video and network parameters, video quality is predicted by solving as regression problem. Experimental results show that the dominated factor on video quality is the channel attenuation and video quality can be well estimated by our models with small errors.

  12. The Research and Application of Visual Saliency and Adaptive Support Vector Machine in Target Tracking Field

    Directory of Open Access Journals (Sweden)

    Yuantao Chen

    2013-01-01

    Full Text Available The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking’s accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM. Furthermore, the paper’s algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target’s saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

  13. Comparison of cardiovascular magnetic resonance feature tracking and tagging for the assessment of left ventricular systolic strain in acute myocardial infarction

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Jamal N., E-mail: jk211@le.ac.uk; Singh, Anvesha, E-mail: as707@le.ac.uk; Nazir, Sheraz A., E-mail: sn191@le.ac.uk; Kanagala, Prathap, E-mail: pk214@le.ac.uk; Gershlick, Anthony H., E-mail: agershlick@aol.com; McCann, Gerry P., E-mail: gerry.mccann@uhl-tr.nhs.uk

    2015-05-15

    Highlights: • We compared feature tracking (FT) and tagging quantification of myocardial strain in acute MI. • This is the first study assessing FT strain assessment in acute MI. • FT was more robust and had better myocardial tracking than tagging. • FT had better interobserver agreement and FT analysis was quicker. • FT has stronger correlation with global and segmental infarct size, area at risk (oedema), myocardial salvage and infarct transmurality. • FT is feasible in acute MI and is likely to become the preferred quantification method. - Abstract: Aims: To assess the feasibility of feature tracking (FT)-measured systolic strain post acute ST-segment elevation myocardial infarction (STEMI) and compare strain values to those obtained with tagging. Methods: Cardiovascular MRI at 1.5 T was performed in 24 patients, 2.2 days post STEMI. Global and segmental circumferential (Ecc) and longitudinal (Ell) strain were assessed using FT and tagging, and correlated with total and segmental infarct size, area at risk and myocardial salvage. Results: All segments tracked satisfactorily with FT (p < 0.001 vs. tagging). Total analysis time per patient was shorter with FT (38.2 ± 3.8 min vs. 63.7 ± 10.3 min, p < 0.001 vs. tagging). Global Ecc and Ell were higher with FT than with tagging, apart from FT Ecc using the average of endocardial and epicardial contours (−13.45 ± 4.1 [FT] vs. −13.85 ± 3.9 [tagging], p = 0.66). Intraobserver and interobserver agreement for global strain were excellent for FT (ICC 0.906–0.990) but interobserver agreement for tagging was lower (ICC < 0.765). Interobserver and intraobserver agreement for segmental strain was good for both techniques (ICC > 0.7) apart from tagging Ell, which was poor (ICC = 0.15). FT-derived Ecc significantly correlated with total infarct size (r = 0.44, p = 0.03) and segmental infarct extent (r = 0.44, p < 0.01), and best distinguished transmurally infarcted segments (AUC 0.77) and infarcted from

  14. 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.

  15. Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature-tracking and pattern-matching

    Science.gov (United States)

    Muckenhuber, Stefan; Sandven, Stein

    2017-04-01

    An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature-tracking and pattern-matching. A computational efficient feature-tracking algorithm produces an initial drift estimate and limits the search area for the pattern-matching, that provides small to medium scale drift adjustments and normalised cross correlation values as quality measure. The algorithm is designed to utilise the respective advantages of the two approaches and allows drift calculation at user defined locations. The pre-processing of the Sentinel-1 data has been optimised to retrieve a feature distribution that depends less on SAR backscatter peak values. A recommended parameter set for the algorithm has been found using a representative image pair over Fram Strait and 350 manually derived drift vectors as validation. Applying the algorithm with this parameter setting, sea ice drift retrieval with a vector spacing of 8 km on Sentinel-1 images covering 400 km x 400 km, takes less than 3.5 minutes on a standard 2.7 GHz processor with 8 GB memory. For validation, buoy GPS data, collected in 2015 between 15th January and 22nd April and covering an area from 81° N to 83.5° N and 12° E to 27° E, have been compared to calculated drift results from 261 corresponding Sentinel-1 image pairs. We found a logarithmic distribution of the error with a peak at 300 m. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.

  16. Cultural and Developmental Influences on Overt Visual Attention to Videos

    OpenAIRE

    Necka, Elizabeth A.; Shneidman, Laura; Krogh-Jespersen, Sheila; Gaskins, Suzanne; Berman, Marc G.; Woodward, Amanda

    2017-01-01

    Top-down influences on observers? overt attention and how they interact with the features of the visual environment have been extensively investigated, but the cultural and developmental aspects of these modulations have been understudied. In this study we investigated these effects for US and Yucatec Mayan infants, children, and adults. Mayan and US participants viewed videos of two actors performing daily Mayan and US tasks in the foreground and the background while their eyes were tracked....

  17. Reviews in instructional video

    NARCIS (Netherlands)

    van der Meij, Hans

    2017-01-01

    This study investigates the effectiveness of a video tutorial for software training whose construction was based on a combination of insights from multimedia learning and Demonstration-Based Training. In the videos, a model of task performance was enhanced with instructional features that were

  18. Personal Digital Video Stories

    DEFF Research Database (Denmark)

    Ørngreen, Rikke; Henningsen, Birgitte Sølbeck; Louw, Arnt Vestergaard

    2016-01-01

    agenda focusing on video productions in combination with digital storytelling, followed by a presentation of the digital storytelling features. The paper concludes with a suggestion to initiate research in what is identified as Personal Digital Video (PDV) Stories within longitudinal settings, while...

  19. Use of an iPhone 4 with Video Features to Assist Location of Students with Moderate Intellectual Disability When Lost in Community Settings

    Science.gov (United States)

    Purrazzella, Kaitlin; Mechling, Linda C.

    2013-01-01

    This study evaluated the acquisition of use of an iPhone 4 by adults with moderate intellectual disability to take and send video captions of their location when lost in the community. A multiple probe across participants design was used to evaluate the effectiveness of the intervention which used video modeling, picture prompts, and instructor…

  20. Human tracking with thermal omnidirectional vision

    Science.gov (United States)

    Tang, Y.; Li, Y. F.; Chen, H.

    2011-12-01

    In this paper, we explore a new tracking system for human tracking in thermal catadioptric omnidirectional vision. Due to very limited features can be adopted in thermal image except for contour information, we proposed to use Histogram of Oriented Gradient (HOG) feature to represent the contour information and employ Support Vector Machine (SVM) to classify the foreground and background. In this paper, there are three novel points. First, the classification posterior probability of SVM will be adopted to relate the observation likelihood of particle filter to guide the particles for tracking purpose instead of neglect in previous tracking method. Second, due to no existing thermal catadioptric omnidirectional vision database available in public, a thermal catadioptric omnidirectional video database and extracted human samples have been established for academic studies. Third, tracking window distribution of particle filter has been adjusted to fit the characteristic of catadioptric omnidirectional vision on account of the size of target in image is varying when the distance between target and omni-sensor changed in world coordinate. In addition, the catadioptric omnidirectional imaging is different with traditional imaging for inherent distortion, so the polar coordinate will be used. The experimental results show that the proposed tracking approach has a stable performance.

  1. Robust Tracking with Discriminative Ranking Middle-Level Patches

    Directory of Open Access Journals (Sweden)

    Hong Liu

    2014-04-01

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

  2. SU-E-J-206: A Comparison of Different Hardware Design Approaches for Feature-Supported Optical Head-Tracking with Respect to Angular Dependencies

    Energy Technology Data Exchange (ETDEWEB)

    Stueber, P; Wissel, T; Wagner, B [Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck (Germany); Graduate School for Computing in Life Science, University of Luebeck, Luebeck (Germany); Bruder, R; Schweikard, A; Ernst, F [Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck (Germany)

    2014-06-01

    Purpose: Recent research has shown that optical features significantly improve marker-less optical head-tracking for cranial radiotherapy. Simulations, however, showed that these optical features, which are used to derive tissue thickness, depend on the incident angle of the IR scanning laser beam and the perspective of the camera analyzing the reflective patterns. We present an experimental analysis determining which is the most robust optical setup concerning angular influences. Methods: In three consecutive experiments, the incident angle of the laser (1), the perspective of the camera (2) or both simultaneously (3, ‘inBeam’-perspective) were changed with respect to the target. We analyzed how this affects feature intensity. These intensities were determined from seven concentric regions of interest (ROIs) around the laser spot. Two targets were used: a tissue-like silicone phantom and a human's forehead. Results: For each experiment, the feature intensity generally decreases with increasing angle. We found that the optical properties of the silicone phantom do not fit the properties of human skin. Furthermore, the angular influence of the laser on the features is significantly higher than the perspective of the camera. With the ‘inBeam’- perspective, the smoothest decays of feature intensity were found. We suppose that this is because of a fixed relationship between both devices. This smoothness, suggesting a predictable functional relationship, may simplify angle compensation for machine learning algorithms. This is particularly prominent for the medial ROIs. The inner ROIs highly depend on the angle and power of the laser. The outer ROIs show less angular dependency but the signal strength is critically low and prone to artifacts. Therefore and because of the smooth decays, medial ROIs are a suitable tradeoff between susceptibility, signal-noise-ratio and distance to the center of the laser spot. Conclusion: For tissue thickness correlated

  3. Visual tracking by separability-maximum boosting

    Science.gov (United States)

    Hou, Jie; Mao, Yao-bin; Sun, Jin-sheng

    2013-10-01

    Recently, visual tracking has been formulated as a classification problem whose task is to detect the object from the scene with a binary classifier. Boosting based online feature selection methods, which adopt the classifier to appearance changes by choosing the most discriminative features, have been demonstrated to be effective for visual tracking. A major problem of such online feature selection methods is that an inaccurate classifier may give imprecise tracking windows. Tracking error accumulates when the tracker trains the classifier with misaligned samples and finally leads to drifting. Separability-maximum boosting (SMBoost), an alternative form of AdaBoost which characterizes the separability between the object and the scene by their means and covariance matrices, is proposed. SMBoost only needs the means and covariance matrices during training and can be easily adopted to online learning problems by estimating the statistics incrementally. Experiment on UCI machine learning datasets shows that SMBoost is as accurate as offline AdaBoost, and significantly outperforms Oza's online boosting. Accurate classifier stabilizes the tracker on challenging video sequences. Empirical results also demonstrate improvements in term of tracking precision and speed, comparing ours to those state-of-the-art ones.

  4. 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...

  5. Markerless tracking for augmented reality for image-guided Endoscopic Retrograde Cholangiopancreatography.

    Science.gov (United States)

    Nguyen, Thinh T; Jung, Hoeryong; Lee, Doo Yong

    2013-01-01

    This paper proposes a markerless tracking method with adaptive pose estimation for augmenting 3D organ models on top of the endoscopic image for Endoscopic Retrograde Cholangiopancreatography (ERCP). While many applications of augmented reality (AR) to surgeries need special markers to track the camera's position and orientation in the live video, our method employs the feature detection techniques to track the endoscopic camera. One of the most difficult problems when applying feature-based method to AR for ERCP is the lack of texture & highly specular reflection surface of duodenum in the endoscopic images, which does not provide a stable number of keypoints to track in the endoscopic video sequence. By introducing an adaptive weight function in the combination of reference-current frame tracking with previous-current frame tracking, we enhance the tracking performance remarkably. The proposed method is evaluated using an endoscopic video of a real ERCP and 3D duodenum model reconstructed from CT data of the patient. The result shows real-time performance and robustness of the method.

  6. A Multisource Heterogeneous Data Fusion Method for Pedestrian Tracking

    Directory of Open Access Journals (Sweden)

    Zhenlian Shi

    2015-01-01

    Full Text Available Traditional visual pedestrian tracking methods perform poorly when faced with problems such as occlusion, illumination changes, and complex backgrounds. In principle, collecting more sensing information should resolve these issues. However, it is extremely challenging to properly fuse different sensing information to achieve accurate tracking results. In this study, we develop a pedestrian tracking method for fusing multisource heterogeneous sensing information, including video, RGB-D sequences, and inertial sensor data. In our method, a RGB-D sequence is used to position the target locally by fusing the texture and depth features. The local position is then used to eliminate the cumulative error resulting from the inertial sensor positioning. A camera calibration process is used to map the inertial sensor position onto the video image plane, where the visual tracking position and the mapped position are fused using a similarity feature to obtain accurate tracking results. Experiments using real scenarios show that the developed method outperforms the existing tracking method, which uses only a single sensing dataset, and is robust to target occlusion, illumination changes, and interference from similar textures or complex backgrounds.

  7. Collaborative Video Sketching

    DEFF Research Database (Denmark)

    Henningsen, Birgitte; Gundersen, Peter Bukovica; Hautopp, Heidi

    2017-01-01

    This paper introduces to what we define as a collaborative video sketching process. This process links various sketching techniques with digital storytelling approaches and creative reflection processes in video productions. Traditionally, sketching has been used by designers across various...... forms and through empirical examples, we present and discuss the video recording of sketching sessions, as well as development of video sketches by rethinking, redoing and editing the recorded sessions. The empirical data is based on workshop sessions with researchers and students from universities...... and university colleges and primary and secondary school teachers. As researchers, we have had different roles in these action research case studies where various video sketching techniques were applied.The analysis illustrates that video sketching can take many forms, and two common features are important...

  8. Multimodal emotion recognition using EEG and eye tracking data.

    Science.gov (United States)

    Zheng, Wei-Long; Dong, Bo-Nan; Lu, Bao-Liang

    2014-01-01

    This paper presents a new emotion recognition method which combines electroencephalograph (EEG) signals and pupillary response collected from eye tracker. We select 15 emotional film clips of 3 categories (positive, neutral and negative). The EEG signals and eye tracking data of five participants are recorded, simultaneously, while watching these videos. We extract emotion-relevant features from EEG signals and eye tracing data of 12 experiments and build a fusion model to improve the performance of emotion recognition. The best average accuracies based on EEG signals and eye tracking data are 71.77% and 58.90%, respectively. We also achieve average accuracies of 73.59% and 72.98% for feature level fusion strategy and decision level fusion strategy, respectively. These results show that both feature level fusion and decision level fusion combining EEG signals and eye tracking data can improve the performance of emotion recognition model.

