WorldWideScience

Sample records for video feature tracking

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  2. Feature Quantization and Pooling for Videos

    Science.gov (United States)

    2014-05-01

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

  3. 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.

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

    Science.gov (United States)

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

    2012-01-01

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

  5. Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

    Science.gov (United States)

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

    2017-11-01

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

  6. Technology survey on video face tracking

    Science.gov (United States)

    Zhang, Tong; Gomes, Herman Martins

    2014-03-01

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

  7. Object tracking using multiple camera video streams

    Science.gov (United States)

    Mehrubeoglu, Mehrube; Rojas, Diego; McLauchlan, Lifford

    2010-05-01

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

  8. 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.

  9. A digital video tracking system

    Science.gov (United States)

    Giles, M. K.

    1980-01-01

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

  10. Coding visual features extracted from video sequences.

    Science.gov (United States)

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

    2014-05-01

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

  11. Multimodal Feature Learning for Video Captioning

    Directory of Open Access Journals (Sweden)

    Sujin Lee

    2018-01-01

    Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

  12. Video genre classification using multimodal features

    Science.gov (United States)

    Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

    2003-12-01

    We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

  13. 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....

  14. 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.

  15. Video Scene Parsing with Predictive Feature Learning

    OpenAIRE

    Jin, Xiaojie; Li, Xin; Xiao, Huaxin; Shen, Xiaohui; Lin, Zhe; Yang, Jimei; Chen, Yunpeng; Dong, Jian; Liu, Luoqi; Jie, Zequn; Feng, Jiashi; Yan, Shuicheng

    2016-01-01

    In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we contribute two novel methods that constitute a unified parsing framework. (1) \\textbf{Predictive feature learning}} from nearly unlimited unlabeled video data. Different from existing methods learning features from single frame parsing, we learn spatiotemporal discriminative features by enforcing a parsing network to ...

  16. Features for detecting smoke in laparoscopic videos

    Directory of Open Access Journals (Sweden)

    Jalal Nour Aldeen

    2017-09-01

    Full Text Available Video-based smoke detection in laparoscopic surgery has different potential applications, such as the automatic addressing of surgical events associated with the electrocauterization task and the development of automatic smoke removal. In the literature, video-based smoke detection has been studied widely for fire surveillance systems. Nevertheless, the proposed methods are insufficient for smoke detection in laparoscopic videos because they often depend on assumptions which rarely hold in laparoscopic surgery such as static camera. In this paper, ten visual features based on motion, texture and colour of smoke are proposed and evaluated for smoke detection in laparoscopic videos. These features are RGB channels, energy-based feature, texture features based on gray level co-occurrence matrix (GLCM, HSV colour space feature, features based on the detection of moving regions using optical flow and the smoke colour in HSV colour space. These features were tested on four laparoscopic cholecystectomy videos. Experimental observations show that each feature can provide valuable information in performing the smoke detection task. However, each feature has weaknesses to detect the presence of smoke in some cases. By combining all proposed features smoke with high and even low density can be identified robustly and the classification accuracy increases significantly.

  17. Multi-view video segmentation and tracking for video surveillance

    Science.gov (United States)

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

    2009-05-01

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

  18. Occlusion Handling in Videos Object Tracking: A Survey

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  19. 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

  20. Manifolds for pose tracking from monocular video

    Science.gov (United States)

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

    2015-03-01

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

  1. SIFT based algorithm for point feature tracking

    Directory of Open Access Journals (Sweden)

    Adrian BURLACU

    2007-12-01

    Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.

  2. Video-based measurements for wireless capsule endoscope tracking

    International Nuclear Information System (INIS)

    Spyrou, Evaggelos; Iakovidis, Dimitris K

    2014-01-01

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

  3. 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.

  4. 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.

  5. 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),

  6. ‘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.

  7. Facial feature tracking: a psychophysiological measure to assess exercise intensity?

    Science.gov (United States)

    Miles, Kathleen H; Clark, Bradley; Périard, Julien D; Goecke, Roland; Thompson, Kevin G

    2018-04-01

    The primary aim of this study was to determine whether facial feature tracking reliably measures changes in facial movement across varying exercise intensities. Fifteen cyclists completed three, incremental intensity, cycling trials to exhaustion while their faces were recorded with video cameras. Facial feature tracking was found to be a moderately reliable measure of facial movement during incremental intensity cycling (intra-class correlation coefficient = 0.65-0.68). Facial movement (whole face (WF), upper face (UF), lower face (LF) and head movement (HM)) increased with exercise intensity, from lactate threshold one (LT1) until attainment of maximal aerobic power (MAP) (WF 3464 ± 3364mm, P exercise intensities (UF minus LF at: LT1, 1048 ± 383mm; LT2, 1208 ± 611mm; MAP, 1401 ± 712mm; P exercise intensity.

  8. Unsupervised Learning of Spatiotemporal Features by Video Completion

    OpenAIRE

    Nallabolu, Adithya Reddy

    2017-01-01

    In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as a surrogate task. Using a large collection of unlabeled videos, we train the CNN to predict the missing pixels of a spatiotemporal hole given the remaining parts of the video through minimizing per...

  9. Code domain steganography in video tracks

    Science.gov (United States)

    Rymaszewski, Sławomir

    2008-01-01

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

  10. A survey on the automatic object tracking technology using video signals

    International Nuclear Information System (INIS)

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

    2003-01-01

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

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

    Science.gov (United States)

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

    2002-12-01

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

  12. 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.

  13. 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.

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

    Science.gov (United States)

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

    2014-10-22

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

  15. Robust feedback zoom tracking for digital video surveillance.

    Science.gov (United States)

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

    2012-01-01

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

  16. Commercial vehicle route tracking using video detection.

    Science.gov (United States)

    2010-10-31

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

  17. Multiscale Architectures and Parallel Algorithms for Video Object Tracking

    Science.gov (United States)

    2011-10-01

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

  18. 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...

  19. Robust object tracking combining color and scale invariant features

    Science.gov (United States)

    Zhang, Shengping; Yao, Hongxun; Gao, Peipei

    2010-07-01

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

  20. 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...

  1. Human features detection in video surveillance

    OpenAIRE

    Barbosa, Patrícia Margarida Silva de Castro Neves

    2016-01-01

    Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores Human activity recognition algorithms have been studied actively from decades using a sequence of 2D and 3D images from a video surveillance. This new surveillance solutions and the areas of image processing and analysis have been receiving special attention and interest from the scientific community. Thus, it became possible to witness the appearance of new video compression techniques, the tr...

  2. Video-based Chinese Input System via Fingertip Tracking

    Directory of Open Access Journals (Sweden)

    Chih-Chang Yu

    2012-10-01

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

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

    International Nuclear Information System (INIS)

    DeTone, D; Neal, H; Lougheed, R

    2012-01-01

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

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

    Science.gov (United States)

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

    2012-12-01

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

  5. Kalman Filter Based Tracking in an Video Surveillance System

    Directory of Open Access Journals (Sweden)

    SULIMAN, C.

    2010-05-01

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

  6. 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.

  7. 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

  8. An Aerial Video Stabilization Method Based on SURF Feature

    Directory of Open Access Journals (Sweden)

    Wu Hao

    2016-01-01

    Full Text Available The video captured by Micro Aerial Vehicle is often degraded due to unexpected random trembling and jitter caused by wind and the shake of the aerial platform. An approach for stabilizing the aerial video based on SURF feature and Kalman filter is proposed. SURF feature points are extracted in each frame, and the feature points between adjacent frames are matched using Fast Library for Approximate Nearest Neighbors search method. Then Random Sampling Consensus matching algorithm and Least Squares Method are used to remove mismatching points pairs, and estimate the transformation between the adjacent images. Finally, Kalman filter is applied to smooth the motion parameters and separate Intentional Motion from Unwanted Motion to stabilize the aerial video. Experiments results show that the approach can stabilize aerial video efficiently with high accuracy, and it is robust to the translation, rotation and zooming motion of camera.

  9. Mining Videos for Features that Drive Attention

    Science.gov (United States)

    2015-04-01

    that can be added or removed from the final saliency computation. Examples of these features include intensity contrast, motion energy , color opponent...corresponding to the image. Each pixel in the feature map indicates the energy that the feature in question contributes at that location. In the standard...eye and head animation using a neurobio - logical model of visual attention. In: Bosacchi B, Fogel DB, Bezdek JC (eds) Proceedings of SPIE 48th annual

  10. Identifying sports videos using replay, text, and camera motion features

    Science.gov (United States)

    Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

    1999-12-01

    Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

  11. Digital video steganalysis using motion vector recovery-based features.

    Science.gov (United States)

    Deng, Yu; Wu, Yunjie; Zhou, Linna

    2012-07-10

    As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.

  12. 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.

  13. AUTOMATIC FAST VIDEO OBJECT DETECTION AND TRACKING ON VIDEO SURVEILLANCE SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Arunachalam

    2012-08-01

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

  14. Multiple feature fusion via covariance matrix for visual tracking

    Science.gov (United States)

    Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui

    2018-04-01

    Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.