  9. Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments

    Directory of Open Access Journals (Sweden)

    Huang KohsiaS

    2008-01-01

    Full Text Available Abstract We present a multilevel system architecture for intelligent environments equipped with omnivideo arrays. In order to gain unobtrusive human awareness, real-time 3D human tracking as well as robust video-based face detection and tracking and face recognition algorithms are needed. We first propose a multiprimitive face detection and tracking loop to crop face videos as the front end of our face recognition algorithm. Both skin-tone and elliptical detections are used for robust face searching, and view-based face classification is applied to the candidates before updating the Kalman filters for face tracking. For video-based face recognition, we propose three decision rules on the facial video segments. The majority rule and discrete HMM (DHMM rule accumulate single-frame face recognition results, while continuous density HMM (CDHMM works directly with the PCA facial features of the video segment for accumulated maximum likelihood (ML decision. The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99% accuracy of the CDHMM rule. We then experiment on the system interactions with single person and group people by the integrated layers of activity awareness. We also discuss the speech-aided incremental learning of new faces.

  10. Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments

    Directory of Open Access Journals (Sweden)

    Mohan M. Trivedi

    2008-04-01

    Full Text Available We present a multilevel system architecture for intelligent environments equipped with omnivideo arrays. In order to gain unobtrusive human awareness, real-time 3D human tracking as well as robust video-based face detection and tracking and face recognition algorithms are needed. We first propose a multiprimitive face detection and tracking loop to crop face videos as the front end of our face recognition algorithm. Both skin-tone and elliptical detections are used for robust face searching, and view-based face classification is applied to the candidates before updating the Kalman filters for face tracking. For video-based face recognition, we propose three decision rules on the facial video segments. The majority rule and discrete HMM (DHMM rule accumulate single-frame face recognition results, while continuous density HMM (CDHMM works directly with the PCA facial features of the video segment for accumulated maximum likelihood (ML decision. The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99% accuracy of the CDHMM rule. We then experiment on the system interactions with single person and group people by the integrated layers of activity awareness. We also discuss the speech-aided incremental learning of new faces.

  11. Interframe coding of feature descriptors for mobile augmented reality.

    Science.gov (United States)

    Makar, Mina; Chandrasekhar, Vijay; Tsai, Sam S; Chen, David; Girod, Bernd

    2014-08-01

    Streaming mobile augmented reality applications require both real-time recognition and tracking of objects of interest in a video sequence. Typically, local features are calculated from the gradients of a canonical patch around a keypoint in individual video frames. In this paper, we propose a temporally coherent keypoint detector and design efficient interframe predictive coding techniques for canonical patches, feature descriptors, and keypoint locations. In the proposed system, we strive to transmit each patch or its equivalent feature descriptor with as few bits as possible by modifying a previously transmitted patch or descriptor. Our solution enables server-based mobile augmented reality where a continuous stream of salient information, sufficient for image-based retrieval, and object localization, is sent at a bit-rate that is practical for today's wireless links and less than one-tenth of the bit-rate needed to stream the compressed video to the server.

  12. 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...

  13. Examining the effect of task on viewing behavior in videos using saliency maps

    Science.gov (United States)

    Alers, Hani; Redi, Judith A.; Heynderickx, Ingrid

    2012-03-01

    Research has shown that when viewing still images, people will look at these images in a different manner if instructed to evaluate their quality. They will tend to focus less on the main features of the image and, instead, scan the entire image area looking for clues for its level of quality. It is questionable, however, whether this finding can be extended to videos considering their dynamic nature. One can argue that when watching a video the viewer will always focus on the dynamically changing features of the video regardless of the given task. To test whether this is true, an experiment was conducted where half of the participants viewed videos with the task of quality evaluation while the other half were simply told to watch the videos as if they were watching a movie on TV or a video downloaded from the internet. The videos contained content which was degraded with compression artifacts over a wide range of quality. An eye tracking device was used to record the viewing behavior in both conditions. By comparing the behavior during each task, it was possible to observe a systematic difference in the viewing behavior which seemed to correlate to the quality of the videos.

  14. In search of video event semantics

    NARCIS (Netherlands)

    Mazloom, M.

    2016-01-01

    In this thesis we aim to represent an event in a video using semantic features. We start from a bank of concept detectors for representing events in video. At first we considered the relevance of concepts to the event inside the video representation. We address the problem of video event

  15. Gaze location prediction for broadcast football video.

    Science.gov (United States)

    Cheng, Qin; Agrafiotis, Dimitris; Achim, Alin M; Bull, David R

    2013-12-01

    The sensitivity of the human visual system decreases dramatically with increasing distance from the fixation location in a video frame. Accurate prediction of a viewer's gaze location has the potential to improve bit allocation, rate control, error resilience, and quality evaluation in video compression. Commercially, delivery of football video content is of great interest because of the very high number of consumers. In this paper, we propose a gaze location prediction system for high definition broadcast football video. The proposed system uses knowledge about the context, extracted through analysis of a gaze tracking study that we performed, to build a suitable prior map. We further classify the complex context into different categories through shot classification thus allowing our model to prelearn the task pertinence of each object category and build the prior map automatically. We thus avoid the limitation of assigning the viewers a specific task, allowing our gaze prediction system to work under free-viewing conditions. Bayesian integration of bottom-up features and top-down priors is finally applied to predict the gaze locations. Results show that the prediction performance of the proposed model is better than that of other top-down models that we adapted to this context.

  16. 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....

  17. 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

  18. A small-scale hyperacute compound eye featuring active eye tremor: application to visual stabilization, target tracking, and short-range odometry.

    Science.gov (United States)

    Colonnier, Fabien; Manecy, Augustin; Juston, Raphaël; Mallot, Hanspeter; Leitel, Robert; Floreano, Dario; Viollet, Stéphane

    2015-02-25

    In this study, a miniature artificial compound eye (15 mm in diameter) called the curved artificial compound eye (CurvACE) was endowed for the first time with hyperacuity, using similar micro-movements to those occurring in the fly's compound eye. A periodic micro-scanning movement of only a few degrees enables the vibrating compound eye to locate contrasting objects with a 40-fold greater resolution than that imposed by the interommatidial angle. In this study, we developed a new algorithm merging the output of 35 local processing units consisting of adjacent pairs of artificial ommatidia. The local measurements performed by each pair are processed in parallel with very few computational resources, which makes it possible to reach a high refresh rate of 500 Hz. An aerial robotic platform with two degrees of freedom equipped with the active CurvACE placed over naturally textured panels was able to assess its linear position accurately with respect to the environment thanks to its efficient gaze stabilization system. The algorithm was found to perform robustly at different light conditions as well as distance variations relative to the ground and featured small closed-loop positioning errors of the robot in the range of 45 mm. In addition, three tasks of interest were performed without having to change the algorithm: short-range odometry, visual stabilization, and tracking contrasting objects (hands) moving over a textured background.

  19. Impact of Cyclone Track Features and Tidal Phase Shift upon Surge Characteristics in the Bay of Bengal along the Bangladesh Coast

    Directory of Open Access Journals (Sweden)

    Mohammad Asad Hussain

    2017-11-01

    Full Text Available The impact of cyclone track features (e.g., cyclone translation speed, cyclone path and cyclone landfall crossing angle in combination with tidal phase shift upon surge characteristics have been investigated at the Bay of Bengal along the Bangladesh coast. A two-dimensional hydrodynamic model in a horizontal direction (2DH coupled with a storm-surge model has been employed for the study. Numerical experiments with three different cyclone translation speeds show that when the surge height is directly forced by the cyclonic wind speed especially within the RWM (Radius of Maximum Wind, faster translation speed produces reduced surge height as the cyclone gets less time to force the water. On the other hand, at locations outside the RMW, surge waves travel as a propagating long wave where higher surges are produced by faster moving cyclones. It is found that surge arrival times are more and more affected by tidal phase when cyclone translation speed is reduced. Analysis of seven hypothetical parallel cyclone paths show that local bathymetry and complex coastline configurations strongly influence the surge height and surge arrival time along the Bangladesh coast. From the analyses of cyclone landfall crossing angles at the Khulna and Chittagong coasts, it is observed that surge durations are the smallest at both the coasts when the coastline crossing angles are the smallest.

  20. 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.

  1. 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.

  2. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    OpenAIRE

    Dat Tien Nguyen; Ki Wan Kim; Hyung Gil Hong; Ja Hyung Koo; Min Cheol Kim; Kang Ryoung Park

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has ...

  3. 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.

  4. Video Editing System

    Science.gov (United States)

    Schlecht, Leslie E.; Kutler, Paul (Technical Monitor)

    1998-01-01

    This is a proposal for a general use system based, on the SGI IRIS workstation platform, for recording computer animation to videotape. In addition, this system would provide features for simple editing and enhancement. Described here are a list of requirements for the system, and a proposed configuration including the SGI VideoLab Integrator, VideoMedia VLAN animation controller and the Pioneer rewritable laserdisc recorder.

  5. Contextual analysis of videos

    CERN Document Server

    Thida, Myo; Monekosso, Dorothy

    2013-01-01

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

  6. Digital Video Teach Yourself VISUALLY

    CERN Document Server

    Watson, Lonzell

    2010-01-01

    Tips and techniques for shooting and sharing superb digital videos. Never before has video been more popular-or more accessible to the home photographer. Now you can create YouTube-worthy, professional-looking video, with the help of this richly illustrated guide. In a straightforward, simple, highly visual format, Teach Yourself VISUALLY Digital Video demystifies the secrets of great video. With colorful screenshots and illustrations plus step-by-step instructions, the book explains the features of your camera and their capabilities, and shows you how to go beyond "auto" to manually

  7. Innovative Solution to Video Enhancement

    Science.gov (United States)

    2001-01-01

    Through a licensing agreement, Intergraph Government Solutions adapted a technology originally developed at NASA's Marshall Space Flight Center for enhanced video imaging by developing its Video Analyst(TM) System. Marshall's scientists developed the Video Image Stabilization and Registration (VISAR) technology to help FBI agents analyze video footage of the deadly 1996 Olympic Summer Games bombing in Atlanta, Georgia. VISAR technology enhanced nighttime videotapes made with hand-held camcorders, revealing important details about the explosion. Intergraph's Video Analyst System is a simple, effective, and affordable tool for video enhancement and analysis. The benefits associated with the Video Analyst System include support of full-resolution digital video, frame-by-frame analysis, and the ability to store analog video in digital format. Up to 12 hours of digital video can be stored and maintained for reliable footage analysis. The system also includes state-of-the-art features such as stabilization, image enhancement, and convolution to help improve the visibility of subjects in the video without altering underlying footage. Adaptable to many uses, Intergraph#s Video Analyst System meets the stringent demands of the law enforcement industry in the areas of surveillance, crime scene footage, sting operations, and dash-mounted video cameras.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Alexánder Ceballos

    2009-01-01

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

  10. Camcorder 101: Buying and Using Video Cameras.

    Science.gov (United States)

    Catron, Louis E.

    1991-01-01

    Lists nine practical applications of camcorders to theater companies and programs. Discusses the purchase of video gear, camcorder features, accessories, the use of the camcorder in the classroom, theater management, student uses, and video production. (PRA)

  11. Video Player Keyboard Shortcuts: MedlinePlus

    Science.gov (United States)

    ... of this page: https://medlineplus.gov/hotkeys.html Video Player Keyboard Shortcuts To use the sharing features ... of accessible keyboard shortcuts for our latest Health videos on the MedlinePlus site. These shortcuts allow you ...

  12. Children's Video Games as Interactive Racialization

    OpenAIRE

    Martin, Cathlena

    2008-01-01

    Cathlena Martin explores in her paper "Children's Video Games as Interactive Racialization" selected children's video games. Martin argues that children's video games often act as reinforcement for the games' television and film counterparts and their racializing characteristics and features. In Martin's analysis the video games discussed represent media through which to analyze racial identities and ideologies. In making the case for positive female minority leads in children's video games, ...

  13. Digital video transcoding for transmission and storage

    CERN Document Server

    Sun, Huifang; Chen, Xuemin

    2004-01-01

    Professionals in the video and multimedia industries need a book that explains industry standards for video coding and how to convert the compressed information between standards. Digital Video Transcoding for Transmission and Storage answers this demand while also supplying the theories and principles of video compression and transcoding technologies. Emphasizing digital video transcoding techniques, this book summarizes its content via examples of practical methods for transcoder implementation. It relates almost all of its featured transcoding technologies to practical applications.This vol

  14. Dual Deep Network for Visual Tracking.

    Science.gov (United States)

    Chi, Zhizhen; Li, Hongyang; Lu, Huchuan; Yang, Minghsuan

    2017-02-15

    Visual tracking addresses the problem of identifying and localizing an unknown target in a video given the target specified by a bounding box in the first frame. In this paper, we propose a dual network to better utilize features among layers for visual tracking. It is observed that features in higher layers encode semantic context while its counterparts in lower layers are sensitive to discriminative appearance. Thus we exploit the hierarchical features in different layers of a deep model and design a dual structure to obtain better feature representation from various streams, which is rarely investigated in previous work. To highlight geometric contours of the target, we integrate the hierarchical feature maps with an edge detector as the coarse prior maps to further embed local details around the target. To leverage the robustness of our dual network, we train it with random patches measuring the similarities between the network activation and target appearance, which serves as a regularization to enforce the dual network to focus on target object. The proposed dual network is updated online in a unique manner based on the observation that the target being tracked in consecutive frames should share more similar feature representations than those in the surrounding background. It is also found that for a target object, the prior maps can help further enhance performance by passing message into the output maps of the dual network. Therefore, an independent component analysis with reference algorithm (ICA-R) is employed to extract target context using prior maps as guidance. Online tracking is conducted by maximizing the posterior estimate on the final maps with stochastic and periodic update. Quantitative and qualitative evaluations on two large-scale benchmark data sets show that the proposed algorithm performs favourably against the stateof- the-arts.

  15. Robust visual multitask tracking via composite sparse model

    Science.gov (United States)

    Jin, Bo; Jing, Zhongliang; Wang, Meng; Pan, Han

    2014-11-01

    Recently, multitask learning was applied to visual tracking by learning sparse particle representations in a joint task, which led to the so-called multitask tracking algorithm (MTT). Although MTT shows impressive tracking performances by mining the interdependencies between particles, the individual feature of each particle is underestimated. The utilized L1,q norm regularization assumes all features are shared between all particles and results in nearly identical representation coefficients in nonsparse rows. We propose a composite sparse multitask tracking algorithm (CSMTT). We develop a composite sparse model to formulate the object appearance as a combination of the shared feature component, the individual feature component, and the outlier component. The composite sparsity is achieved via the L and L1,1 norm minimization, and is optimized by the alternating direction method of multipliers, which provides a favorable reconstruction performance and an impressive computational efficiency. Moreover, a dynamical dictionary updating scheme is proposed to capture appearance changes. CSMTT is tested on real-world video sequences under various challenges, and experimental results show that the composite sparse model achieves noticeable lower reconstruction errors and higher computational speeds than traditional sparse models, and CSMTT has consistently better tracking performances against seven state-of-the-art trackers.

  16. Siamese convolutional networks for tracking the spine motion

    Science.gov (United States)

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

    2017-09-01

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

  17. A Study of Relationships among Technical, Tactical, Physical Parameters and Final Outcomes in Elite Soccer Matches as Analyzed by a Semiautomatic Video Tracking System.

    Science.gov (United States)

    Filetti, Cristoforo; Ruscello, Bruno; D'Ottavio, Stefano; Fanelli, Vito

    2017-06-01

    The performance of a soccer team depends on many factors such as decision-making, cognitive and physical skills, and dynamic ever-changing space-time interactions between teammate and opponents in relation to the ball. Seventy ( n = 70) matches of the Italian SERIE A season 2013-2014 were investigated to analyze the mean performance of 360 players in terms of physical (physical efficiency index; PEI) and technical-tactical (technical efficiency index; TEI) standpoints. Using a semiautomatic video analysis system that has incorporated new parameters able to measure technical-tactical and physical efficiency (Patent IB2010/002593, 2011-ISA), the correlation between these new variables and how much it relates to the likelihood of winning were verified. Correlations between TEI and PEI were significant ( n = 140, r = .60, p < .001), and TEI showed a higher likelihood of winning than PEI factors ( p < .0001 vs. .0001, CI 95% [1.64, 3.00] vs. [1.28, 2.07]). Higher TEI and TEI + PEI differences between the teams were associated with a greater likelihood of winning, but PEI differences were not. Key performance indicators and this performance assessment method might be useful to better understand what determines winning and to assist the overall training process and match management.

  18. Indexed Captioned Searchable Videos: A Learning Companion for STEM Coursework

    Science.gov (United States)

    Tuna, Tayfun; Subhlok, Jaspal; Barker, Lecia; Shah, Shishir; Johnson, Olin; Hovey, Christopher

    2017-01-01

    Videos of classroom lectures have proven to be a popular and versatile learning resource. A key shortcoming of the lecture video format is accessing the content of interest hidden in a video. This work meets this challenge with an advanced video framework featuring topical indexing, search, and captioning (ICS videos). Standard optical character…

  19. Digital video.

    Science.gov (United States)

    Johnson, Don; Johnson, Mike

    2004-04-01

    The process of digital capture, editing, and archiving video has become an important aspect of documenting arthroscopic surgery. Recording the arthroscopic findings before and after surgery is an essential part of the patient's medical record. The hardware and software has become more reasonable to purchase, but the learning curve to master the software is steep. Digital video is captured at the time of arthroscopy to a hard disk, and written to a CD at the end of the operative procedure. The process of obtaining video of open procedures is more complex. Outside video of the procedure is recorded on digital tape with a digital video camera. The camera must be plugged into a computer to capture the video on the hard disk. Adobe Premiere software is used to edit the video and render the finished video to the hard drive. This finished video is burned onto a CD. We outline the choice of computer hardware and software for the manipulation of digital video. The techniques of backup and archiving the completed projects and files also are outlined. The uses of digital video for education and the formats that can be used in PowerPoint presentations are discussed.

  20. A new video programme

    CERN Multimedia

    CERN video productions

    2011-01-01

    "What's new @ CERN?", a new monthly video programme, will be broadcast on the Monday of every month on webcast.cern.ch. Aimed at the general public, the programme will cover the latest CERN news, with guests and explanatory features. Tune in on Monday 3 October at 4 pm (CET) to see the programme in English, and then at 4:20 pm (CET) for the French version.   var flash_video_player=get_video_player_path(); insert_player_for_external('Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0753-kbps-640x360-25-fps-audio-64-kbps-44-kHz-stereo', 'mms://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-Multirate-200-to-753-kbps-640x360-25-fps.wmv', 'false', 480, 360, 'https://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-posterframe-640x360-at-10-percent.jpg', '1383406', true, 'Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0600-kbps-maxH-360-25-fps-...

  1. Fast Aerial Video Stitching

    Directory of Open Access Journals (Sweden)

    Jing Li

    2014-10-01

    Full Text Available The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS. In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

  2. Effectiveness of an Automatic Tracking Software in Underwater Motion Analysis

    Directory of Open Access Journals (Sweden)

    Fabrício A. Magalhaes

    2013-12-01

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

  3. 3-D model-based frame interpolation for distributed video coding of static scenes.

    Science.gov (United States)

    Maitre, Matthieu; Guillemot, Christine; Morin, Luce

    2007-05-01

    This paper addresses the problem of side information extraction for distributed coding of videos captured by a camera moving in a 3-D static environment. Examples of targeted applications are augmented reality, remote-controlled robots operating in hazardous environments, or remote exploration by drones. It explores the benefits of the structure-from-motion paradigm for distributed coding of this type of video content. Two interpolation methods constrained by the scene geometry, based either on block matching along epipolar lines or on 3-D mesh fitting, are first developed. These techniques are based on a robust algorithm for sub-pel matching of feature points, which leads to semi-dense correspondences between key frames. However, their rate-distortion (RD) performances are limited by misalignments between the side information and the actual Wyner-Ziv (WZ) frames due to the assumption of linear motion between key frames. To cope with this problem, two feature point tracking techniques are introduced, which recover the camera parameters of the WZ frames. A first technique, in which the frames remain encoded separately, performs tracking at the decoder and leads to significant RD performance gains. A second technique further improves the RD performances by allowing a limited tracking at the encoder. As an additional benefit, statistics on tracks allow the encoder to adapt the key frame frequency to the video motion content.

  4. Tracking people by learning their appearance.

    Science.gov (United States)

    Ramanan, Deva; Forsyth, David A; Zisserman, Andrew

    2007-01-01

    An open vision problem is to automatically track the articulations of people from a video sequence. This problem is difficult because one needs to determine both the number of people in each frame and estimate their configurations. But, finding people and localizing their limbs is hard because people can move fast and unpredictably, can appear in a variety of poses and clothes, and are often surrounded by limb-like clutter. We develop a completely automatic system that works in two stages; it first builds a model of appearance of each person in a video and then it tracks by detecting those models in each frame ("tracking by model-building and detection"). We develop two algorithms that build models; one bottom-up approach groups together candidate body parts found throughout a sequence. We also describe a top-down approach that automatically builds people-models by detecting convenient key poses within a sequence. We finally show that building a discriminative model of appearance is quite helpful since it exploits structure in a background (without background-subtraction). We demonstrate the resulting tracker on hundreds of thousands of frames of unscripted indoor and outdoor activity, a feature-length film ("Run Lola Run"), and legacy sports footage (from the 2002 World Series and 1998 Winter Olympics). Experiments suggest that our system 1) can count distinct individuals, 2) can identify and track them, 3) can recover when it loses track, for example, if individuals are occluded or briefly leave the view, 4) can identify body configuration accurately, and 5) is not dependent on particular models of human motion.

  5. 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.

  6. Immersive video

    Science.gov (United States)

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

    1996-03-01

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

  7. Registration using natural features for augmented reality systems.

    Science.gov (United States)

    Yuan, M L; Ong, S K; Nee, A Y C

    2006-01-01

    Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have

  8. A unified and efficient framework for court-net sports video analysis using 3D camera modeling

    Science.gov (United States)

    Han, Jungong; de With, Peter H. N.

    2007-01-01

    The extensive amount of video data stored on available media (hard and optical disks) necessitates video content analysis, which is a cornerstone for different user-friendly applications, such as, smart video retrieval and intelligent video summarization. This paper aims at finding a unified and efficient framework for court-net sports video analysis. We concentrate on techniques that are generally applicable for more than one sports type to come to a unified approach. To this end, our framework employs the concept of multi-level analysis, where a novel 3-D camera modeling is utilized to bridge the gap between the object-level and the scene-level analysis. The new 3-D camera modeling is based on collecting features points from two planes, which are perpendicular to each other, so that a true 3-D reference is obtained. Another important contribution is a new tracking algorithm for the objects (i.e. players). The algorithm can track up to four players simultaneously. The complete system contributes to summarization by various forms of information, of which the most important are the moving trajectory and real-speed of each player, as well as 3-D height information of objects and the semantic event segments in a game. We illustrate the performance of the proposed system by evaluating it for a variety of court-net sports videos containing badminton, tennis and volleyball, and we show that the feature detection performance is above 92% and events detection about 90%.

  9. A novel visual saliency detection method for infrared video sequences

    Science.gov (United States)

    Wang, Xin; Zhang, Yuzhen; Ning, Chen

    2017-12-01

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

  10. Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting.

    Science.gov (United States)

    Morais, Pedro; Marchi, Alberto; Bogaert, Julie A; Dresselaers, Tom; Heyde, Brecht; D'hooge, Jan; Bogaert, Jan

    2017-02-17

    Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising technique for quantification of myocardial strain from steady-state free precession (SSFP) cine images. We sought to determine the variability of CMR-FT using a non-rigid elastic registration algorithm recently available in a commercial software package (Segment, Medviso) in a real-life clinical setting. Firstly, we studied the variability in a healthy volunteer who underwent 10 CMR studies over five consecutive days. Secondly, 10 patients were selected from our CMR database yielding normal findings (normal group). Finally, we prospectively studied 10 patients with known or suspected myocardial pathology referred for further investigation to CMR (patient group). In the patient group a second study was performed respecting an interval of 30 min between studies. All studies were manually segmented at the end-diastolic phase by three observers. In all subjects left ventricular (LV) circumferential and radial strain were calculated in the short-axis direction (EccSAX and ErrSAX, respectively) and longitudinal strain in the long-axis direction (EllLAX). The level of CMR experience of the observers was 2 weeks, 6 months and >20 years. Mean contouring time was 7 ± 1 min, mean FT calculation time 13 ± 2 min. Intra- and inter-observer variability was good to excellent with an coefficient of reproducibility (CR) ranging 1.6% to 11.5%, and 1.7% to 16.0%, respectively and an intraclass correlation coefficient (ICC) ranging 0.89 to 1.00 and 0.74 to 0.99, respectively. Variability considerably increased in the test-retest setting with a CR ranging 4.2% to 29.1% and an ICC ranging 0.66 to 0.95 in the patient group. Variability was not influenced by level of expertise of the observers. Neither did the presence of myocardial pathology at CMR negatively impact variability. However, compared to global myocardial strain, segmental myocardial strain variability increased with a factor

  11. Tracking Eyes using Shape and Appearance

    DEFF Research Database (Denmark)

    Hansen, Dan Witzner; Nielsen, Mads; Hansen, John Paulin

    2002-01-01

    We propose a non-intrusive eye tracking system intended for the use of everyday gaze typing using web cameras. We argue that high precision in gaze tracking is not needed for on-screen typing due to natural language redundancy. This facilitates the use of low-cost video components for advanced...... multi-modal interactions based on video tracking systems. Robust methods are needed to track the eyes using web cameras due to the poor image quality. A real-time tracking scheme using a mean-shift color tracker and an Active Appearance Model of the eye is proposed. From this model, it is possible...

  12. Sign Language Video Processing for Text Detection in Hindi Language

    Directory of Open Access Journals (Sweden)

    Rashmi B Hiremath

    2016-10-01

    Full Text Available Sign language is a way of expressing yourself with your body language, where every bit of ones expressions, goals, or sentiments are conveyed by physical practices, for example, outward appearances, body stance, motions, eye movements, touch and the utilization of space. Non-verbal communication exists in both creatures and people, yet this article concentrates on elucidations of human non-verbal or sign language interpretation into Hindi textual expression. The proposed method of implementation utilizes the image processing methods and synthetic intelligence strategies to get the goal of sign video recognition. To carry out the proposed task implementation it uses image processing methods such as frame analysing based tracking, edge detection, wavelet transform, erosion, dilation, blur elimination, noise elimination, on training videos. It also uses elliptical Fourier descriptors called SIFT for shape feature extraction and most important part analysis for feature set optimization and reduction. For result analysis, this paper uses different category videos such as sign of weeks, months, relations etc. Database of extracted outcomes are compared with the video fed to the system as a input of the signer by a trained unclear inference system.

  13. Dense Trajectories and DHOG for Classification of Viewpoints from Echocardiogram Videos

    Directory of Open Access Journals (Sweden)

    Liqin Huang

    2016-01-01

    Full Text Available In echo-cardiac clinical computer-aided diagnosis, an important step is to automatically classify echocardiography videos from different angles and different regions. We propose a kind of echocardiography video classification algorithm based on the dense trajectory and difference histograms of oriented gradients (DHOG. First, we use the dense grid method to describe feature characteristics in each frame of echocardiography sequence and then track these feature points by applying the dense optical flow. In order to overcome the influence of the rapid and irregular movement of echocardiography videos and get more robust tracking results, we also design a trajectory description algorithm which uses the derivative of the optical flow to obtain the motion trajectory information and associates the different characteristics (e.g., the trajectory shape, DHOG, HOF, and MBH with embedded structural information of the spatiotemporal pyramid. To avoid “dimension disaster,” we apply Fisher’s vector to reduce the dimension of feature description followed by the SVM linear classifier to improve the final classification result. The average accuracy of echocardiography video classification is 77.12% for all eight viewpoints and 100% for three primary viewpoints.

  14. 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

  15. Robust online face tracking-by-detection

    NARCIS (Netherlands)

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

    2016-01-01

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

  16. 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.