  15. 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

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

    Science.gov (United States)

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

    2013-12-01

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

  17. Lung tumor tracking in fluoroscopic video based on optical flow

    International Nuclear Information System (INIS)

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

    2008-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-02-15

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

  19. Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

    Science.gov (United States)

    Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

    2012-10-01

    Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

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

    Directory of Open Access Journals (Sweden)

    Mohammadreza Asghari Oskoei

    2017-11-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

    2018-01-01

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

  3. Adaptive Colour Feature Identification in Image for Object Tracking

    Directory of Open Access Journals (Sweden)

    Feng Su

    2012-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Video Tracking Protocol to Screen Deterrent Chemistries for Honey Bees.

    Science.gov (United States)

    Larson, Nicholas R; Anderson, Troy D

    2017-06-12

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

  9. Collaborative Tracking of Image Features Based on Projective Invariance

    Science.gov (United States)

    Jiang, Jinwei

    -mode sensors for improving the flexibility and robustness of the system. From the experimental results during three field tests for the LASOIS system, we observed that most of the errors in the image processing algorithm are caused by the incorrect feature tracking. This dissertation addresses the feature tracking problem in image sequences acquired from cameras. Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow equation has been the most popular approach used by many in the field. This dissertation attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem, which provides collaboration among features. In contrast to alternative geometry based methods, the proposed approach provides an online solution to optical flow estimation in a collaborative fashion by exploiting Horn and Schunck flow estimation regularized by view geometric constraints. Proposed collaborative tracker estimates the motion of a feature based on the geometry of the scene and how the other features are moving. Alternative to this approach, a new closed form solution to tracking that combines the image appearance with the view geometry is also introduced. We particularly use invariants in the projective coordinates and conjecture that the traditional appearance solution can be significantly improved using view geometry. The geometric constraint is introduced by defining a new optical flow equation which exploits the scene geometry from a set drawn from tracked features. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template. The proposed collaborative tracking method is also tested in the visual navigation

  10. Understanding Learning Style by Eye Tracking in Slide Video Learning

    Science.gov (United States)

    Cao, Jianxia; Nishihara, Akinori

    2012-01-01

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

  11. Stereoscopic Feature Tracking System for Retrieving Velocity of Surface Waters

    Science.gov (United States)

    Zuniga Zamalloa, C. C.; Landry, B. J.

    2017-12-01

    The present work is concerned with the surface velocity retrieval of flows using a stereoscopic setup and finding the correspondence in the images via feature tracking (FT). The feature tracking provides a key benefit of substantially reducing the level of user input. In contrast to other commonly used methods (e.g., normalized cross-correlation), FT does not require the user to prescribe interrogation window sizes and removes the need for masking when specularities are present. The results of the current FT methodology are comparable to those obtained via Large Scale Particle Image Velocimetry while requiring little to no user input which allowed for rapid, automated processing of imagery.

  12. 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…

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

    KAUST Repository

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

    2016-01-01

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

  14. 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

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

    Directory of Open Access Journals (Sweden)

    Baojun Zhao

    2018-03-01

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

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

    Science.gov (United States)

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

    2018-03-04

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

  17. 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.

  18. Tracking image features with PCA-SURF descriptors

    CSIR Research Space (South Africa)

    Pancham, A

    2015-05-01

    Full Text Available IAPR International Conference on Machine Vision Applications, May 18-22, 2015, Tokyo, JAPAN Tracking Image Features with PCA-SURF Descriptors Ardhisha Pancham CSIR, UKZN South Africa apancham@csir.co.za Daniel Withey CSIR South Africa...

  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. 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.

  1. Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

    Directory of Open Access Journals (Sweden)

    Li Yao

    2016-01-01

    Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

  2. 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

  3. 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...

  4. Spatio-temporal features for tracking and quadruped/biped discrimination

    Science.gov (United States)

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

    2012-05-01

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

  5. OpenCV and TYZX : video surveillance for tracking.

    Energy Technology Data Exchange (ETDEWEB)

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-08-01

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

  6. OpenCV and TYZX : video surveillance for tracking

    International Nuclear Information System (INIS)

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-01-01

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

  7. Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

    Directory of Open Access Journals (Sweden)

    Ting-quan Deng

    2014-01-01

    Full Text Available In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios.

  8. 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.

  9. Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

    Science.gov (United States)

    Khayat, Omid; Afarideh, Hossein

    2013-04-01

    Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

  10. An adaptive approach to human motion tracking from video

    Science.gov (United States)

    Wu, Lifang; Chen, Chang Wen

    2010-07-01

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

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

    Science.gov (United States)

    Reader, Arran T; Holmes, Nicholas P

    2015-01-01

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

  12. Teen videos on YouTube: Features and digital vulnerabilities

    OpenAIRE

    Montes-Vozmediano, Manuel; García-Jiménez, Antonio; Menor-Sendra, Juan

    2018-01-01

    As a mechanism for social participation and integration and for the purpose of building their identity, teens make and share videos on platforms such as YouTube of which they are also content consumers. The vulnerability conditions that occur and the risks to which adolescents are exposed, both as creators and consumers of videos, are the focus of this study. The methodology used is content analysis, applied to 400 videos. This research has worked with manifest variables (such as the scene) a...

  13. Video Surveillance using a Multi-Camera Tracking and Fusion System

    OpenAIRE

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

    2008-01-01

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

  14. 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.

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

    Science.gov (United States)

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

    2016-09-01

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

  16. Teen Videos on YouTube: Features and Digital Vulnerabilities

    Science.gov (United States)

    Montes-Vozmediano, Manuel; García-Jiménez, Antonio; Menor-Sendra, Juan

    2018-01-01

    As a mechanism for social participation and integration and for the purpose of building their identity, teens make and share videos on platforms such as YouTube of which they are also content consumers. The vulnerability conditions that occur and the risks to which adolescents are exposed, both as creators and consumers of videos, are the focus of…

  17. Reidentification of Persons Using Clothing Features in Real-Life Video

    Directory of Open Access Journals (Sweden)

    Guodong Zhang

    2017-01-01

    Full Text Available Person reidentification, which aims to track people across nonoverlapping cameras, is a fundamental task in automated video processing. Moving people often appear differently when viewed from different nonoverlapping cameras because of differences in illumination, pose, and camera properties. The color histogram is a global feature of an object that can be used for identification. This histogram describes the distribution of all colors on the object. However, the use of color histograms has two disadvantages. First, colors change differently under different lighting and at different angles. Second, traditional color histograms lack spatial information. We used a perception-based color space to solve the illumination problem of traditional histograms. We also used the spatial pyramid matching (SPM model to improve the image spatial information in color histograms. Finally, we used the Gaussian mixture model (GMM to show features for person reidentification, because the main color feature of GMM is more adaptable for scene changes, and improve the stability of the retrieved results for different color spaces in various scenes. Through a series of experiments, we found the relationships of different features that impact person reidentification.

  18. 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.

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

    Institute of Scientific and Technical Information of China (English)

    Chen Ken; Napolitano; Zhang Yun; Li Dong

    2010-01-01

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

  20. 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 .

  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. Feature Tracking for High Speed AFM Imaging of Biopolymers.

    Science.gov (United States)

    Hartman, Brett; Andersson, Sean B

    2018-03-31

    The scanning speed of atomic force microscopes continues to advance with some current commercial microscopes achieving on the order of one frame per second and at least one reaching 10 frames per second. Despite the success of these instruments, even higher frame rates are needed with scan ranges larger than are currently achievable. Moreover, there is a significant installed base of slower instruments that would benefit from algorithmic approaches to increasing their frame rate without requiring significant hardware modifications. In this paper, we present an experimental demonstration of high speed scanning on an existing, non-high speed instrument, through the use of a feedback-based, feature-tracking algorithm that reduces imaging time by focusing on features of interest to reduce the total imaging area. Experiments on both circular and square gratings, as well as silicon steps and DNA strands show a reduction in imaging time by a factor of 3-12 over raster scanning, depending on the parameters chosen.

  3. Quantitative analysis of spider locomotion employing computer-automated video tracking

    DEFF Research Database (Denmark)

    Baatrup, E; Bayley, M

    1993-01-01

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

  4. Using Genetic Algorithm for Eye Detection and Tracking in Video Sequence

    Directory of Open Access Journals (Sweden)

    Takuya Akashi

    2007-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Seymour Rowan

    2008-01-01

    Full Text Available Abstract 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.

  6. 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.

  7. Pricise Target Geolocation and Tracking Based on Uav Video Imagery

    Science.gov (United States)

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

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Xin Li

    2014-06-01

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

  9. Fast and efficient search for MPEG-4 video using adjacent pixel intensity difference quantization histogram feature

    Science.gov (United States)

    Lee, Feifei; Kotani, Koji; Chen, Qiu; Ohmi, Tadahiro

    2010-02-01

    In this paper, a fast search algorithm for MPEG-4 video clips from video database is proposed. An adjacent pixel intensity difference quantization (APIDQ) histogram is utilized as the feature vector of VOP (video object plane), which had been reliably applied to human face recognition previously. Instead of fully decompressed video sequence, partially decoded data, namely DC sequence of the video object are extracted from the video sequence. Combined with active search, a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by total 15 hours of video contained of TV programs such as drama, talk, news, etc. to search for given 200 MPEG-4 video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 2 % in drama and news categories are achieved, which are more accurately and robust than conventional fast video search algorithm.