  17. Video games

    OpenAIRE

    Kolář, Vojtěch

    2012-01-01

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

  18. Unusual features of negative leaders' development in natural lightning, according to simultaneous records of current, electric field, luminosity, and high-speed video

    Science.gov (United States)

    Guimaraes, Miguel; Arcanjo, Marcelo; Murta Vale, Maria Helena; Visacro, Silverio

    2017-02-01

    The development of downward and upward leaders that formed two negative cloud-to-ground return strokes in natural lightning, spaced only about 200 µs apart and terminating on ground only a few hundred meters away, was monitored at Morro do Cachimbo Station, Brazil. The simultaneous records of current, close electric field, relative luminosity, and corresponding high-speed video frames (sampling rate of 20,000 frames per second) reveal that the initiation of the first return stroke interfered in the development of the second negative leader, leading it to an apparent continuous development before the attachment, without stepping, and at a regular two-dimensional speed. Based on the experimental data, the formation processes of the two return strokes are discussed, and plausible interpretations for their development are provided.

  19. A GAZE TRACKER AND A GAZE TRACKING METHOD

    DEFF Research Database (Denmark)

    2017-01-01

    A gaze tracker and a computer-implemented method for gaze tracking, comprising the steps of: recording video images of a being's eye such that an eye pupil and a glint on the eye ball caused by a light source () are recorded; processing the video images to compute an offset between the position...... of the predetermined spatial feature and a predetermined position with respect to the glint; by means of the light source such as a display, emitting light from a light pattern at a location selected among a multitude of preconfigured locations of light patterns towards the being's eye; wherein the location...... spatial feature of the being's eye; wherein the above steps are repeated to establish a control loop with the location of the light pattern being controlled via the feedback signal....

  20. CHARACTER RECOGNITION OF VIDEO SUBTITLES\\

    Directory of Open Access Journals (Sweden)

    Satish S Hiremath

    2016-11-01

    Full Text Available An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm

  1. ABOUT SOUNDS IN VIDEO GAMES

    Directory of Open Access Journals (Sweden)

    Denikin Anton A.

    2012-12-01

    Full Text Available The article considers the aesthetical and practical possibilities for sounds (sound design in video games and interactive applications. Outlines the key features of the game sound, such as simulation, representativeness, interactivity, immersion, randomization, and audio-visuality. The author defines the basic terminology in study of game audio, as well as identifies significant aesthetic differences between film sounds and sounds in video game projects. It is an attempt to determine the techniques of art analysis for the approaches in study of video games including aesthetics of their sounds. The article offers a range of research methods, considering the video game scoring as a contemporary creative practice.

  2. Combining Information Sources for Video Retrieval

    NARCIS (Netherlands)

    Westerveld, T.H.W.; Ianeva, T.; Boldareva, L.; de Vries, A.P.; Hiemstra, Djoerd

    The previous video track results demonstrated that it is far from trivial to take advantage of multiple modalities for the video retrieval search task. For almost any query, results based on ASR transcripts have been better than any other run. This year’s main success in our runs is that a

  3. Video Conferencing for a Virtual Seminar Room

    DEFF Research Database (Denmark)

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

    2002-01-01

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

  4. Video Pulses: User-Based Modeling of Interesting Video Segments

    Directory of Open Access Journals (Sweden)

    Markos Avlonitis

    2014-01-01

    Full Text Available We present a user-based method that detects regions of interest within a video in order to provide video skims and video summaries. Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. We are proposing a pulse modeling method, which makes sense of a web video by analyzing users' Replay interactions with the video player. In particular, we have modeled the user information seeking behavior as a time series and the semantic regions as a discrete pulse of fixed width. Then, we have calculated the correlation coefficient between the dynamically detected pulses at the local maximums of the user activity signal and the pulse of reference. We have found that users' Replay activity significantly matches the important segments in information-rich and visually complex videos, such as lecture, how-to, and documentary. The proposed signal processing of user activity is complementary to previous work in content-based video retrieval and provides an additional user-based dimension for modeling the semantics of a social video on the web.

  5. 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 ...

  6. Computational Thinking in Constructionist Video Games

    Science.gov (United States)

    Weintrop, David; Holbert, Nathan; Horn, Michael S.; Wilensky, Uri

    2016-01-01

    Video games offer an exciting opportunity for learners to engage in computational thinking in informal contexts. This paper describes a genre of learning environments called constructionist video games that are especially well suited for developing learners' computational thinking skills. These games blend features of conventional video games with…

  7. Features of the propagation of pseudorandom pulse signals from the shelf to deep water in the presence of gyre formation on the acoustic track

    Science.gov (United States)

    Akulichev, V. A.; Burenin, A. V.; Ladychenko, S. Yu.; Lobanov, V. B.; Morgunov, Yu. N.

    2017-08-01

    The paper discusses the results of an experiment conducted in the Sea of Japan in March 2016 on an acoustic track 194 km long in winter hydrological conditions. The most complex case of propagation of pseudorandom pulse signals from the shelf to deep water in the presence of gyre formation on the acoustic track. An analysis of the experimentally obtained pulse characteristics show that at all points, a maximum, in terms of amplitude, first arrival of acoustic energy is recorded. This is evidence that at a given depth horizon, pulses that have passed the shortest distance through a near-surface sound channel at small angles close to zero are received first. The calculation method of mean sound velocity on the track, based on the satellite data of surface temperature monitoring, is proposed. We expect that the results obtained with this method can be successfully used for the purposes of acoustic range finding and navigation.

  8. Robust video object cosegmentation.

    Science.gov (United States)

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

    2015-10-01

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

  9. 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.

  10. Slab track

    OpenAIRE

    Golob, Tina

    2014-01-01

    The last 160 years has been mostly used conventional track with ballasted bed, sleepers and steel rail. Ensuring the high speed rail traffic, increasing railway track capacities, providing comfortable and safe ride as well as high reliability and availability railway track, has led to development of innovative systems for railway track. The so-called slab track was first built in 1972 and since then, they have developed many different slab track systems around the world. Slab track was also b...

  11. Automated tracking of colloidal clusters with sub-pixel accuracy and precision

    Science.gov (United States)

    van der Wel, Casper; Kraft, Daniela J.

    2017-02-01

    Quantitative tracking of features from video images is a basic technique employed in many areas of science. Here, we present a method for the tracking of features that partially overlap, in order to be able to track so-called colloidal molecules. Our approach implements two improvements into existing particle tracking algorithms. Firstly, we use the history of previously identified feature locations to successfully find their positions in consecutive frames. Secondly, we present a framework for non-linear least-squares fitting to summed radial model functions and analyze the accuracy (bias) and precision (random error) of the method on artificial data. We find that our tracking algorithm correctly identifies overlapping features with an accuracy below 0.2% of the feature radius and a precision of 0.1 to 0.01 pixels for a typical image of a colloidal cluster. Finally, we use our method to extract the three-dimensional diffusion tensor from the Brownian motion of colloidal dimers. , which features invited work from the best early-career researchers working within the scope of Journal of Physics: Condensed Matter. This project is part of the Journal of Physics series’ 50th anniversary celebrations in 2017. Daniela Kraft was selected by the Editorial Board of Journal of Physics: Condensed Matter as an Emerging Leader.

  12. An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points

    Science.gov (United States)

    Shahamatnia, Ehsan; Dorotovič, Ivan; Fonseca, Jose M.; Ribeiro, Rita A.

    2016-03-01

    Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.

  13. Collaborative web-based annotation of video footage of deep-sea life, ecosystems and geological processes

    Science.gov (United States)

    Kottmann, R.; Ratmeyer, V.; Pop Ristov, A.; Boetius, A.

    2012-04-01

    More and more seagoing scientific expeditions use video-controlled research platforms such as Remote Operating Vehicles (ROV), Autonomous Underwater Vehicles (AUV), and towed camera systems. These produce many hours of video material which contains detailed and scientifically highly valuable footage of the biological, chemical, geological, and physical aspects of the oceans. Many of the videos contain unique observations of unknown life-forms which are rare, and which cannot be sampled and studied otherwise. To make such video material online accessible and to create a collaborative annotation environment the "Video Annotation and processing platform" (V-App) was developed. A first solely web-based installation for ROV videos is setup at the German Center for Marine Environmental Sciences (available at http://videolib.marum.de). It allows users to search and watch videos with a standard web browser based on the HTML5 standard. Moreover, V-App implements social web technologies allowing a distributed world-wide scientific community to collaboratively annotate videos anywhere at any time. It has several features fully implemented among which are: • User login system for fine grained permission and access control • Video watching • Video search using keywords, geographic position, depth and time range and any combination thereof • Video annotation organised in themes (tracks) such as biology and geology among others in standard or full screen mode • Annotation keyword management: Administrative users can add, delete, and update single keywords for annotation or upload sets of keywords from Excel-sheets • Download of products for scientific use This unique web application system helps making costly ROV videos online available (estimated cost range between 5.000 - 10.000 Euros per hour depending on the combination of ship and ROV). Moreover, with this system each expert annotation adds instantaneous available and valuable knowledge to otherwise uncharted

  14. Apples to Oranges: Comparing Streaming Video Platforms

    OpenAIRE

    Milewski, Steven; Threatt, Monique

    2017-01-01

    Librarians rely on an ever-increasing variety of platforms to deliver streaming video content to our patrons. These two presentations will examine different aspects of video streaming platforms to gain guidance from the comparison of platforms. The first will examine the accessibility compliance of the various video streaming platforms for users with disabilities by examining accessibility features of the platforms. The second will be a comparison of subject usage of two of the larger video s...

  15. Tracks: Nurses and the Tracking Network

    Centers for Disease Control (CDC) Podcasts

    2012-06-06

    This podcast highlights the utility of the National Environmental Public Health Tracking Network for nurses in a variety of work settings. It features commentary from the American Nurses Association and includes stories from a public health nurse in Massachusetts.  Created: 6/6/2012 by National Center for Environmental Health (NCEH)/Division of Environmental Hazards and Health Effects (DEHHE)/Environmental Health Tracking Branch (EHTB).   Date Released: 6/6/2012.

  16. Music-Guided Video Summarization using Quadratic Assignments

    NARCIS (Netherlands)

    Mensink, T.; Jongstra, T.; Mettes, P.; Snoek, C.G.M.

    2017-01-01

    This paper aims to automatically generate a summary of an unedited video, guided by an externally provided music-track. The tempo, energy and beats in the music determine the choices and cuts in the video summarization. To solve this challenging task, we model video summarization as a quadratic

  17. Recognizing problem video game use.

    Science.gov (United States)

    Porter, Guy; Starcevic, Vladan; Berle, David; Fenech, Pauline

    2010-02-01

    It has been increasingly recognized that some people develop problem video game use, defined here as excessive use of video games resulting in various negative psychosocial and/or physical consequences. The main objectives of the present study were to identify individuals with problem video game use and compare them with those without problem video game use on several variables. An international, anonymous online survey was conducted, using a questionnaire with provisional criteria for problem video game use, which the authors have developed. These criteria reflect the crucial features of problem video game use: preoccupation with and loss of control over playing video games and multiple adverse consequences of this activity. A total of 1945 survey participants completed the survey. Respondents who were identified as problem video game users (n = 156, 8.0%) differed significantly from others (n = 1789) on variables that provided independent, preliminary validation of the provisional criteria for problem video game use. They played longer than planned and with greater frequency, and more often played even though they did not want to and despite believing that they should not do it. Problem video game users were more likely to play certain online role-playing games, found it easier to meet people online, had fewer friends in real life, and more often reported excessive caffeine consumption. People with problem video game use can be identified by means of a questionnaire and on the basis of the present provisional criteria, which require further validation. These findings have implications for recognition of problem video game users among individuals, especially adolescents, who present to mental health services. Mental health professionals need to acknowledge the public health significance of the multiple negative consequences of problem video game use.

  18. Real-time video analysis for retail stores

    Science.gov (United States)

    Hassan, Ehtesham; Maurya, Avinash K.

    2015-03-01

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

  19. 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...

  20. Video Podcasts

    DEFF Research Database (Denmark)

    Nortvig, Anne Mette; Sørensen, Birgitte Holm

    2016-01-01

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

  1. Video enhancement effectiveness for target detection

    Science.gov (United States)

    Simon, Michael; Fischer, Amber; Petrov, Plamen

    2011-05-01

    Unmanned aerial vehicles (UAVs) capture real-time video data of military targets while keeping the warfighter at a safe distance. This keeps soldiers out of harm's way while they perform intelligence, surveillance and reconnaissance (ISR) and close-air support troops in contact (CAS-TIC) situations. The military also wants to use UAV video to achieve force multiplication. One method of achieving effective force multiplication involves fielding numerous UAVs with cameras and having multiple videos processed simultaneously by a single operator. However, monitoring multiple video streams is difficult for operators when the videos are of low quality. To address this challenge, we researched several promising video enhancement algorithms that focus on improving video quality. In this paper, we discuss our video enhancement suite and provide examples of video enhancement capabilities, focusing on stabilization, dehazing, and denoising. We provide results that show the effects of our enhancement algorithms on target detection and tracking algorithms. These results indicate that there is potential to assist the operator in identifying and tracking relevant targets with aided target recognition even on difficult video, increasing the force multiplier effect of UAVs. This work also forms the basis for human factors research into the effects of enhancement algorithms on ISR missions.

  2. An intelligent video framework for homeland protection

    Science.gov (United States)

    Tu, Peter H.; Doretto, Gianfranco; Krahnstoever, Nils O.; Perera, A. G. Amitha; Wheeler, Frederick W.; Liu, Xiaoming; Rittscher, Jens; Sebastian, Thomas B.; Yu, Ting; Harding, Kevin G.

    2007-04-01

    This paper presents an overview of Intelligent Video work currently under development at the GE Global Research Center and other research institutes. The image formation process is discussed in terms of illumination, methods for automatic camera calibration and lessons learned from machine vision. A variety of approaches for person detection are presented. Crowd segmentation methods enabling the tracking of individuals through dense environments such as retail and mass transit sites are discussed. It is shown how signature generation based on gross appearance can be used to reacquire targets as they leave and enter disjoint fields of view. Camera calibration information is used to further constrain the detection of people and to synthesize a top-view, which fuses all camera views into a composite representation. It is shown how site-wide tracking can be performed in this unified framework. Human faces are an important feature as both a biometric identifier and as a method for determining the focus of attention via head pose estimation. It is shown how automatic pan-tilt- zoom control; active shape/appearance models and super-resolution methods can be used to enhance the face capture and analysis problem. A discussion of additional features that can be used for inferring intent is given. These include body-part motion cues and physiological phenomena such as thermal images of the face.