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

    Science.gov (United States)

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

    2016-05-01

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

  11. 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.

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

    OpenAIRE

    Marimón Sanjuán, David

    2007-01-01

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

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

    OpenAIRE

    Marimón Sanjuán, David; Ebrahimi, Touradj

    2008-01-01

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

  14. A modular CUDA-based framework for scale-space feature detection in video streams

    International Nuclear Information System (INIS)

    Kinsner, M; Capson, D; Spence, A

    2010-01-01

    Multi-scale image processing techniques enable extraction of features where the size of a feature is either unknown or changing, but the requirement to process image data at multiple scale levels imposes a substantial computational load. This paper describes the architecture and emerging results from the implementation of a GPGPU-accelerated scale-space feature detection framework for video processing. A discrete scale-space representation is generated for image frames within a video stream, and multi-scale feature detection metrics are applied to detect ridges and Gaussian blobs at video frame rates. A modular structure is adopted, in which common feature extraction tasks such as non-maximum suppression and local extrema search may be reused across a variety of feature detectors. Extraction of ridge and blob features is achieved at faster than 15 frames per second on video sequences from a machine vision system, utilizing an NVIDIA GTX 480 graphics card. By design, the framework is easily extended to additional feature classes through the inclusion of feature metrics to be applied to the scale-space representation, and using common post-processing modules to reduce the required CPU workload. The framework is scalable across multiple and more capable GPUs, and enables previously intractable image processing at video frame rates using commodity computational hardware.

  15. 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.

  16. News video story segmentation method using fusion of audio-visual features

    Science.gov (United States)

    Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

    2007-11-01

    News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

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

    OpenAIRE

    McCall, J C; Trivedi, Mohan Manubhai

    2006-01-01

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

  18. 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.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  20. 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

  1. 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

  2. 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.

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

    NARCIS (Netherlands)

    Bouma, H.; Baan, J.; Burghouts, G.J.; Eendebak, P.T.; Huis, J.R. van; Dijk, J.; Rest, J.H.C. van

    2014-01-01

    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

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

    Science.gov (United States)

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

    2013-06-20

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

  5. 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.

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

    Science.gov (United States)

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

    2014-10-12

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

  7. Right ventricular mechanics in hypertrophic cardiomyopathy using feature tracking

    Science.gov (United States)

    Badran, Hala Mahfouz; Soliman, Mahmood; Hassan, Hesham; Abdelfatah, Raed; Saadan, Haythem; Yacoub, Magdi

    2013-01-01

    Objectives: Right ventricular (RV) mechanics in hypertrophic cardiomyopathy (HCM) are poorly understood. We investigate global and regional deformation of the RV in HCM and its relationship to LV phenotype, using 2D strain vector velocity imaging (VVI). Methods: 100 HCM patients (42% females, 41 ± 19 years) and 30 control patients were studied using VVI. Longitudinal peak systolic strain (ϵsys), strain rate (SR), time to peak (ϵ) (TTP), displacement of RV free wall (RVFW) and septal wall were analyzed. Similar parameters were quantified in LV septal, lateral, anterior and inferior segments. Intra-V-delay was defined as SD of TTP. Inter-V-delay was estimated from TTP difference between the most delayed LV segment & RVFW. Results: ϵsys and SR of both RV & LV, showed loss of base to apex gradient and significant decline in HCM (p < 0.001). Deformation variables estimated from RVFW were strongly correlated with each other (r = 0.93, p < 0.0001). Both were directly related to LV ϵsys, SRsys, SRe, ejection fraction (EF)%, RVFW displacement (P < 0.001) and inversely related to age, positive family history (p < 0.004, 0.005), RV wall thickness, maximum wall thickness (MWT), intra-V-delay, LA volume (P < 0.0001), LVOT gradient (p < 0.02, 0.005) respectively. ROC curves were constructed to explore the cut-off point that discriminates RV dysfunction. Global and RVFW ϵsys: − 19.5% shows 77, 70% sensitivity & 97% specificity, SRsys: − 1.3s− 1 shows 82, 70% sensitivity & 30% specificity. Multivariate analyses revealed that RVFW displacement (β = − 0.9, p < 0.0001) and global LV SRsys (β = 5.9, p < 0.0001) are independent predictors of global RV deformation. Conclusions: Impairment of RV deformation is evident in HCM using feature tracking. It is independently influenced by LV mechanics and correlated to the severity of LV phenotype. RVFW deformation analysis and global RV assessment are comparable. PMID:24689019

  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. Infrared video based gas leak detection method using modified FAST features

    Science.gov (United States)

    Wang, Min; Hong, Hanyu; Huang, Likun

    2018-03-01

    In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-08-01

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

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

    International Nuclear Information System (INIS)

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

    1976-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ming Xue

    2014-02-01

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

  15. FEATURES OF THE RESEARCH WORK ELEMENTS DEFORMABILITY OF RAILWAY TRACK

    Directory of Open Access Journals (Sweden)

    I. O. Bondarenko

    2015-06-01

    Full Text Available Purpose. The scientific paper is supposed the determination of basic physical and structural conditions in modeling life cycle of the elements of the railway line for the study of deformation processes as the basis of normative base of the track at the condition of railway safety. Methodology. To achieve the aim principles of the elasticity theory and wave propagation process in the description of the interaction between the track and rolling stock were used. Findings. The basic physical and structural conditions under which it is necessary to carry out the simulation of the life cycle of the elements of the railway line for the study of deformation processes were determined. The basic physical and structural principles of drawing the design schemes of railway track elements for the process assessment of the track deformation work were formulated. The decision correctness and the possibility of the problem solution are proved. Originality. The study of the track reliability questions motivates the development of new models, allow considering it for some developments. There is a need to identify the main physical and structural conditions for assembly design schemes based on assessment and prediction of possible track state changes during its operation. The paper presents the basic principles of physical and structural drafting design schemes of railway line items for which Huygens’ principle is implemented. This principle can be performed only when the four dimensional space: the volume changing over time is considered. Practical value. Analytical models applied in determining the parameters of strength and resistance lines, fully satisfy the task, but can not be used to determine the parameters of track reliability. One of the main impossibility factors of these models is quasidynamic approach. Therefore, as a rule, receive and examine not only dynamic process of a railway track, but also its consequences. Besides, these models are related to

  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. 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.

  18. 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…

  19. The distinguishing motor features of cataplexy: a study from video-recorded attacks.

    Science.gov (United States)

    Pizza, Fabio; Antelmi, Elena; Vandi, Stefano; Meletti, Stefano; Erro, Roberto; Baumann, Christian R; Bhatia, Kailash P; Dauvilliers, Yves; Edwards, Mark J; Iranzo, Alex; Overeem, Sebastiaan; Tinazzi, Michele; Liguori, Rocco; Plazzi, Giuseppe

    2018-05-01

    To describe the motor pattern of cataplexy and to determine its phenomenological differences from pseudocataplexy in the differential diagnosis of episodic falls. We selected 30 video-recorded cataplexy and 21 pseudocataplexy attacks in 17 and 10 patients evaluated for suspected narcolepsy and with final diagnosis of narcolepsy type 1 and conversion disorder, respectively, together with self-reported attacks features, and asked expert neurologists to blindly evaluate the motor features of the attacks. Video documented and self-reported attack features of cataplexy and pseudocataplexy were contrasted. Video-recorded cataplexy can be positively differentiated from pseudocataplexy by the occurrence of facial hypotonia (ptosis, mouth opening, tongue protrusion) intermingled by jerks and grimaces abruptly interrupting laughter behavior (i.e. smile, facial expression) and postural control (head drops, trunk fall) under clear emotional trigger. Facial involvement is present in both partial and generalized cataplexy. Conversely, generalized pseudocataplexy is associated with persistence of deep tendon reflexes during the attack. Self-reported features confirmed the important role of positive emotions (laughter, telling a joke) in triggering the attacks, as well as the more frequent occurrence of partial body involvement in cataplexy compared with pseudocataplexy. Cataplexy is characterized by abrupt facial involvement during laughter behavior. Video recording of suspected cataplexy attacks allows the identification of positive clinical signs useful for diagnosis and, possibly in the future, for severity assessment.

  20. A line feature-based camera tracking method applicable to nuclear power plant environment

    International Nuclear Information System (INIS)

    Yan, Weida; Ishii, Hirotake; Shimoda, Hiroshi; Izumi, Masanori

    2014-01-01

    Augmented reality, which can support the maintenance and decommissioning work of an NPP to improve efficiency and reduce human error, is expected to be practically used in an NPP. AR has indispensable tracking technology that estimates the 3D position and orientation of users in real time, but because of the complication of the NPP environment, it is difficult for its practial use in the large space of an NPP. This study attempt to develop a tracking method for the practial use in an NPP. Marker tracking is a legacy tracking method, but the preparation work necessary for that method is onerous. Therefore, this study developed and evaluated a natural feature-based camera tracking method that demands less preparation and which is applicable in an NPP environment. This method registers natural features as landmarks. When tracking, the natural features existing in the NPP environment can be registered automatically as landmarks. It is therefore possible to expand the tracking area to cover a wide environment in theory. The evaluation result shows that the proposed tracking method has the possibility to support field work of some kinds in an NPP environment. It is possible to reduce the preparation work necessary for the marker tracking method. (author)

  1. Mobile Augmented Reality Support for Architects Based on Feature Tracking Techniques

    DEFF Research Database (Denmark)

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

    2004-01-01

    on the horizon view from an office building, while working on a courtyard garden proposal. The SitePack applies a novel combination of GPS tracking and vision based feature tracking in its support for architects. The SitePack requires no preparation of the site and combines and extends the strengths of previous...

  2. 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...

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

    OpenAIRE

    Bouma, H.; Baan, J.; Burghouts, G.J.; Eendebak, P.T.; Huis, J.R. van; Dijk, J.; Rest, J.H.C. van

    2014-01-01

    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 snat...

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

    Science.gov (United States)

    Borkowski, Jeffrey M.; Vasquez, Juan R.

    2006-05-01

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

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

    Science.gov (United States)

    Liu, Yu-Che; Huang, Chung-Lin

    2013-03-01

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

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

    Science.gov (United States)

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

    2011-06-01

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

  7. 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.

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2015-09-22

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

    Luo, Xiongbiao; Mori, Kensaku

    2014-06-01

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

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

    International Nuclear Information System (INIS)

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

    1991-01-01

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

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

    Science.gov (United States)

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

    2004-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lim Hye-Youn

    2011-01-01

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

  16. 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.

  17. A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series

    Directory of Open Access Journals (Sweden)

    Keke Zhang

    2018-01-01

    Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.

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

    Directory of Open Access Journals (Sweden)

    Chundi eWang

    2016-05-01

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

  19. Feature Extraction for Track Section Status Classification Based on UGW Signals

    Directory of Open Access Journals (Sweden)

    Lei Yuan

    2018-04-01

    Full Text Available Track status classification is essential for the stability and safety of railway operations nowadays, when railway networks are becoming more and more complex and broad. In this situation, monitoring systems are already a key element in applications dedicated to evaluating the status of a certain track section, often determining whether it is free or occupied by a train. Different technologies have already been involved in the design of monitoring systems, including ultrasonic guided waves (UGW. This work proposes the use of the UGW signals captured by a track monitoring system to extract the features that are relevant for determining the corresponding track section status. For that purpose, three features of UGW signals have been considered: the root mean square value, the energy, and the main frequency components. Experimental results successfully validated how these features can be used to classify the track section status into free, occupied and broken. Furthermore, spatial and temporal dependencies among these features were analysed in order to show how they can improve the final classification performance. Finally, a preliminary high-level classification system based on deep learning networks has been envisaged for future works.

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

    CSIR Research Space (South Africa)

    Senekal, F

    2010-11-01

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

  1. 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.

  2. 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.

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

    Science.gov (United States)

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

    2015-04-01

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

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Akhmad Yusuf

    2017-12-01

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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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 sys...

  13. Omnidirectional sparse visual path following with occlusion-robust feature tracking

    OpenAIRE

    Goedemé, Toon; Tuytelaars, Tinne; Van Gool, Luc; Vanacker, Gerolf; Nuttin, Marnix

    2005-01-01

    Goedemé T., Tuytelaars T., Van Gool L., Vanacker G., Nuttin M., ''Omnidirectional sparse visual path following with occlusion-robust feature tracking'', Proceedings 6th workshop on omnidirectional vision, camera networks and non-classical cameras, 8 pp., October 21, 2005, Beijing, China.

  14. Automatic assessment of mitral regurgitation severity based on extensive textural features on 2D echocardiography videos.

    Science.gov (United States)

    Moghaddasi, Hanie; Nourian, Saeed

    2016-06-01

    Heart disease is the major cause of death as well as a leading cause of disability in the developed countries. Mitral Regurgitation (MR) is a common heart disease which does not cause symptoms until its end stage. Therefore, early diagnosis of the disease is of crucial importance in the treatment process. Echocardiography is a common method of diagnosis in the severity of MR. Hence, a method which is based on echocardiography videos, image processing techniques and artificial intelligence could be helpful for clinicians, especially in borderline cases. In this paper, we introduce novel features to detect micro-patterns of echocardiography images in order to determine the severity of MR. Extensive Local Binary Pattern (ELBP) and Extensive Volume Local Binary Pattern (EVLBP) are presented as image descriptors which include details from different viewpoints of the heart in feature vectors. Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Template Matching techniques are used as classifiers to determine the severity of MR based on textural descriptors. The SVM classifier with Extensive Uniform Local Binary Pattern (ELBPU) and Extensive Volume Local Binary Pattern (EVLBP) have the best accuracy with 99.52%, 99.38%, 99.31% and 99.59%, respectively, for the detection of Normal, Mild MR, Moderate MR and Severe MR subjects among echocardiography videos. The proposed method achieves 99.38% sensitivity and 99.63% specificity for the detection of the severity of MR and normal subjects. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2018-04-23

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

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

    Science.gov (United States)

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

    2009-06-15

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

  17. 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/.

  18. Side-Scan Sonar Image Mosaic Using Couple Feature Points with Constraint of Track Line Positions

    Directory of Open Access Journals (Sweden)

    Jianhu Zhao

    2018-06-01

    Full Text Available To obtain large-scale seabed surface image, this paper proposes a side-scan sonar (SSS image mosaic method using couple feature points (CFPs with constraint of track line positions. The SSS geocoded images are firstly used to form a coarsely mosaicked one and the overlapping areas between adjacent strip images can be determined based on geographic information. Inside the overlapping areas, the feature point (FP detection and registration operation are adopted for both strips. According to the detected CFPs and track line positions, an adjustment model is established to accommodate complex local distortions as well as ensure the global stability. This proposed method effectively solves the problem of target ghosting or dislocation and no accumulated errors arise in the mosaicking process. Experimental results show that the finally mosaicked image correctly reflects the object distribution, which is meaningful for understanding and interpreting seabed topography.

  19. 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.

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

    Science.gov (United States)

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

    2017-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Shuangbao Paul Wang

    2017-08-01

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

  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. Automated Music Video Generation Using Multi-level Feature-based Segmentation

    Science.gov (United States)

    Yoon, Jong-Chul; Lee, In-Kwon; Byun, Siwoo

    The expansion of the home video market has created a requirement for video editing tools to allow ordinary people to assemble videos from short clips. However, professional skills are still necessary to create a music video, which requires a stream to be synchronized with pre-composed music. Because the music and the video are pre-generated in separate environments, even a professional producer usually requires a number of trials to obtain a satisfactory synchronization, which is something that most amateurs are unable to achieve.

  4. 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.

  5. Linear feature detection algorithm for astronomical surveys - II. Defocusing effects on meteor tracks

    Science.gov (United States)

    Bektešević, Dino; Vinković, Dejan; Rasmussen, Andrew; Ivezić, Željko

    2018-03-01

    Given the current limited knowledge of meteor plasma micro-physics and its interaction with the surrounding atmosphere and ionosphere, meteors are a highly interesting observational target for high-resolution wide-field astronomical surveys. Such surveys are capable of resolving the physical size of meteor plasma heads, but they produce large volumes of images that need to be automatically inspected for possible existence of long linear features produced by meteors. Here, we show how big aperture sky survey telescopes detect meteors as defocused tracks with a central brightness depression. We derive an analytic expression for a defocused point source meteor track and use it to calculate brightness profiles of meteors modelled as uniform brightness discs. We apply our modelling to meteor images as seen by the Sloan Digital Sky Survey and Large Synoptic Survey Telescope telescopes. The expression is validated by Monte Carlo ray-tracing simulations of photons travelling through the atmosphere and the Large Synoptic Survey Telescope telescope optics. We show that estimates of the meteor distance and size can be extracted from the measured full width at half-maximum and the strength of the central dip in the observed brightness profile. However, this extraction becomes difficult when the defocused meteor track is distorted by the atmospheric seeing or contaminated by a long-lasting glowing meteor trail. The full width at half-maximum of satellite tracks is distinctly narrower than meteor values, which enables removal of a possible confusion between satellites and meteors.

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

    Science.gov (United States)

    Zhang, Yongjie; Wang, Jian; Yang, Xin

    2017-08-01

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

  7. Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature

    Directory of Open Access Journals (Sweden)

    Yuankun Li

    2018-02-01

    Full Text Available Although correlation filter (CF-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

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

    Science.gov (United States)

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

    2004-03-01

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

  9. 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....

  10. 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

    ... finance systems have to keep track of mail costs? 102-192.65 Section 102-192.65 Public Contracts and... What features must our finance systems have to keep track of mail costs? All agencies must have an... requirement, because the level at which it is cost-beneficial differs widely. The agency's finance system(s...