  3. Videography-Based Unconstrained Video Analysis.

    Science.gov (United States)

    Li, Kang; Li, Sheng; Oh, Sangmin; Fu, Yun

    2017-05-01

    Video analysis and understanding play a central role in visual intelligence. In this paper, we aim to analyze unconstrained videos, by designing features and approaches to represent and analyze videography styles in the videos. Videography denotes the process of making videos. The unconstrained videos are defined as the long duration consumer videos that usually have diverse editing artifacts and significant complexity of contents. We propose to construct a videography dictionary, which can be utilized to represent every video clip as a sequence of videography words. In addition to semantic features, such as foreground object motion and camera motion, we also incorporate two novel interpretable features to characterize videography, including the scale information and the motion correlations. We then demonstrate that, by using statistical analysis methods, the unique videography signatures extracted from different events can be automatically identified. For real-world applications, we explore the use of videography analysis for three types of applications, including content-based video retrieval, video summarization (both visual and textual), and videography-based feature pooling. In the experiments, we evaluate the performance of our approach and other methods on a large-scale unconstrained video dataset, and show that the proposed approach significantly benefits video analysis in various ways.

  4. Video Primal Sketch: A Unified Middle-Level Representation for Video

    OpenAIRE

    Han, Zhi; Xu, Zongben; Zhu, Song-Chun

    2015-01-01

    This paper presents a middle-level video representation named Video Primal Sketch (VPS), which integrates two regimes of models: i) sparse coding model using static or moving primitives to explicitly represent moving corners, lines, feature points, etc., ii) FRAME /MRF model reproducing feature statistics extracted from input video to implicitly represent textured motion, such as water and fire. The feature statistics include histograms of spatio-temporal filters and velocity distributions. T...

  5. ANNOTATION SUPPORTED OCCLUDED OBJECT TRACKING

    Directory of Open Access Journals (Sweden)

    Devinder Kumar

    2012-08-01

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

  6. Calculating track thrust with track functions

    Science.gov (United States)

    Chang, Hsi-Ming; Procura, Massimiliano; Thaler, Jesse; Waalewijn, Wouter J.

    2013-08-01

    In e+e- event shapes studies at LEP, two different measurements were sometimes performed: a “calorimetric” measurement using both charged and neutral particles and a “track-based” measurement using just charged particles. Whereas calorimetric measurements are infrared and collinear safe, and therefore calculable in perturbative QCD, track-based measurements necessarily depend on nonperturbative hadronization effects. On the other hand, track-based measurements typically have smaller experimental uncertainties. In this paper, we present the first calculation of the event shape “track thrust” and compare to measurements performed at ALEPH and DELPHI. This calculation is made possible through the recently developed formalism of track functions, which are nonperturbative objects describing how energetic partons fragment into charged hadrons. By incorporating track functions into soft-collinear effective theory, we calculate the distribution for track thrust with next-to-leading logarithmic resummation. Due to a partial cancellation between nonperturbative parameters, the distributions for calorimeter thrust and track thrust are remarkably similar, a feature also seen in LEP data.

  7. Track-based event recognition in a realistic crowded environment

    Science.gov (United States)

    van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

    2014-10-01

    Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

  8. Deep video deblurring

    KAUST Repository

    Su, Shuochen

    2016-11-25

    Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on aligning nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task which requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-to-end to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high framerate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

  9. Video Game Playing and Gambling in Adolescents: Common Risk Factors

    Science.gov (United States)

    Wood, Richard T. A.; Gupta, Rina; Griffiths, Mark

    2004-01-01

    Video games and gambling often contain very similar elements with both providing intermittent rewards and elements of randomness. Furthermore, at a psychological and behavioral level, slot machine gambling, video lottery terminal (VLT) gambling and video game playing share many of the same features. Despite the similarities between video game…

  10. Using MPEG DASH SRD for zoomable and navigable video

    NARCIS (Netherlands)

    D'Acunto, L.; Berg, J. van den; Thomas, E.; Niamut, O.A.

    2016-01-01

    This paper presents a video streaming client implementation that makes use of the Spatial Relationship Description (SRD) feature of the MPEG-DASH standard, to provide a zoomable and navigable video to an end user. SRD allows a video streaming client to request spatial subparts of a particular video

  11. Satisfaction with Online Teaching Videos: A Quantitative Approach

    Science.gov (United States)

    Meseguer-Martinez, Angel; Ros-Galvez, Alejandro; Rosa-Garcia, Alfonso

    2017-01-01

    We analyse the factors that determine the number of clicks on the "Like" button in online teaching videos, with a sample of teaching videos in the area of Microeconomics across Spanish-speaking countries. The results show that users prefer short online teaching videos. Moreover, some features of the videos have a significant impact on…

  12. Video Game Structural Characteristics: A New Psychological Taxonomy

    Science.gov (United States)

    King, Daniel; Delfabbro, Paul; Griffiths, Mark

    2010-01-01

    Excessive video game playing behaviour may be influenced by a variety of factors including the structural characteristics of video games. Structural characteristics refer to those features inherent within the video game itself that may facilitate initiation, development and maintenance of video game playing over time. Numerous structural…

  13. 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

  14. Tracking a Subset of Skeleton Joints: An Effective Approach towards Complex Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Muhammad Latif Anjum

    2017-01-01

    Full Text Available We present a robust algorithm for complex human activity recognition for natural human-robot interaction. The algorithm is based on tracking the position of selected joints in human skeleton. For any given activity, only a few skeleton joints are involved in performing the activity, so a subset of joints contributing the most towards the activity is selected. Our approach of tracking a subset of skeleton joints (instead of tracking the whole skeleton is computationally efficient and provides better recognition accuracy. We have developed both manual and automatic approaches for the selection of these joints. The position of the selected joints is tracked for the duration of the activity and is used to construct feature vectors for each activity. Once the feature vectors have been constructed, we use a Support Vector Machines (SVM multiclass classifier for training and testing the algorithm. The algorithm has been tested on a purposely built dataset of depth videos recorded using Kinect camera. The dataset consists of 250 videos of 10 different activities being performed by different users. Experimental results show classification accuracy of 83% when tracking all skeleton joints, 95% when using manual selection of subset joints, and 89% when using automatic selection of subset joints.

  15. Role of intraoperative indocyanine green video-angiography to identify small, posterior fossa arteriovenous malformations mimicking cavernous angiomas. Technical report and review of the literature on common features of these cerebral vascular malformations.

    Science.gov (United States)

    Barbagallo, Giuseppe M V; Certo, Francesco; Caltabiano, Rosario; Chiaramonte, Ignazio; Albanese, Vincenzo; Visocchi, Massimiliano

    2015-11-01

    To illustrate the usefulness of intraoperative indocyanine green videoangiography (ICG-VA) to identify the nidus and feeders of a small cerebellar AVM resembling a cavernous hemangioma. To review the unique features regarding the overlay between these two vascular malformations and to highlight the importance to identify with ICG-VA, and treat accordingly, the arterial and venous vessels of the AVM. A 36-year old man presented with bilateral cerebellar hemorrhage. MRI was equivocal in showing an underlying vascular malformation but angiography demonstrated a small, Spetzler-Martin grade I AVM. Surgical resection of the AVM with the aid of intraoperative ICG-VA was performed. After hematoma evacuation, pre-resection ICG-VA did not reveal tortuous arterial and venous vessels in keeping with a typical AVM but rather an unusual blackberry-like image resembling a cavernous hemangioma, with tiny surrounding vessels. Such intraoperative appearance, which could also be the consequence of a "leakage" of fluorescent dye from the nidal pathological vessels, with absent blood-brain barrier, into the surrounding parenchymal pathological capillary network, is important to be recognized as an unusual AVM appearance. Post-resection ICG-VA confirmed the AVM removal, as also shown by postoperative and 3-month follow-up DSAs. Despite technical limitations associated with ICG-VA in post-hemorrhage AVMs, this case together with the intraoperative video, demonstrates the useful role of ICG-VA in identifying small AVMs with peculiar features. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Audiovisual data fusion for successive speakers tracking

    OpenAIRE

    Labourey, Quentin; Aycard, Olivier; Pellerin, Denis; Rombaut, Michèle

    2014-01-01

    International audience; In this paper, a human speaker tracking method on audio and video data is presented. It is applied to con- versation tracking with a robot. Audiovisual data fusion is performed in a two-steps process. Detection is performed independently on each modality: face detection based on skin color on video data and sound source localization based on the time delay of arrival on audio data. The results of those detection processes are then fused thanks to an adaptation of bayes...

  17. Automatic face detection and tracking based on Adaboost with camshift algorithm

    Science.gov (United States)

    Lin, Hui; Long, JianFeng

    2011-10-01

    With the development of information technology, video surveillance is widely used in security monitoring and identity recognition. For most of pure face tracking algorithms are hard to specify the initial location and scale of face automatically, this paper proposes a fast and robust method to detect and track face by combining adaboost with camshift algorithm. At first, the location and scale of face is specified by adaboost algorithm based on Haar-like features and it will be conveyed to the initial search window automatically. Then, we apply camshift algorithm to track face. The experimental results based on OpenCV software yield good results, even in some special circumstances, such as light changing and face rapid movement. Besides, by drawing out the tracking trajectory of face movement, some abnormal behavior events can be analyzed.

  18. 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.

  19. 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.

  20. Pixel-Level and Robust Vibration Source Sensing in High-Frame-Rate Video Analysis

    Directory of Open Access Journals (Sweden)

    Mingjun Jiang

    2016-11-01

    Full Text Available We investigate the effect of appearance variations on the detectability of vibration feature extraction with pixel-level digital filters for high-frame-rate videos. In particular, we consider robust vibrating object tracking, which is clearly different from conventional appearance-based object tracking with spatial pattern recognition in a high-quality image region of a certain size. For 512 × 512 videos of a rotating fan located at different positions and orientations and captured at 2000 frames per second with different lens settings, we verify how many pixels are extracted as vibrating regions with pixel-level digital filters. The effectiveness of dynamics-based vibration features is demonstrated by examining the robustness against changes in aperture size and the focal condition of the camera lens, the apparent size and orientation of the object being tracked, and its rotational frequency, as well as complexities and movements of background scenes. Tracking experiments for a flying multicopter with rotating propellers are also described to verify the robustness of localization under complex imaging conditions in outside scenarios.

  1. An Approach to Streaming Video Segmentation With Sub-Optimal Low-Rank Decomposition.

    Science.gov (United States)

    Li, Chenglong; Lin, Liang; Zuo, Wangmeng; Wang, Wenzhong; Tang, Jin

    2016-05-01

    This paper investigates how to perform robust and efficient video segmentation while suppressing the effects of data noises and/or corruptions, and an effective approach is introduced to this end. First, a general algorithm, called sub-optimal low-rank decomposition (SOLD), is proposed to pursue the low-rank representation for video segmentation. Given the data matrix formed by supervoxel features of an observed video sequence, SOLD seeks a sub-optimal solution by making the matrix rank explicitly determined. In particular, the representation coefficient matrix with the fixed rank can be decomposed into two sub-matrices of low rank, and then we iteratively optimize them with closed-form solutions. Moreover, we incorporate a discriminative replication prior into SOLD based on the observation that small-size video patterns tend to recur frequently within the same object. Second, based on SOLD, we present an efficient inference algorithm to perform streaming video segmentation in both unsupervised and interactive scenarios. More specifically, the constrained normalized-cut algorithm is adopted by incorporating the low-rank representation with other low level cues and temporal consistent constraints for spatio-temporal segmentation. Extensive experiments on two public challenging data sets VSB100 and SegTrack suggest that our approach outperforms other video segmentation approaches in both accuracy and efficiency.

  2. 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.

  3. Akademisk video

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2017-01-01

    Dette kapitel har fokus på metodiske problemstillinger, der opstår i forhold til at bruge (digital) video i forbindelse med forskningskommunikation, ikke mindst online. Video har længe været benyttet i forskningen til dataindsamling og forskningskommunikation. Med digitaliseringen og internettet er...... der dog opstået nye muligheder og udfordringer i forhold til at formidle og distribuere forskningsresultater til forskellige målgrupper via video. Samtidig er klassiske metodologiske problematikker som forskerens positionering i forhold til det undersøgte stadig aktuelle. Både klassiske og nye...... problemstillinger diskuteres i kapitlet, som rammesætter diskussionen ud fra forskellige positioneringsmuligheder: formidler, historiefortæller, eller dialogist. Disse positioner relaterer sig til genrer inden for ’akademisk video’. Afslutningsvis præsenteres en metodisk værktøjskasse med redskaber til planlægning...

  4. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...... World Videos. The workshops were run on December 4, 2016, in Cancun in Mexico. The two workshops together received 13 papers. Each paper was then reviewed by at least two expert reviewers in the field. In all, 11 papers were accepted to be presented at the workshops. The topics covered in the papers...

  5. MedlinePlus FAQ: Is audio description available for videos on MedlinePlus?

    Science.gov (United States)

    ... audiodescription.html Question: Is audio description available for videos on MedlinePlus? To use the sharing features on ... page, please enable JavaScript. Answer: Audio description of videos helps make the content of videos accessible to ...

  6. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real W...

  7. Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

    Science.gov (United States)

    Zhao, Zijian; Voros, Sandrine; Weng, Ying; Chang, Faliang; Li, Ruijian

    2017-12-01

    Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

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

    Directory of Open Access Journals (Sweden)

    Huang Tian

    2014-10-01

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

  9. Simultaneous Eye Tracking and Blink Detection with Interactive Particle Filters

    Directory of Open Access Journals (Sweden)

    Mohan M. Trivedi

    2008-04-01

    Full Text Available We present a system that simultaneously tracks eyes and detects eye blinks. Two interactive particle filters are used for this purpose, one for the closed eyes and the other one for the open eyes. Each particle filter is used to track the eye locations as well as the scales of the eye subjects. The set of particles that gives higher confidence is defined as the primary set and the other one is defined as the secondary set. The eye location is estimated by the primary particle filter, and whether the eye status is open or closed is also decided by the label of the primary particle filter. When a new frame comes, the secondary particle filter is reinitialized according to the estimates from the primary particle filter. We use autoregression models for describing the state transition and a classification-based model for measuring the observation. Tensor subspace analysis is used for feature extraction which is followed by a logistic regression model to give the posterior estimation. The performance is carefully evaluated from two aspects: the blink detection rate and the tracking accuracy. The blink detection rate is evaluated using videos from varying scenarios, and the tracking accuracy is given by comparing with the benchmark data obtained using the Vicon motion capturing system. The setup for obtaining benchmark data for tracking accuracy evaluation is presented and experimental results are shown. Extensive experimental evaluations validate the capability of the algorithm.

  10. Video consultation use by Australian general practitioners: video vignette study.

    Science.gov (United States)

    Jiwa, Moyez; Meng, Xingqiong

    2013-06-19

    There is unequal access to health care in Australia, particularly for the one-third of the population living in remote and rural areas. Video consultations delivered via the Internet present an opportunity to provide medical services to those who are underserviced, but this is not currently routine practice in Australia. There are advantages and shortcomings to using video consultations for diagnosis, and general practitioners (GPs) have varying opinions regarding their efficacy. The aim of this Internet-based study was to explore the attitudes of Australian GPs toward video consultation by using a range of patient scenarios presenting different clinical problems. Overall, 102 GPs were invited to view 6 video vignettes featuring patients presenting with acute and chronic illnesses. For each vignette, they were asked to offer a differential diagnosis and to complete a survey based on the theory of planned behavior documenting their views on the value of a video consultation. A total of 47 GPs participated in the study. The participants were younger than Australian GPs based on national data, and more likely to be working in a larger practice. Most participants (72%-100%) agreed on the differential diagnosis in all video scenarios. Approximately one-third of the study participants were positive about video consultations, one-third were ambivalent, and one-third were against them. In all, 91% opposed conducting a video consultation for the patient with symptoms of an acute myocardial infarction. Inability to examine the patient was most frequently cited as the reason for not conducting a video consultation. Australian GPs who were favorably inclined toward video consultations were more likely to work in larger practices, and were more established GPs, especially in rural areas. The survey results also suggest that the deployment of video technology will need to focus on follow-up consultations. Patients with minor self-limiting illnesses and those with medical

  11. Online Tracking

    Science.gov (United States)

    ... for other purposes, such as research, measurement, and fraud prevention. Mobile browsers work much like traditional web ... users’ Do Not Track preferences. Can I block online tracking? Consumers can learn about tracker-blocking browser ...

  12. 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...

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

    DEFF Research Database (Denmark)

    2014-01-01

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

  14. Telemetry and Communication IP Video Player

    Science.gov (United States)

    OFarrell, Zachary L.

    2011-01-01

    Aegis Video Player is the name of the video over IP system for the Telemetry and Communications group of the Launch Services Program. Aegis' purpose is to display video streamed over a network connection to be viewed during launches. To accomplish this task, a VLC ActiveX plug-in was used in C# to provide the basic capabilities of video streaming. The program was then customized to be used during launches. The VLC plug-in can be configured programmatically to display a single stream, but for this project multiple streams needed to be accessed. To accomplish this, an easy to use, informative menu system was added to the program to enable users to quickly switch between videos. Other features were added to make the player more useful, such as watching multiple videos and watching a video in full screen.

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

    Science.gov (United States)

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

    2007-04-01

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

  16. Digital Video Stabilization with Inertial Fusion

    OpenAIRE

    Freeman, William John

    2013-01-01

    As computing power becomes more and more available, robotic systems are moving away from active sensors for environmental awareness and transitioning into passive vision sensors.  With the advent of teleoperation and real-time video tracking of dynamic environments, the need to stabilize video onboard mobile robots has become more prevalent. This thesis presents a digital stabilization method that incorporates inertial fusion with a Kalman filter.  The camera motion is derived visually by tra...

  17. Cultural and Developmental Influences on Overt Visual Attention to Videos.

    Science.gov (United States)

    Kardan, Omid; Shneidman, Laura; Krogh-Jespersen, Sheila; Gaskins, Suzanne; Berman, Marc G; Woodward, Amanda

    2017-09-12

    Top-down influences on observers' overt attention and how they interact with the features of the visual environment have been extensively investigated, but the cultural and developmental aspects of these modulations have been understudied. In this study we investigated these effects for US and Yucatec Mayan infants, children, and adults. Mayan and US participants viewed videos of two actors performing daily Mayan and US tasks in the foreground and the background while their eyes were tracked. Our region of interest analysis showed that viewers from the US looked significantly less at the foreground activity and spent more time attending to the 'contextual' information (static background) compared to Mayans. To investigate how and what visual features of videos were attended to in a comprehensive manner, we used multivariate methods which showed that visual features are attended to differentially by each culture. Additionally, we found that Mayan and US infants utilize the same eye-movement patterns in which fixation duration and saccade amplitude are altered in response to the visual stimuli independently. However, a bifurcation happens by age 6, at which US participants diverge and engage in eye-movement patterns where fixation durations and saccade amplitudes are altered simultaneously.

  18. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...... include: re-identification, consumer behavior analysis, utilizing pupillary response for task difficulty measurement, logo detection, saliency prediction, classification of facial expressions, face recognition, face verification, age estimation, super-resolution, pose estimation, and pain recognition...

  19. Video Analytics

    DEFF Research Database (Denmark)

    include: re-identification, consumer behavior analysis, utilizing pupillary response for task difficulty measurement, logo detection, saliency prediction, classification of facial expressions, face recognition, face verification, age estimation, super-resolution, pose estimation, and pain recognition......This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...

  20. Mining Videos for Features that Drive Attention

    Science.gov (United States)

    2015-04-01

    1_14 311 312 F. Baluch and L. Itti known as a saccade , to bring the area of interest into alignment with the fovea.Within the fovea too, attention can...infer attentional allocation. The eye traces recorded during the viewing of the stimuli by the subjects were parsed into saccades based on a threshold...of velocity as described before [1]. A total of 11,430 saccades were extracted and analyzed. Using the saliency model, we were able to extract

  1. Particle tracking

    CERN Document Server

    Safarík, K; Newby, J; Sørensen, P

    2002-01-01

    In this lecture we will present a short historical overview of different tracking detectors. Then we will describe currently used gaseous and silicon detectors and their performance. In the second part we will discuss how to estimate tracking precision, how to design a tracker and how the track finding works. After a short description of the LHC the main attention is drawn to the ALICE experiment since it is dedicated to study new states in hadronic matter at the LHC. The ALICE tracking procedure is discussed in detail. A comparison to the tracking in ATLAS, CMS and LHCb is given. (5 refs).

  2. User-oriented summary extraction for soccer video based on multimodal analysis

    Science.gov (United States)

    Liu, Huayong; Jiang, Shanshan; He, Tingting

    2011-11-01

    An advanced user-oriented summary extraction method for soccer video is proposed in this work. Firstly, an algorithm of user-oriented summary extraction for soccer video is introduced. A novel approach that integrates multimodal analysis, such as extraction and analysis of the stadium features, moving object features, audio features and text features is introduced. By these features the semantic of the soccer video and the highlight mode are obtained. Then we can find the highlight position and put them together by highlight degrees to obtain the video summary. The experimental results for sports video of world cup soccer games indicate that multimodal analysis is effective for soccer video browsing and retrieval.

  3. Production of 360° video : Introduction to 360° video and production guidelines

    OpenAIRE

    Ghimire, Sujan

    2016-01-01

    The main goal of this thesis project is to introduce latest media technology and provide a complete guideline. This project is based on the production of 360° video by using multiple GoPro cameras. This project was the first 360° video project at Helsinki Metropolia University of Applied Sciences. 360° video is a video with a totally different viewing experience and incomparable features on it. 360° x 180° video coverage and active participation from viewers are the best part of this vid...

  4. Using Video Clips To Teach Social Psychology.

    Science.gov (United States)

    Roskos-Ewoldsen, David R.; Roskos-Ewoldsen, Beverly

    2001-01-01

    Explores the effectiveness of using short video clips from feature films to highlight theoretical concepts when teaching social psychology. Reveals that short video clips have many of the same advantages as showing full-length films and demonstrates that students saw the use of these clips as an effective tool. (CMK)

  5. Indexed Captioned Searchable Videos: A Learning Companion for STEM Coursework

    Science.gov (United States)

    Tuna, Tayfun; Subhlok, Jaspal; Barker, Lecia; Shah, Shishir; Johnson, Olin; Hovey, Christopher

    2017-02-01

    Videos of classroom lectures have proven to be a popular and versatile learning resource. A key shortcoming of the lecture video format is accessing the content of interest hidden in a video. This work meets this challenge with an advanced video framework featuring topical indexing, search, and captioning (ICS videos). Standard optical character recognition (OCR) technology was enhanced with image transformations for extraction of text from video frames to support indexing and search. The images and text on video frames is analyzed to divide lecture videos into topical segments. The ICS video player integrates indexing, search, and captioning in video playback providing instant access to the content of interest. This video framework has been used by more than 70 courses in a variety of STEM disciplines and assessed by more than 4000 students. Results presented from the surveys demonstrate the value of the videos as a learning resource and the role played by videos in a students learning process. Survey results also establish the value of indexing and search features in a video platform for education. This paper reports on the development and evaluation of ICS videos framework and over 5 years of usage experience in several STEM courses.

  6. An Evaluation of Video-to-Video Face Verification

    NARCIS (Netherlands)

    Poh, N.; Chan, C.H.; Kittler, J.; Marcel, S.; Mc Cool, C.; Argones Rúa, E.; Alba Castro, J.L.; Villegas, M.; Paredes, R.; Štruc, V.; Pavešić, N.; Salah, A.A.; Fang, H.; Costen, N.

    2010-01-01

    Person recognition using facial features, e.g., mug-shot images, has long been used in identity documents. However, due to the widespread use of web-cams and mobile devices embedded with a camera, it is now possible to realize facial video recognition, rather than resorting to just still images. In

  7. Binocular eye tracking with the Tracking Scanning Laser Ophthalmoscope.

    Science.gov (United States)

    Stevenson, S B; Sheehy, C K; Roorda, A

    2016-01-01

    The development of high magnification retinal imaging has brought with it the ability to track eye motion with a precision of less than an arc minute. Previously these systems have provided only monocular records. Here we describe a modification to the Tracking Scanning Laser Ophthalmoscope (Sheehy et al., 2012) that splits the optical path in a way that slows the left and right retinas to be scanned almost simultaneously by a single system. A mirror placed at a retinal conjugate point redirects half of each horizontal scan line to the fellow eye. The collected video is a split image with left and right retinas appearing side by side in each frame. Analysis of the retinal motion in the recorded video provides an eye movement trace with very high temporal and spatial resolution. Results are presented from scans of subjects with normal ocular motility that fixated steadily on a green laser dot. The retinas were scanned at 4° eccentricity with a 2° square field. Eye position was extracted offline from recorded videos with an FFT based image analysis program written in Matlab. The noise level of the tracking was estimated to range from 0.25 to 0.5arcmin SD for three subjects. In the binocular recordings, the left eye/right eye difference was 1-2arcmin SD for vertical motion and 10-15arcmin SD for horizontal motion, in agreement with published values from other tracking techniques. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery

    Science.gov (United States)

    Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J.

    2014-01-01

    This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions. PMID:25264956

  9. Adaptive low-rank subspace learning with online optimization for robust visual tracking.

    Science.gov (United States)

    Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

    2017-04-01

    In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Characterizing the DNA Damage Response by Cell Tracking Algorithms and Cell Features Classification Using High-Content Time-Lapse Analysis.

    Directory of Open Access Journals (Sweden)

    Walter Georgescu

    Full Text Available Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were able to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when

  11. Attitude and position tracking

    CSIR Research Space (South Africa)

    Candy, LP

    2011-01-01

    Full Text Available velocity data separately in a suitable frame. In this chapter we make the case for using bivectors as the attitude tracking method of choice since several features make their performance and flexibility superior to that of DCMs, Euler angles or even rotors...

  12. Energy Tracking Diagrams

    Science.gov (United States)

    Scherr, Rachel E.; Harrer, Benedikt W.; Close, Hunter G.; Daane, Abigail R.; DeWater, Lezlie S.; Robertson, Amy D.; Seeley, Lane; Vokos, Stamatis

    2016-01-01

    Energy is a crosscutting concept in science and features prominently in national science education documents. In the "Next Generation Science Standards," the primary conceptual learning goal is for learners to conserve energy as they "track" the transfers and transformations of energy within, into, or out of the system of…

  13. Roadside video data analysis deep learning

    CERN Document Server

    Verma, Brijesh; Stockwell, David

    2017-01-01

    This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

  14. Fast Compressive Tracking.

    Science.gov (United States)

    Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

    2014-10-01

    It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

  15. BUILDING ROBUST APPEARANCE MODELS USING ON-LINE FEATURE SELECTION

    Energy Technology Data Exchange (ETDEWEB)

    PORTER, REID B. [Los Alamos National Laboratory; LOVELAND, ROHAN [Los Alamos National Laboratory; ROSTEN, ED [Los Alamos National Laboratory

    2007-01-29

    In many tracking applications, adapting the target appearance model over time can improve performance. This approach is most popular in high frame rate video applications where latent variables, related to the objects appearance (e.g., orientation and pose), vary slowly from one frame to the next. In these cases the appearance model and the tracking system are tightly integrated, and latent variables are often included as part of the tracking system's dynamic model. In this paper we describe our efforts to track cars in low frame rate data (1 frame/second) acquired from a highly unstable airborne platform. Due to the low frame rate, and poor image quality, the appearance of a particular vehicle varies greatly from one frame to the next. This leads us to a different problem: how can we build the best appearance model from all instances of a vehicle we have seen so far. The best appearance model should maximize the future performance of the tracking system, and maximize the chances of reacquiring the vehicle once it leaves the field of view. We propose an online feature selection approach to this problem and investigate the performance and computational trade-offs with a real-world dataset.

  16. Measuring energy expenditure in sports by thermal video analysis

    DEFF Research Database (Denmark)

    Gade, Rikke; Larsen, Ryan Godsk; Moeslund, Thomas B.