  11. Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

    International Nuclear Information System (INIS)

    Wu, Lingfei; Wu, Kesheng; Sim, Alex; Churchill, Michael; Choi, Jong Youl

    2016-01-01

    A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.

  12. Tracking hydrothermal feature changes in response to seismicity and deformation at Mud Volcano thermal area, Yellowstone

    Science.gov (United States)

    Diefenbach, A. K.; Hurwitz, S.; Murphy, F.; Evans, W.

    2013-12-01

    The Mud Volcano thermal area in Yellowstone National Park comprises many hydrothermal features including fumaroles, mudpots, springs, and thermal pools. Observations of hydrothermal changes have been made for decades in the Mud Volcano thermal area, and include reports of significant changes (the appearance of new features, increased water levels in pools, vigor of activity, and tree mortality) following an earthquake swarm in 1978 that took place beneath the area. However, no quantitative method to map and measure surface feature changes through time has been applied. We present an analysis of aerial photographs from 1954 to present to track temporal changes in the boundaries between vegetated and thermally barren areas, as well as location, extent, color, clarity, and runoff patterns of hydrothermal features within the Mud Volcano thermal area. This study attempts to provide a detailed, long-term (>50 year) inventory of hydrothermal features and change detection at Mud Volcano thermal area that can be used to identify changes in hydrothermal activity in response to seismicity, uplift and subsidence episodes of the adjacent Sour Creek resurgent dome, or other potential causes.

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

    Science.gov (United States)

    Green, C. S.; Bavelier, D.

    2006-01-01

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

  14. Dust Storm Feature Identification and Tracking from 4D Simulation Data

    Science.gov (United States)

    Yu, M.; Yang, C. P.

    2016-12-01

    Dust storms cause significant damage to health, property and the environment worldwide every year. To help mitigate the damage, dust forecasting models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. Normally, the model simulations are conducted in four-dimensions (i.e., latitude, longitude, elevation and time) and represent three-dimensional (3D), spatial heterogeneous features of the storm and its evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing based identification algorithm to identify critical dust storm features, and track the evolution process of dust storm events through space and time. In addition, a spatiotemporal data model is proposed, which can support the characterization and representation of dust storm events and their dynamic patterns. Quantitative and qualitative evaluations for the algorithm are conducted to test the sensitivity, and capability of identify and track dust storm events. This study has the potential to assist a better early warning system for decision-makers and the public, thus making hazard mitigation plans more effective.

  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. 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.

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

    OpenAIRE

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

    2017-01-01

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

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

    Science.gov (United States)

    Leny, Marc; Prêteux, Françoise; Nicholson, Didier

    2008-02-01

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

  19. 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.

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

    International Nuclear Information System (INIS)

    Dowdell, S; Paganetti, H; Schuemann, J; Greilich, S; Zimmerman, F; Evans, C

    2014-01-01

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

    NARCIS (Netherlands)

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

    2018-01-01

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

  2. 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

  3. A PTV method based on ultrasound imaging and feature tracking in a low-concentration sediment-laden flow

    Science.gov (United States)

    Ma, Zhimin; Hu, Wenbin; Zhao, Xiaohong; Tao, Weiliang

    2018-02-01

    This study aims to provide a particle tracking velocimetry (PTV) method based on ultrasound imaging and feature-tracking in a low-concentration sediment-laden flow. A phased array probe is used to generate a 2D ultrasound image at different times. Then, the feature points are extracted to be tracked instead of the centroids of the particle image. In order to better identify the corresponding feature point, each feature is described by an oriented angle and its location. Then, a statistical interpolation procedure is used to yield the displacement vector on the desired grid point. Finally a correction procedure is adopted because the ultrasound image is sequentially acquired line by line through the field of view. A simple test experiment was carried out to evaluate the performance. The ultrasound PTV system was applied to a sediment-laden flow with a low concentration of 1‰, and the speed was up to 10 cm s-1. In comparison to optical particle image velocimetry (PIV), ultrasound imaging does not have a limitation in optical access. The feature-tracking method does not have a binarisation and segmentation procedure, which can result in overlapping particles or a serious loss of particle data. The feature-tracking algorithm improves the peak locking effect and measurement accuracy. Thus, the ultrasound PTV algorithm is a feasible alternative and is significantly more robust against gradients than the correlation-based PIV algorithms in a low-concentration sediment-laden fluid.

  4. 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.

  5. 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.

  6. Manipulations of the features of standard video lottery terminal (VLT) games: effects in pathological and non-pathological gamblers.

    Science.gov (United States)

    Loba, P; Stewart, S H; Klein, R M; Blackburn, J R

    2001-01-01

    The present study was conducted to identify game parameters that would reduce the risk of abuse of video lottery terminals (VLTs) by pathological gamblers, while exerting minimal effects on the behavior of non-pathological gamblers. Three manipulations of standard VLT game features were explored. Participants were exposed to: a counter which displayed a running total of money spent; a VLT spinning reels game where participants could no longer "stop" the reels by touching the screen; and sensory feature manipulations. In control conditions, participants were exposed to standard settings for either a spinning reels or a video poker game. Dependent variables were self-ratings of reactions to each set of parameters. A set of 2(3) x 2 x 2 (game manipulation [experimental condition(s) vs. control condition] x game [spinning reels vs. video poker] x gambler status [pathological vs. non-pathological]) repeated measures ANOVAs were conducted on all dependent variables. The findings suggest that the sensory manipulations (i.e., fast speed/sound or slow speed/no sound manipulations) produced the most robust reaction differences. Before advocating harm reduction policies such as lowering sensory features of VLT games to reduce potential harm to pathological gamblers, it is important to replicate findings in a more naturalistic setting, such as a real bar.

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

    Science.gov (United States)

    Beato, Marco; Jamil, Mikael

    2017-05-09

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

  8. 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.

  9. 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.

  10. 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.

  11. How Is Marijuana Vaping Portrayed on YouTube? Content, Features, Popularity and Retransmission of Vaping Marijuana YouTube Videos.

    Science.gov (United States)

    Yang, Qinghua; Sangalang, Angeline; Rooney, Molly; Maloney, Erin; Emery, Sherry; Cappella, Joseph N

    2018-01-01

    The purpose of the study is to investigate how vaping marijuana, a novel but emerging risky health behavior, is portrayed on YouTube, and how the content and features of these YouTube videos influence their popularity and retransmission. A content analysis of vaping marijuana YouTube videos published between July 2014 to June 2015 (n = 214) was conducted. Video genre, valence, promotional and warning arguments, emotional appeals, message sensation value, presence of misinformation and misleading information, and user-generated statistics, including number of views, comments, shares, likes and dislikes, were coded. The results showed that these videos were predominantly pro-marijuana-vaping, with the most frequent videos being user-sharing. The genre and message features influenced the popularity, evaluations, and retransmission of vaping marijuana YouTube videos. Theoretical and practical implications are discussed.

  12. 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

  13. Endocardial left ventricle feature tracking and reconstruction from tri-plane trans-esophageal echocardiography data

    Science.gov (United States)

    Dangi, Shusil; Ben-Zikri, Yehuda K.; Cahill, Nathan; Schwarz, Karl Q.; Linte, Cristian A.

    2015-03-01

    Two-dimensional (2D) ultrasound (US) has been the clinical standard for over two decades for monitoring and assessing cardiac function and providing support via intra-operative visualization and guidance for minimally invasive cardiac interventions. Developments in three-dimensional (3D) image acquisition and transducer design and technology have revolutionized echocardiography imaging enabling both real-time 3D trans-esophageal and intra-cardiac image acquisition. However, in most cases the clinicians do not access the entire 3D image volume when analyzing the data, rather they focus on several key views that render the cardiac anatomy of interest during the US imaging exam. This approach enables image acquisition at a much higher spatial and temporal resolution. Two such common approaches are the bi-plane and tri-plane data acquisition protocols; as their name states, the former comprises two orthogonal image views, while the latter depicts the cardiac anatomy based on three co-axially intersecting views spaced at 600 to one another. Since cardiac anatomy is continuously changing, the intra-operative anatomy depicted using real-time US imaging also needs to be updated by tracking the key features of interest and endocardial left ventricle (LV) boundaries. Therefore, rapid automatic feature tracking in US images is critical for three reasons: 1) to perform cardiac function assessment; 2) to identify location of surgical targets for accurate tool to target navigation and on-target instrument positioning; and 3) to enable pre- to intra-op image registration as a means to fuse pre-op CT or MR images used during planning with intra-operative images for enhanced guidance. In this paper we utilize monogenic filtering, graph-cut based segmentation and robust spline smoothing in a combined work flow to process the acquired tri-plane TEE time series US images and demonstrate robust and accurate tracking of the LV endocardial features. We reconstruct the endocardial LV

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

    OpenAIRE

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2012-02-01

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

  16. 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.

  17. Rett syndrome: basic features of visual processing-a pilot study of eye-tracking.

    Science.gov (United States)

    Djukic, Aleksandra; Valicenti McDermott, Maria; Mavrommatis, Kathleen; Martins, Cristina L

    2012-07-01

    Consistently observed "strong eye gaze" has not been validated as a means of communication in girls with Rett syndrome, ubiquitously affected by apraxia, unable to reply either verbally or manually to questions during formal psychologic assessment. We examined nonverbal cognitive abilities and basic features of visual processing (visual discrimination attention/memory) by analyzing patterns of visual fixation in 44 girls with Rett syndrome, compared with typical control subjects. To determine features of visual fixation patterns, multiple pictures (with the location of the salient and presence/absence of novel stimuli as variables) were presented on the screen of a TS120 eye-tracker. Of the 44, 35 (80%) calibrated and exhibited meaningful patterns of visual fixation. They looked longer at salient stimuli (cartoon, 2.8 ± 2 seconds S.D., vs shape, 0.9 ± 1.2 seconds S.D.; P = 0.02), regardless of their position on the screen. They recognized novel stimuli, decreasing the fixation time on the central image when another image appeared on the periphery of the slide (2.7 ± 1 seconds S.D. vs 1.8 ± 1 seconds S.D., P = 0.002). Eye-tracking provides a feasible method for cognitive assessment and new insights into the "hidden" abilities of individuals with Rett syndrome. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Pritchard, D.A.

    1987-05-01

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

  20. 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.

  1. 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…

  2. 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.

  3. KALMAN FILTER BASED FEATURE ANALYSIS FOR TRACKING PEOPLE FROM AIRBORNE IMAGES

    Directory of Open Access Journals (Sweden)

    B. Sirmacek

    2012-09-01

    Full Text Available Recently, analysis of man events in real-time using computer vision techniques became a very important research field. Especially, understanding motion of people can be helpful to prevent unpleasant conditions. Understanding behavioral dynamics of people can also help to estimate future states of underground passages, shopping center like public entrances, or streets. In order to bring an automated solution to this problem, we propose a novel approach using airborne image sequences. Although airborne image resolutions are not enough to see each person in detail, we can still notice a change of color components in the place where a person exists. Therefore, we propose a color feature detection based probabilistic framework in order to detect people automatically. Extracted local features behave as observations of the probability density function (pdf of the people locations to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf. First, we use estimated pdf to detect boundaries of dense crowds. After that, using background information of dense crowds and previously extracted local features, we detect other people in non-crowd regions automatically for each image in the sequence. We benefit from Kalman filtering to track motion of detected people. To test our algorithm, we use a stadium entrance image data set taken from airborne camera system. Our experimental results indicate possible usage of the algorithm in real-life man events. We believe that the proposed approach can also provide crucial information to police departments and crisis management teams to achieve more detailed observations of people in large open area events to prevent possible accidents or unpleasant conditions.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Christos Asteriou

    2016-01-01

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

  6. Detection of goal events in soccer videos

    Science.gov (United States)

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

    2005-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Aleksej MAKAROV

    2016-02-01

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

  8. 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

    . 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...... 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...

  9. 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.

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

    OpenAIRE

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

    2014-01-01

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

  11. Features of single tracks in coaxial laser cladding of a NIbased self-fluxing alloy

    Directory of Open Access Journals (Sweden)

    Feldshtein Eugene

    2017-01-01

    Full Text Available In the present paper, the influence of coaxial laser cladding conditions on the dimensions, microstructure, phases and microhardness of Ni-based self-fluxing alloy single tracks is studied. The height and width of single tracks depend on the speed and distance of the laser cladding: increasing the nozzle distance from the deposited surface 1.4 times reduces the width of the track 1.2 - 1.3 times and increases its height 1.2 times. The increase of the laser spot speed 3 times reduces the track width 1.2 - 1.4 times and the height in 1.5 - 1.6 times. At the same time, the increase of the laser spot speed 3 times reduces the track width 1.2 - 1.4 times and the height 1.5 - 1.6 times. Regularities in the formation of single tracks microstructure with different cladding conditions are defined, as well as regularity of distribution of elements over the track depth and in the transient zone. The patterns of microhardness distribution over the track depth for different cladding conditions are found.

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

    International Nuclear Information System (INIS)

    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; Doerner, Jonas; Fimmers, Rolf

    2017-01-01

    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.)

  13. 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.)

  14. 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

  15. Ice Velocity Variations of the Polar Record Glacier (East Antarctica Using a Rotation-Invariant Feature-Tracking Approach

    Directory of Open Access Journals (Sweden)

    Tingting Liu

    2017-12-01

    Full Text Available In this study, the ice velocity changes from 2004 to 2015 of the Polar Record Glacier (PRG in East Antarctica were investigated based on a feature-tracking method using Landsat-7 enhanced thematic mapper plus (ETM+ and Landsat-8 operational land imager (OLI images. The flow field of the PRG curves make it difficult to generate ice velocities in some areas using the traditional normalized cross-correlation (NCC-based feature-tracking method. Therefore, a rotation-invariant parameter from scale-invariant feature transform (SIFT is introduced to build a novel rotation-invariant feature-tracking approach. The validation was performed based on multi-source images and the making earth system data records for use in research environments (MEaSUREs interferometric synthetic aperture radar (InSAR-based Antarctica ice velocity map data set. The results indicate that the proposed method is able to measure the ice velocity in more areas and performs as well as the traditional NCC-based feature-tracking method. The sequential ice velocities obtained present the variations in the PRG during this period. Although the maximum ice velocity of the frontal margin of the PRG and the frontal iceberg reached about 900 m/a and 1000 m/a, respectively, the trend from 2004 to 2015 showed no significant change. Under the interaction of the Polar Times Glacier and the Polarforschung Glacier, both the direction and the displacement of the PRG were influenced. This impact also led to higher velocities in the western areas of the PRG than in the eastern areas. In addition, elevation changes and frontal iceberg calving also impacted the ice velocity of the PRG.

  16. 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 (BoVW) 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 be conveniently 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 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 ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

  17. 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.

  18. User-assisted video segmentation system for visual communication

    Science.gov (United States)

    Wu, Zhengping; Chen, Chun

    2002-01-01

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

  19. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

  1. Video Book Trailers: Coming to a Library Near You! Spotlight Feature

    Science.gov (United States)

    Dopke-Wilson, MariRae

    2009-01-01

    This article features two library media specialists who discovered a way to motivate high school students to read. When most people go to the movies, the "coming attractions" or movie trailers are as anticipated as the popcorn! This Americana movie tradition hooks people again and again on what they will come back to see next. So, it's no surprise…

  2. Left and right atrial feature tracking in acute myocarditis: A feasibility study

    International Nuclear Information System (INIS)

    Dick, Anastasia; Schmidt, Björn; Michels, Guido; Bunck, Alexander C.; Maintz, David; Baeßler, Bettina

    2017-01-01

    Purpose: The present study aims at evaluating the feasibility and reproducibility of cardiac magnetic resonance (CMR) feature tracking (FT) derived strain and strain rate (SR) parameters of the left and right atrium (LA, RA) in patients with acute myocarditis as well as their potential to detect diastolic dysfunction. In addition, the diagnostic value of LA and RA strain parameters in the setting of acute myocarditis is investigated. Methods: CMR cine data of 30 patients with CMR-positive acute myocarditis were retrospectively analyzed. 25 age- and gender-matched healthy individuals served as a control. Analysis of longitudinal strain and SR of both atria was performed in two long-axis views using a dedicated FT-software. LA and RA deformation was analyzed including reservoir function (total strain [ε s ], peak positive SR [SR s ]), conduit function (passive strain [ε e ], peak early negative SR [SR e ]) and booster pump function (active strain [ε a ], peak late negative SR [SR a ]). Intra- and inter-observer reproducibility was assessed for all strain and SR parameters using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation (CV). Results: FT analyses of both atria were feasible in all patients and controls. Reproducibility was good for reservoir and conduit function parameters and moderate for booster pump function parameters. Myocarditis patients demonstrated an impaired LA reservoir and conduit function when compared to healthy controls (LA ε s : 32 ± 17 vs. 46 ± 13, p = 0.019; LA SR s : 1.5 ± 0.5 vs. 1.8 ± 0.5, p = 0.117; LA SR e : −1.3 ± 0.5 vs. −1.9 ± 0.5, p < 0.001), while LA booster pump function was preserved. In logistic regression and ROC-analyses, LA SR e proved to be the best independent predictor of acute myocarditis (AUC 0.80), and using LA SR e with a cut-off of −1.6 s −1 resulted in a diagnostic sensitivity of 83% and a specificity of 80%. Changes in RA phasic function parameters

  3. 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

  4. Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

    Science.gov (United States)

    Xie, Yaoqin; Xing, Lei; Gu, Jia; Liu, Wu

    2013-06-01

    Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.

  5. Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

    International Nuclear Information System (INIS)

    Xie Yaoqin; Gu Jia; Xing Lei; Liu Wu

    2013-01-01

    Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow. (paper)

  6. 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.

  7. 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.

  8. Automatic measurement for solid state track detectors

    International Nuclear Information System (INIS)

    Ogura, Koichi

    1982-01-01

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

  9. Decomposing price differentials due to ENERGY STARR labels and energy efficiency features in appliances: proxy for market share tracking?

    International Nuclear Information System (INIS)

    Gardner, John; Skumatz, Lisa A.