    2017-01-01

    Estimation of human energy expenditure in sports and exercise contributes to performance analyses and tracking of physical activity levels. The focus of this work is to develop a video-based method for estimation of energy expenditure in athletes. We propose a method using thermal video analysis ...

  17. Application aware approach to compression and transmission of H.264 encoded video for automated and centralized transportation surveillance.

    Science.gov (United States)

    2012-10-01

    In this report we present a transportation video coding and wireless transmission system specically tailored to automated : vehicle tracking applications. By taking into account the video characteristics and the lossy nature of the wireless channe...

  18. Mengolah Data Video Analog menjadi Video Digital Sederhana

    Directory of Open Access Journals (Sweden)

    Nick Soedarso

    2010-10-01

    Full Text Available Nowadays, editing technology has entered the digital age. Technology will demonstrate the evidence of processing analog to digital data has become simpler since editing technology has been integrated in the society in all aspects. Understanding the technique of processing analog to digital data is important in producing a video. To utilize this technology, the introduction of equipments is fundamental to understand the features. The next phase is the capturing process that supports the preparation in editing process from scene to scene; therefore, it will become a watchable video.   

  19. 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.

  20. Use of automated video analysis for the evaluation of bicycle movement and interaction

    Science.gov (United States)

    Twaddle, Heather; Schendzielorz, Tobias; Fakler, Oliver; Amini, Sasan

    2014-03-01

    With the purpose of developing valid models of microscopic bicycle behavior, a large quantity of video data is collected at three busy urban intersections in Munich, Germany. Due to the volume of data, the manual processing of this data is infeasible and an automated or semi-automated analysis method must be implemented. An open source software, "Traffic Intelligence", is used and extended to analyze the collected video data with regard to research questions concerning the tactical behavior of bicyclists. In a first step, the feature detection parameters, the tracking parameters and the object grouping parameters are calibrated, making it possible to accurately track and group the objects at intersections used by large volumes of motor vehicles, bicycles and pedestrians. The resulting parameters for the three intersections are presented. A methodology for the classification of road users as cars, bicycles or pedestrians is presented and evaluated. This is achieved by making hypotheses about which features belong to cars, or bicycles and pedestrians, and using grouping parameters specified for that road user group to cluster the features into objects. These objects are then classified based on their dynamic characteristics. A classification structure for the maneuvers of different road users is presented and future applications are discussed.

  1. Timber tracking

    DEFF Research Database (Denmark)

    Düdder, Boris; Ross, Omry

    2017-01-01

    Managing and verifying forest products in a value chain is often reliant on easily manipulated document or digital tracking methods - Chain of Custody Systems. We aim to create a new means of tracking timber by developing a tamper proof digital system based on Blockchain technology. Blockchain...

  2. No-Reference Video Quality Assessment by HEVC Codec Analysis

    DEFF Research Database (Denmark)

    Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

    2015-01-01

    the transform coefficients, estimates the distortion, and assesses the video quality. The proposed scheme generates VQA features based on Intra coded frames, and then maps features using an Elastic Net to predict subjective video quality. A set of HEVC coded 4K UHD sequences are tested. Results show......This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by High Efficiency Video Coding (HEVC). The proposed assessment can be performed either as a BitstreamBased (BB) method or as a Pixel-Based (PB). It extracts or estimates...

  3. Eye tracking in user experience design

    CERN Document Server

    Romano Bergstorm, Jennifer

    2014-01-01

    Eye Tracking for User Experience Design explores the many applications of eye tracking to better understand how users view and interact with technology. Ten leading experts in eye tracking discuss how they have taken advantage of this new technology to understand, design, and evaluate user experience. Real-world stories are included from these experts who have used eye tracking during the design and development of products ranging from information websites to immersive games. They also explore recent advances in the technology which tracks how users interact with mobile devices, large-screen displays and video game consoles. Methods for combining eye tracking with other research techniques for a more holistic understanding of the user experience are discussed. This is an invaluable resource to those who want to learn how eye tracking can be used to better understand and design for their users. * Includes highly relevant examples and information for those who perform user research and design interactive experi...

  4. Classifying smoke in laparoscopic videos using SVM

    Directory of Open Access Journals (Sweden)

    Alshirbaji Tamer Abdulbaki

    2017-09-01

    Full Text Available Smoke in laparoscopic videos usually appears due to the use of electrocautery when cutting or coagulating tissues. Therefore, detecting smoke can be used for event-based annotation in laparoscopic surgeries by retrieving the events associated with the electrocauterization. Furthermore, smoke detection can also be used for automatic smoke removal. However, detecting smoke in laparoscopic video is a challenge because of the changeability of smoke patterns, the moving camera and the different lighting conditions. In this paper, we present a video-based smoke detection algorithm to detect smoke of different densities such as fog, low and high density in laparoscopic videos. The proposed method depends on extracting various visual features from the laparoscopic images and providing them to support vector machine (SVM classifier. Features are based on motion, colour and texture patterns of the smoke. We validated our algorithm using experimental evaluation on four laparoscopic cholecystectomy videos. These four videos were manually annotated by defining every frame as smoke or non-smoke frame. The algorithm was applied to the videos by using different feature combinations for classification. Experimental results show that the combination of all proposed features gives the best classification performance. The overall accuracy (i.e. correctly classified frames is around 84%, with the sensitivity (i.e. correctly detected smoke frames and the specificity (i.e. correctly detected non-smoke frames are 89% and 80%, respectively.

  5. Development of a new method to track multiple honey bees with complex behaviors on a flat laboratory arena.

    Science.gov (United States)

    Kimura, Toshifumi; Ohashi, Mizue; Crailsheim, Karl; Schmickl, Thomas; Okada, Ryuichi; Radspieler, Gerald; Ikeno, Hidetoshi

    2014-01-01

    A computer program that tracks animal behavior, thereby revealing various features and mechanisms of social animals, is a powerful tool in ethological research. Because honeybee colonies are populated by thousands of bees, individuals co-exist in high physical densities and are difficult to track unless specifically tagged, which can affect behavior. In addition, honeybees react to light and recordings must be made under special red-light conditions, which the eyes of bees perceive as darkness. The resulting video images are scarcely distinguishable. We have developed a new algorithm, K-Track, for tracking numerous bees in a flat laboratory arena. Our program implements three main processes: (A) The object (bee's) region is detected by simple threshold processing on gray scale images, (B) Individuals are identified by size, shape and spatiotemporal positional changes, and (C) Centers of mass of identified individuals are connected through all movie frames to yield individual behavioral trajectories. The tracking performance of our software was evaluated on movies of mobile multi-artificial agents and of 16 bees walking around a circular arena. K-Track accurately traced the trajectories of both artificial agents and bees. In the latter case, K-track outperformed Ctrax, well-known software for tracking multiple animals. To investigate interaction events in detail, we manually identified five interaction categories; 'crossing', 'touching', 'passing', 'overlapping' and 'waiting', and examined the extent to which the models accurately identified these categories from bee's interactions. All 7 identified failures occurred near a wall at the outer edge of the arena. Finally, K-Track and Ctrax successfully tracked 77 and 60 of 84 recorded interactive events, respectively. K-Track identified multiple bees on a flat surface and tracked their speed changes and encounters with other bees, with good performance.

  6. Development of a new method to track multiple honey bees with complex behaviors on a flat laboratory arena.

    Directory of Open Access Journals (Sweden)

    Toshifumi Kimura

    Full Text Available A computer program that tracks animal behavior, thereby revealing various features and mechanisms of social animals, is a powerful tool in ethological research. Because honeybee colonies are populated by thousands of bees, individuals co-exist in high physical densities and are difficult to track unless specifically tagged, which can affect behavior. In addition, honeybees react to light and recordings must be made under special red-light conditions, which the eyes of bees perceive as darkness. The resulting video images are scarcely distinguishable. We have developed a new algorithm, K-Track, for tracking numerous bees in a flat laboratory arena. Our program implements three main processes: (A The object (bee's region is detected by simple threshold processing on gray scale images, (B Individuals are identified by size, shape and spatiotemporal positional changes, and (C Centers of mass of identified individuals are connected through all movie frames to yield individual behavioral trajectories. The tracking performance of our software was evaluated on movies of mobile multi-artificial agents and of 16 bees walking around a circular arena. K-Track accurately traced the trajectories of both artificial agents and bees. In the latter case, K-track outperformed Ctrax, well-known software for tracking multiple animals. To investigate interaction events in detail, we manually identified five interaction categories; 'crossing', 'touching', 'passing', 'overlapping' and 'waiting', and examined the extent to which the models accurately identified these categories from bee's interactions. All 7 identified failures occurred near a wall at the outer edge of the arena. Finally, K-Track and Ctrax successfully tracked 77 and 60 of 84 recorded interactive events, respectively. K-Track identified multiple bees on a flat surface and tracked their speed changes and encounters with other bees, with good performance.

  7. The role of structural characteristics in problem video game playing: a review

    OpenAIRE

    King, DL; Delfabbro, PH; Griffiths, M.

    2010-01-01

    The structural characteristics of video games may play an important role in explaining why some people play video games to excess. This paper provides a review of the literature on structural features of video games and the psychological experience of playing video games. The dominant view of the appeal of video games is based on operant conditioning theory and the notion that video games satisfy various needs for social interaction and belonging. However, there is a lack of experimental and ...

  8. OLIVE: Speech-Based Video Retrieval

    NARCIS (Netherlands)

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

    1999-01-01

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

  9. Artificial Intelligence in Video Games: Towards a Unified Framework

    OpenAIRE

    Safadi, Firas; Fonteneau, Raphael; Ernst, Damien

    2015-01-01

    With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of complex environments is pressing. Since video game AI is often specifically designed for each game, video game AI tools currently focus on allowing video game developers to quickly and efficiently create specific AI. One issue with this approach is that it does not efficiently exploit the numerous similarities that exist betw...

  10. A system for endobronchial video analysis

    Science.gov (United States)

    Byrnes, Patrick D.; Higgins, William E.

    2017-03-01

    Image-guided bronchoscopy is a critical component in the treatment of lung cancer and other pulmonary disorders. During bronchoscopy, a high-resolution endobronchial video stream facilitates guidance through the lungs and allows for visual inspection of a patient's airway mucosal surfaces. Despite the detailed information it contains, little effort has been made to incorporate recorded video into the clinical workflow. Follow-up procedures often required in cancer assessment or asthma treatment could significantly benefit from effectively parsed and summarized video. Tracking diagnostic regions of interest (ROIs) could potentially better equip physicians to detect early airway-wall cancer or improve asthma treatments, such as bronchial thermoplasty. To address this need, we have developed a system for the postoperative analysis of recorded endobronchial video. The system first parses an input video stream into endoscopic shots, derives motion information, and selects salient representative key frames. Next, a semi-automatic method for CT-video registration creates data linkages between a CT-derived airway-tree model and the input video. These data linkages then enable the construction of a CT-video chest model comprised of a bronchoscopy path history (BPH) - defining all airway locations visited during a procedure - and texture-mapping information for rendering registered video frames onto the airwaytree model. A suite of analysis tools is included to visualize and manipulate the extracted data. Video browsing and retrieval is facilitated through a video table of contents (TOC) and a search query interface. The system provides a variety of operational modes and additional functionality, including the ability to define regions of interest. We demonstrate the potential of our system using two human case study examples.

  11. Web-Mediated Augmentation and Interactivity Enhancement of Omni-Directional Video in Both 2D and 3D

    OpenAIRE

    Wijnants, Maarten; Van Erum, Kris; QUAX, Peter; Lamotte, Wim

    2015-01-01

    Video consumption has since the emergence of the medium largely been a passive affair. This paper proposes augmented Omni-Directional Video (ODV) as a novel format to engage viewers and to open up new ways of interacting with video content. Augmented ODV blends two important contemporary technologies: Augmented Video Viewing and 360 degree video. The former allows for the addition of interactive features to Web-based video playback, while the latter unlocks spatial video navigation opportunit...

  12. A Video Game Platform for Exploring Satellite and In-Situ Data Streams

    Science.gov (United States)

    Cai, Y.

    2014-12-01

    Exploring spatiotemporal patterns of moving objects are essential to Earth Observation missions, such as tracking, modeling and predicting movement of clouds, dust, plumes and harmful algal blooms. Those missions involve high-volume, multi-source, and multi-modal imagery data analysis. Analytical models intend to reveal inner structure, dynamics, and relationship of things. However, they are not necessarily intuitive to humans. Conventional scientific visualization methods are intuitive but limited by manual operations, such as area marking, measurement and alignment of multi-source data, which are expensive and time-consuming. A new development of video analytics platform has been in progress, which integrates the video game engine with satellite and in-situ data streams. The system converts Earth Observation data into articulated objects that are mapped from a high-dimensional space to a 3D space. The object tracking and augmented reality algorithms highlight the objects' features in colors, shapes and trajectories, creating visual cues for observing dynamic patterns. The head and gesture tracker enable users to navigate the data space interactively. To validate our design, we have used NASA SeaWiFS satellite images of oceanographic remote sensing data and NOAA's in-situ cell count data. Our study demonstrates that the video game system can reduce the size and cost of traditional CAVE systems in two to three orders of magnitude. This system can also be used for satellite mission planning and public outreaching.

  13. Multi-Modal Surrogates for Retrieving and Making Sense of Videos: Is Synchronization between the Multiple Modalities Optimal?

    Science.gov (United States)

    Song, Yaxiao

    2010-01-01

    Video surrogates can help people quickly make sense of the content of a video before downloading or seeking more detailed information. Visual and audio features of a video are primary information carriers and might become important components of video retrieval and video sense-making. In the past decades, most research and development efforts on…

  14. Online tracking of outdoor lighting variations for augmented reality with moving cameras.

    Science.gov (United States)

    Liu, Yanli; Granier, Xavier

    2012-04-01

    In augmented reality, one of key tasks to achieve a convincing visual appearance consistency between virtual objects and video scenes is to have a coherent illumination along the whole sequence. As outdoor illumination is largely dependent on the weather, the lighting condition may change from frame to frame. In this paper, we propose a full image-based approach for online tracking of outdoor illumination variations from videos captured with moving cameras. Our key idea is to estimate the relative intensities of sunlight and skylight via a sparse set of planar feature-points extracted from each frame. To address the inevitable feature misalignments, a set of constraints are introduced to select the most reliable ones. Exploiting the spatial and temporal coherence of illumination, the relative intensities of sunlight and skylight are finally estimated by using an optimization process. We validate our technique on a set of real-life videos and show that the results with our estimations are visually coherent along the video sequences.

  15. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... NEI YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration ... Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: ...

  16. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia ... of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ...

  17. NEI You Tube Videos: Amblyopia

    Science.gov (United States)

    ... YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia ... of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ...

  18. Video surveillance of epilepsy patients using color image processing

    DEFF Research Database (Denmark)

    Bager, Gitte; Vilic, Kenan; Vilic, Adnan

    2014-01-01

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

  19. Video Surveillance of Epilepsy Patients using Color Image Processing

    DEFF Research Database (Denmark)

    Bager, Gitte; Vilic, Kenan; Alving, Jørgen

    2007-01-01

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

  20. Objective Feature Identification and Tracking: A Review

    Science.gov (United States)

    1994-09-15

    these techniques in a visualization case study us- ferent approaches and modules can be put together ing the DieCAST model for the Gulf of Mexico... DieCAST model output for the Gulf equal magnitude but opposite sign. If the point of Mexico region. An example of the sharpness of being tested were to... DieCAST ocean Kittler, J. and J. Illingworth 1985: Relaxation circulation model in coastal and semi-enclosed labeling algorithms - a review.Image and

  1. 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

  2. Data-driven spatially-adaptive metric adjustment for visual tracking.

    Science.gov (United States)

    Jiang, Nan; Liu, Wenyu

    2014-04-01

    Matching visual appearances of the target over consecutive video frames is a fundamental yet challenging task in visual tracking. Its performance largely depends on the distance metric that determines the quality of visual matching. Rather than using fixed and predefined metric, recent attempts of integrating metric learning-based trackers have shown more robust and promising results, as the learned metric can be more discriminative. In general, these global metric adjustment methods are computationally demanding in real-time visual tracking tasks, and they tend to underfit the data when the target exhibits dynamic appearance variation. This paper presents a nonparametric data-driven local metric adjustment method. The proposed method finds a spatially adaptive metric that exhibits different properties at different locations in the feature space, due to the differences of the data distribution in a local neighborhood. It minimizes the deviation of the empirical misclassification probability to obtain the optimal metric such that the asymptotic error as if using an infinite set of training samples can be approximated. Moreover, by taking the data local distribution into consideration, it is spatially adaptive. Integrating this new local metric learning method into target tracking leads to efficient and robust tracking performance. Extensive experiments have demonstrated the superiority and effectiveness of the proposed tracking method in various tracking scenarios.

  3. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos was designed ... Activity Role of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic ...

  4. Robust infrared target tracking using discriminative and generative approaches

    Science.gov (United States)

    Asha, C. S.; Narasimhadhan, A. V.

    2017-09-01

    The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

  5. 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.

  6. 61214++++','DOAJ-ART-EN'); return false;" href="+++++https://jual.nipissingu.ca/wp-content/uploads/sites/25/2014/06/v61214.m4v">61214++++">Jailed - Video

    Directory of Open Access Journals (Sweden)

    Cameron CULBERT

    2012-07-01

    Full Text Available As the public education system in Northern Ontario continues to take a downward spiral, a plethora of secondary school students are being placed in an alternative educational environment. Juxtaposing the two educational settings reveals very similar methods and characteristics of educating our youth as opposed to using a truly alternative approach to education. This video reviews the relationship between public education and alternative education in a remote Northern Ontario setting. It is my belief that the traditional methods of teaching are not appropriate in educating at risk students in alternative schools. Paper and pencil worksheets do not motivate these students to learn and succeed. Alternative education should emphasize experiential learning, a just in time curriculum based on every unique individual and the students true passion for everyday life. Cameron Culbert was born on February 3rd, 1977 in North Bay, Ontario. His teenage years were split between attending public school and his willed curriculum on the ski hill. Culbert spent 10 years (1996-2002 & 2006-2010 competing for Canada as an alpine ski racer. His passion for teaching and coaching began as an athlete and has now transferred into the classroom and the community. As a graduate of Nipissing University (BA, BEd, MEd. Camerons research interests are alternative education, physical education and technology in the classroom. Currently Cameron is an active educator and coach in Northern Ontario.

  7. Tracking FEMA

    OpenAIRE

    Leskanic, Tyler; Kays, Kevin; Maier, Emily; Cannon, Seth

    2015-01-01

    The zip archive attached to this project is the compressed TrackingFEMA Git repository. It contains the CMS (RefineryCMS - Rails), processing scripts, as well as visualization sample code. The processing scripts are in a folder called TrackingFEMAProcessing. The visualizations are contained in Visualization. The rest of the rails files are contained within the usual Ruby on Rails file system structure. The finished product is a website visualizing the efforts of disaster response organizat...

  8. Video Design Games

    DEFF Research Database (Denmark)

    Smith, Rachel Charlotte; Christensen, Kasper Skov; Iversen, Ole Sejer

    We introduce Video Design Games to train educators in teaching design. The Video Design Game is a workshop format consisting of three rounds in which participants observe, reflect and generalize based on video snippets from their own practice. The paper reports on a Video Design Game workshop...

  9. Characterization of social video

    Science.gov (United States)

    Ostrowski, Jeffrey R.; Sarhan, Nabil J.

    2009-01-01

    The popularity of social media has grown dramatically over the World Wide Web. In this paper, we analyze the video popularity distribution of well-known social video websites (YouTube, Google Video, and the AOL Truveo Video Search engine) and characterize their workload. We identify trends in the categories, lengths, and formats of those videos, as well as characterize the evolution of those videos over time. We further provide an extensive analysis and comparison of video content amongst the main regions of the world.

  10. Online scene change detection of multicast (MBone) video

    Science.gov (United States)

    Zhou, Wensheng; Shen, Ye; Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    Many multimedia applications, such as multimedia data management systems and communication systems, require efficient representation of multimedia content. Thus semantic interpretation of video content has been a popular research area. Currently, most content-based video representation involves the segmentation of video based on key frames which are generated using scene change detection techniques as well as camera/object motion. Then, video features can be extracted from key frames. However most of such research performs off-line video processing in which the whole video scope is known as a priori which allows multiple scans of the stored video files during video processing. In comparison, relatively not much research has been done in the area of on-line video processing, which is crucial in video communication applications such as on-line collaboration, news broadcasts and so on. Our research investigates on-line real-time scene change detection of multicast video over the Internet. Our on-line processing system are designed to meet the requirements of real-time video multicasting over the Internet and to utilize the successful video parsing techniques available today. The proposed algorithms extract key frames from video bitstreams sent through the MBone network, and the extracted key frames are multicasted as annotations or metadata over a separate channel to assist in content filtering such as those anticipated to be in use by on-line filtering proxies in the Internet. The performance of the proposed algorithms are demonstrated and discussed in this paper.

  11. Tracking the Motion of Box Jellyfish

    OpenAIRE

    Kjellberg, Tobias; Palmér, Tobias; Oskarsson, Magnus; Åström, Karl

    2014-01-01

    In this paper we investigate a system for tracking the motion of box jellyfish tripedalia cystophora in a special test setup. The goal is to measure the motor response of the animal given certain visual stimuli. The approach is based on tracking the special sensory structures – the rhopalia – of the box jellyfish from high-speed video sequences. We have focused on a realtime system with simple building blocks in our system. However, using a combination of simple intensity...

  12. Video visual analytics

    OpenAIRE

    Höferlin, Markus Johannes

    2013-01-01

    The amount of video data recorded world-wide is tremendously growing and has already reached hardly manageable dimensions. It originates from a wide range of application areas, such as surveillance, sports analysis, scientific video analysis, surgery documentation, and entertainment, and its analysis represents one of the challenges in computer science. The vast amount of video data renders manual analysis by watching the video data impractical. However, automatic evaluation of video material...

  13. Luge Track Safety

    CERN Document Server

    Hubbard, Mont

    2012-01-01

    Simple geometric models of ice surface shape and equations of motion of objects on these surfaces can be used to explain ejection of sliders from ice tracks. Simulations using these can be used to explain why certain design features can be viewed as proximate causes of ejection from the track and hence design flaws. This paper studies the interaction of a particle model for the luge sled (or its right runner) with the ice fillet commonly connecting inside vertical walls and the flat track bottom. A numerical example analyzes the 2010 luge accident at the Vancouver Olympics. It shows that this runner-fillet interaction, and specifically the fillet's positive curvature up the inside wall, can cause a vertical velocity more than sufficient to clear the outside exit wall. In addition its negative curvature along the track, together with large vertical velocity, explains loss of fillet or wall contact and slider ejection. This exposes the fillet along inside walls as a track design flaw. A more transparent design ...

  14. Visual Analytics for Mobile Eye Tracking.

    Science.gov (United States)

    Kurzhals, Kuno; Hlawatsch, Marcel; Seeger, Christof; Weiskopf, Daniel

    2017-01-01

    The analysis of eye tracking data often requires the annotation of areas of interest (AOIs) to derive semantic interpretations of human viewing behavior during experiments. This annotation is typically the most time-consuming step of the analysis process. Especially for data from wearable eye tracking glasses, every independently recorded video has to be annotated individually and corresponding AOIs between videos have to be identified. We provide a novel visual analytics approach to ease this annotation process by image-based, automatic clustering of eye tracking data integrated in an interactive labeling and analysis system. The annotation and analysis are tightly coupled by multiple linked views that allow for a direct interpretation of the labeled data in the context of the recorded video stimuli. The components of our analytics environment were developed with a user-centered design approach in close cooperation with an eye tracking expert. We demonstrate our approach with eye tracking data from a real experiment and compare it to an analysis of the data by manual annotation of dynamic AOIs. Furthermore, we conducted an expert user study with 6 external eye tracking researchers to collect feedback and identify analysis strategies they used while working with our application.

  15. Online multi-face detection and tracking using detector confidence and structured SVMs

    NARCIS (Netherlands)

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

    2015-01-01

    Online detection and tracking of a variable number of faces in video is a crucial component in many real-world applications ranging from video-surveillance to online gaming. In this paper we propose FAST-DT, a fully automated system capable of detecting and tracking a variable number of faces online

  16. Video Game Genre Affordances for Physics Education

    Science.gov (United States)

    Anagnostou, Kostas; Pappa, Anastasia

    2011-01-01

    In this work, the authors analyze the video game genres' features and investigate potential mappings to specific didactic approaches in the context of Physics education. To guide the analysis, the authors briefly review the main didactic approaches for Physics and identify qualities that can be projected into game features. Based on the…

  17. Human tracking over camera networks: a review

    Science.gov (United States)

    Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang

    2017-12-01

    In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.

  18. A Novel Quantum Video Steganography Protocol with Large Payload Based on MCQI Quantum Video

    Science.gov (United States)

    Qu, Zhiguo; Chen, Siyi; Ji, Sai

    2017-11-01

    As one of important multimedia forms in quantum network, quantum video attracts more and more attention of experts and scholars in the world. A secure quantum video steganography protocol with large payload based on the video strip encoding method called as MCQI (Multi-Channel Quantum Images) is proposed in this paper. The new protocol randomly embeds the secret information with the form of quantum video into quantum carrier video on the basis of unique features of video frames. It exploits to embed quantum video as secret information for covert communication. As a result, its capacity are greatly expanded compared with the previous quantum steganography achievements. Meanwhile, the new protocol also achieves good security and imperceptibility by virtue of the randomization of embedding positions and efficient use of redundant frames. Furthermore, the receiver enables to extract secret information from stego video without retaining the original carrier video, and restore the original quantum video as a follow. The simulation and experiment results prove that the algorithm not only has good imperceptibility, high security, but also has large payload.

  19. Determining the Discharge Rate from a Submerged Oil Leaks using ROV Video and CFD study

    Science.gov (United States)

    Saha, Pankaj; Shaffer, Frank; Shahnam, Mehrdad; Savas, Omer; Devites, Dave; Steffeck, Timothy

    2016-11-01

    The current paper reports a technique to measure the discharge rate by analyzing the video from a Remotely Operated Vehicle (ROV). The technique uses instantaneous images from ROV video to measure the velocity of visible features (turbulent eddies) along the boundary of an oil leak jet and subsequently classical theory of turbulent jets is imposed to determine the discharge rate. The Flow Rate Technical Group (FRTG) Plume Team developed this technique that manually tracked the visible features and produced the first accurate government estimates of the oil discharge rate from the Deepwater Horizon (DWH). For practical application this approach needs automated control. Experiments were conducted at UC Berkeley and OHMSETT that recorded high speed, high resolution video of submerged dye-colored water or oil jets and subsequently, measured the velocity data employing LDA and PIV software. Numerical simulation have been carried out using experimental submerged turbulent oil jets flow conditions employing LES turbulence closure and VOF interface capturing technique in OpenFOAM solver. The CFD results captured jet spreading angle and jet structures in close agreement with the experimental observations. The work was funded by NETL and DOI Bureau of Safety and Environmental Enforcement (BSEE).

  20. A low-cost video-oculography system for vestibular function testing.

    Science.gov (United States)

    Jihwan Park; Youngsun Kong; Yunyoung Nam

    2017-07-01

    In order to remain in focus during head movements, vestibular-ocular reflex causes eyes to move in the opposite direction to head movement. Disorders of vestibular system decrease vision, causing abnormal nystagmus and dizziness. To diagnose abnormal nystagmus, various studies have been reported including the use of rotating chair tests and videonystagmography. However, these tests are unsuitable for home use due to their high costs. Thus, a low-cost video-oculography system is necessary to obtain clinical features at home. In this paper, we present a low-cost video-oculography system using an infrared camera and Raspberry Pi board for tracking the pupils and evaluating a vestibular system. Horizontal eye movement is derived from video data obtained from an infrared camera and infrared light-emitting diodes, and the velocity of head rotation is obtained from a gyroscope sensor. Each pupil was extracted using a morphology operation and a contour detection method. Rotatory chair tests were conducted with our developed device. To evaluate our system, gain, asymmetry, and phase were measured and compared with System 2000. The average IQR errors of gain, phase and asymmetry were 0.81, 2.74 and 17.35, respectively. We showed that our system is able to measure clinical features.