    2005-01-01

    This paper summarizes recent work using statistical methods to examine the portions of the apparent price differences for a variety of appliances that are attributable to efficiency labels or components of efficient measures. The work stems from research examining progress in market transformation. The goal was to monitor market progress in the premium associated with efficient equipment compared to standard equipment - and potentially track these changes (hopefully, according to logic, declining) over time. However, the incremental cost metric is always confounded by the fact that the 'feature bundle' on appliances and lighting is not consistent ( i.e. , many efficient products are loaded up with other, high-end features). Based on work conducted by the authors some years ago, we adapted statistical models to decompose the price differentials for efficient and standard refrigerators, clothes washers, and dish washers. The authors used site visits and web searches to gather data on appliance prices and features for a set of efficient and standard models. The authors first examined apparent (raw) price differentials between efficient and standard models. Then, using regression techniques to control for differences in features on the measures, the differences attributable to various features - and in particular to energy efficient features and logos - were estimated. The results showed that while the apparent (gross) price differences for efficient measures are high, the percentage and dollar differences decrease dramatically when the price differences statistically attributable to other features of the measure are accounted for. The work illustrates a promising approach for three important applications in program planning and evaluation: tracking market progress within and between states or service territories, using a proxy variable that is less expensive and complicated to measure than direct indicators of sales or market share, identifying appropriate levels for

  10. Left and right atrial feature tracking in acute myocarditis: A feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Dick, Anastasia, E-mail: anastasia-dick@web.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany); Schmidt, Björn, E-mail: bjoernschmidt1989@gmx.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany); Michels, Guido, E-mail: guido.michels@uk-koeln.de [Department III of Internal Medicine, Heart Centre, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany); Bunck, Alexander C., E-mail: alexander.bunck@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany); Maintz, David, E-mail: david.maintz@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany); Baeßler, Bettina, E-mail: bettina.baessler@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, 50937 Cologne (Germany)

    2017-04-15

    Purpose: The present study aims at evaluating the feasibility and reproducibility of cardiac magnetic resonance (CMR) feature tracking (FT) derived strain and strain rate (SR) parameters of the left and right atrium (LA, RA) in patients with acute myocarditis as well as their potential to detect diastolic dysfunction. In addition, the diagnostic value of LA and RA strain parameters in the setting of acute myocarditis is investigated. Methods: CMR cine data of 30 patients with CMR-positive acute myocarditis were retrospectively analyzed. 25 age- and gender-matched healthy individuals served as a control. Analysis of longitudinal strain and SR of both atria was performed in two long-axis views using a dedicated FT-software. LA and RA deformation was analyzed including reservoir function (total strain [ε{sub s}], peak positive SR [SR{sub s}]), conduit function (passive strain [ε{sub e}], peak early negative SR [SR{sub e}]) and booster pump function (active strain [ε{sub a}], peak late negative SR [SR{sub a}]). Intra- and inter-observer reproducibility was assessed for all strain and SR parameters using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation (CV). Results: FT analyses of both atria were feasible in all patients and controls. Reproducibility was good for reservoir and conduit function parameters and moderate for booster pump function parameters. Myocarditis patients demonstrated an impaired LA reservoir and conduit function when compared to healthy controls (LA ε{sub s}: 32 ± 17 vs. 46 ± 13, p = 0.019; LA SR{sub s}: 1.5 ± 0.5 vs. 1.8 ± 0.5, p = 0.117; LA SR{sub e}: −1.3 ± 0.5 vs. −1.9 ± 0.5, p < 0.001), while LA booster pump function was preserved. In logistic regression and ROC-analyses, LA SR{sub e} proved to be the best independent predictor of acute myocarditis (AUC 0.80), and using LA SR{sub e} with a cut-off of −1.6 s{sup −1} resulted in a diagnostic sensitivity of 83% and a specificity of

  11. New method for identifying features of an image on a digital video display

    Science.gov (United States)

    Doyle, Michael D.

    1991-04-01

    The MetaMap process extends the concept of direct manipulation human-computer interfaces to new limits. Its specific capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. The correlation is accomplished through reprogramming of both the color map and the image so that discrete image elements comprise unique sets of color indices. This process allows the correlation to be accomplished with very efficient data storage and program execution times. Image databases adapted to this process become object-oriented as a result. Very sophisticated interrelationships can be set up between images text and program control mechanisms using this process. An application of this interfacing process to the design of an interactive atlas of medical histology as well as other possible applications are described. The MetaMap process is protected by U. S. patent #4

  12. Tracking Persons-of-Interest via Unsupervised Representation Adaptation

    OpenAIRE

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

    2017-01-01

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

  13. Detecting PHG frames in wireless capsule endoscopy video by integrating rough global dominate-color with fine local texture features

    Science.gov (United States)

    Liu, Xiaoqi; Wang, Chengliang; Bai, Jianying; Liao, Guobin

    2018-02-01

    Portal hypertensive gastropathy (PHG) is common in gastrointestinal (GI) diseases, and a severe stage of PHG (S-PHG) is a source of gastrointestinal active bleeding. Generally, the diagnosis of PHG is made visually during endoscopic examination; compared with traditional endoscopy, (wireless capsule endoscopy) WCE with noninvasive and painless is chosen as a prevalent tool for visual observation of PHG. However, accurate measurement of WCE images with PHG is a difficult task due to faint contrast and confusing variations in background gastric mucosal tissue for physicians. Therefore, this paper proposes a comprehensive methodology to automatically detect S-PHG images in WCE video to help physicians accurately diagnose S-PHG. Firstly, a rough dominatecolor-tone extraction approach is proposed for better describing global color distribution information of gastric mucosa. Secondly, a hybrid two-layer texture acquisition model is designed by integrating co-occurrence matrix into local binary pattern to depict complex and unique gastric mucosal microstructure local variation. Finally, features of mucosal color and microstructure texture are merged into linear support vector machine to accomplish this automatic classification task. Experiments were implemented on an annotated data set including 1,050 SPHG and 1,370 normal images collected from 36 real patients of different nationalities, ages and genders. By comparison with three traditional texture extraction methods, our method, combined with experimental results, performs best in detection of S-PHG images in WCE video: the maximum of accuracy, sensitivity and specificity reach 0.90, 0.92 and 0.92 respectively.

  14. 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.

  15. A transition radiation detector which features accurate tracking and dE/dx particle identification

    International Nuclear Information System (INIS)

    O'Brien, E.; Lissauer, D.; McCorkle, S.; Polychronakos, V.; Takai, H.; Chi, C.Y.; Nagamiya, S.; Sippach, W.; Toy, M.; Wang, D.; Wang, Y.F.; Wiggins, C.; Willis, W.; Cherniatin, V.; Dolgoshein, B.; Bennett, M.; Chikanian, A.; Kumar, S.; Mitchell, J.T.; Pope, K.

    1991-01-01

    We describe the results of a test run involving a Transition Radiation Detector that can both distinguish electrons from pions with momenta greater than 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 is effective above 1.5 GeV/c. Combined, the electron-pion separation is better than 5 x l0 2 . The single-wire, track-position resolution for the TRD is ∼230μm

  16. 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.

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

    DEFF Research Database (Denmark)

    Baatrup, E; Bayley, M

    1993-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-08-15

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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  20. Quantification of biventricular myocardial function using cardiac magnetic resonance feature tracking, endocardial border delineation and echocardiographic speckle tracking in patients with repaired tetralogy of fallot and healthy controls

    Science.gov (United States)

    2012-01-01

    Background Parameters of myocardial deformation have been suggested to be superior to conventional measures of ventricular function in patients with tetralogy of Fallot (ToF), but have required non-routine, tagged cardiovascular magnetic resonance (CMR) techniques. We assessed biventricular myocardial function using CMR cine-based feature tracking (FT) and compared it to speckle tracking echocardiography (STE) and to simple endocardial border delineation (EBD). In addition, the relation between parameters of myocardial deformation and clinical parameters was assessed. Methods Overall, 28 consecutive adult patients with repaired ToF (age 40.4 ± 13.3 years) underwent standard steady-state-free precession sequence CMR, echocardiography, and cardiopulmonary exercise testing. In addition, 25 healthy subjects served as controls. Myocardial deformation was assessed by CMR based FT (TomTec Diogenes software), CMR based EBD (using custom written software) and STE (TomTec Cardiac Performance Analysis software). Results Feature tracking was feasible in all subjects. A close agreement was found between measures of global left (LV) and right ventricular (RV) global strain. Interobserver agreement for FT and STE was similar for longitudinal LV global strain, but FT showed better inter-observer reproducibility than STE for circumferential or radial LV and longitudinal RV global strain. Reproducibility of regional strain on FT was, however, poor. The relative systolic length change of the endocardial border measured by EBD yielded similar results to FT global strain. Clinically, biventricular longitudinal strain on FT was reduced compared to controls (P < 0.0001) and was related to the number of previous cardiac operations. In addition, FT derived RV strain was related to exercise capacity and VE/VCO2-slope. Conclusions Although neither the inter-study reproducibility nor accuracy of FT software were investigated, and its inter-observer reproducibility for regional

  1. 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.

  2. 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.

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

    International Nuclear Information System (INIS)

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

    1983-07-01

    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. 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.

  5. Speckle tracking in a phantom and feature-based tracking in liver in the presence of respiratory motion using 4D ultrasound

    International Nuclear Information System (INIS)

    Harris, Emma J; Miller, Naomi R; Bamber, Jeffrey C; Symonds-Tayler, J Richard N; Evans, Philip M

    2010-01-01

    We have evaluated a 4D ultrasound-based motion tracking system developed for tracking of abdominal organs during therapy. Tracking accuracy and precision were determined using a tissue-mimicking phantom, by comparing tracked motion with known 3D sinusoidal motion. The feasibility of tracking 3D liver motion in vivo was evaluated by acquiring 4D ultrasound data from four healthy volunteers. For two of these volunteers, data were also acquired whilst simultaneously measuring breath flow using a spirometer. Hepatic blood vessels, tracked off-line using manual tracking, were used as a reference to assess, in vivo, two types of automated tracking algorithm: incremental (from one volume to the next) and non-incremental (from the first volume to each subsequent volume). For phantom-based experiments, accuracy and precision (RMS error and SD) were found to be 0.78 mm and 0.54 mm, respectively. For in vivo measurements, mean absolute distance and standard deviation of the difference between automatically and manually tracked displacements were less than 1.7 mm and 1 mm respectively in all directions (left-right, anterior-posterior and superior-inferior). In vivo non-incremental tracking gave the best agreement. In both phantom and in vivo experiments, tracking performance was poorest for the elevational component of 3D motion. Good agreement between automatically and manually tracked displacements indicates that 4D ultrasound-based motion tracking has potential for image guidance applications in therapy.

  6. Intelligent keyframe extraction for video printing

    Science.gov (United States)

    Zhang, Tong

    2004-10-01

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

    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 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.)

  8. 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.)

  9. 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

  10. 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.

  11. 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.

  12. An Eye-tracking Study of Feature-based Choice in One-shot Games

    DEFF Research Database (Denmark)

    Devetag, Giovanna; Di Guida, Sibilla; Polonio, Luca

    2016-01-01

    for a subset of game outcomes. We analyze subjects’ eye movements while playing a series of two-person, 3x3 one-shot games in normal form. Games within each class differ by a set of descriptive features (i.e., features that can be changed without altering the game equilibrium properties). Data show......Previous experimental research suggests that individuals apply rules of thumb to a simplified mental model of the "real" decision problem. We claim that this simplification is obtained either by neglecting the other players' incentives and beliefs or by taking them into consideration only...... that subjects on average perform partial or non-strategic analysis of the payoff matrix, often ignoring the opponent´s payoffs and rarely performing the necessary steps to detect dominance. Our analysis of eye-movements supports the hypothesis that subjects use simple decision rules such as "choose the strategy...

  13. Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

    Science.gov (United States)

    Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

    2016-06-01

    Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

  14. Heartbeat Rate Measurement from Facial Video

    DEFF Research Database (Denmark)

    Haque, Mohammad Ahsanul; Irani, Ramin; Nasrollahi, Kamal

    2016-01-01

    Heartbeat Rate (HR) reveals a person’s health condition. This paper presents an effective system for measuring HR from facial videos acquired in a more realistic environment than the testing environment of current systems. The proposed method utilizes a facial feature point tracking method...... by combining a ‘Good feature to track’ and a ‘Supervised descent method’ in order to overcome the limitations of currently available facial video based HR measuring systems. Such limitations include, e.g., unrealistic restriction of the subject’s movement and artificial lighting during data capture. A face...

  15. 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.

  16. Functional measurements based on feature tracking of cine magnetic resonance images identify left ventricular segments with myocardial scar

    Directory of Open Access Journals (Sweden)

    Nylander Eva

    2009-11-01

    Full Text Available Abstract Background The aim of the study was to perform a feature tracking analysis on cine magnetic resonance (MR images to elucidate if functional measurements of the motion of the left ventricular wall may detect scar defined with gadolinium enhanced MR. Myocardial contraction can be measured in terms of the velocity, displacement and local deformation (strain of a particular myocardial segment. Contraction of the myocardial wall will be reduced in the presence of scar and as a consequence of reduced myocardial blood flow. Methods Thirty patients (3 women and 27 men were selected based on the presence or absence of extensive scar in the anteroseptal area of the left ventricle. The patients were investigated in stable clinical condition, 4-8 weeks post ST-elevation myocardial infarction treated with percutaneous coronary intervention. Seventeen had a scar area >75% in at least one anteroseptal segment (scar and thirteen had scar area Results In the scar patients, segments with scar showed lower functional measurements than remote segments. Radial measurements of velocity, displacement and strain performed better in terms of receiver-operator-characteristic curves (ROC than the corresponding longitudinal measurements. The best area-under-curve was for radial strain, 0.89, where a cut-off value of 38.8% had 80% sensitivity and 86% specificity for the detection of a segment with scar area >50%. As a percentage of the mean, intraobserver variability was 16-14-26% for radial measurements of displacement-velocity-strain and corresponding interobserver variability was 13-12-18%. Conclusion Feature tracking analysis of cine-MR displays velocity, displacement and strain in the radial and longitudinal direction and may be used for the detection of transmural scar. The accuracy and repeatability of the radial functional measurements is satisfactory and global measures agree.

  17. Direct comparison of cardiac magnetic resonance feature tracking and 2D/3D echocardiography speckle tracking for evaluation of global left ventricular strain.

    Science.gov (United States)

    Obokata, Masaru; Nagata, Yasufumi; Wu, Victor Chien-Chia; Kado, Yuichiro; Kurabayashi, Masahiko; Otsuji, Yutaka; Takeuchi, Masaaki

    2016-05-01

    Cardiac magnetic resonance (CMR) feature tracking (FT) with steady-state free precession (SSFP) has advantages over traditional myocardial tagging to analyse left ventricular (LV) strain. However, direct comparisons of CMRFT and 2D/3D echocardiography speckle tracking (2/3DEST) for measurement of LV strain are limited. The aim of this study was to investigate the feasibility and reliability of CMRFT and 2D/3DEST for measurement of global LV strain. We enrolled 106 patients who agreed to undergo both CMR and 2D/3DE on the same day. SSFP images at multiple short-axis and three apical views were acquired. 2DE images from three levels of short-axis, three apical views, and 3D full-volume datasets were also acquired. Strain data were expressed as absolute values. Feasibility was highest in CMRFT, followed by 2DEST and 3DEST. Analysis time was shortest in 3DEST, followed by CMRFT and 2DEST. There was good global longitudinal strain (GLS) correlation between CMRFT and 2D/3DEST (r = 0.83 and 0.87, respectively) with the limit of agreement (LOA) ranged from ±3.6 to ±4.9%. Excellent global circumferential strain (GCS) correlation between CMRFT and 2D/3DEST was observed (r = 0.90 and 0.88) with LOA of ±6.8-8.5%. Global radial strain showed fair correlations (r = 0.69 and 0.82, respectively) with LOA ranged from ±12.4 to ±16.3%. CMRFT GCS showed least observer variability with highest intra-class correlation. Although not interchangeable, the high GLS and GCS correlation between CMRFT and 2D/3DEST makes CMRFT a useful modality for quantification of global LV strain in patients, especially those with suboptimal echo image quality. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

  18. 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.

  19. 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.

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

    Institute of Scientific and Technical Information of China (English)

    赵林; 冯燕; 吕维

    2011-01-01

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

  1. 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

  2. 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...

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

    Science.gov (United States)

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

    2014-01-01

    Animal models of stroke have been crucial in advancing our understanding of the pathophysiology of cerebral ischemia. Currently, the standards for determining neurological deficit in rodents are the Bederson and Garcia scales, manual assessments scoring animals based on parameters ranked on a narrow scale of severity. Automated open field analysis of a live-video tracking system that analyzes animal behavior may provide a more sensitive test. Results obtained from the manual Bederson and Garcia scales did not show significant differences between pre- and post-stroke animals in a small cohort. When using the same cohort, however, post-stroke data obtained from automated open field analysis showed significant differences in several parameters. Furthermore, large cohort analysis also demonstrated increased sensitivity with automated open field analysis versus the Bederson and Garcia scales. These early data indicate use of automated open field analysis software may provide a more sensitive assessment when compared to traditional Bederson and Garcia scales.

  4. 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.

  5. 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.

  6. Video Comparator

    International Nuclear Information System (INIS)

    Rose, R.P.

    1978-01-01

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

  7. A Multiple Model SNR/RCS Likelihood Ratio Score for Radar-Based Feature-Aided Tracking

    National Research Council Canada - National Science Library

    Slocumb, Benjamin J; Klusman, III, Michael E

    2005-01-01

    ...) and radar cross section (RCS) for use in narrowband radar tracking. The formulation requires an estimate of the target mean RCS, and a key challenge is the tracking of the mean RCS through significant jumps due to aspect dependencies...

  8. 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…

  9. Physics and Video Analysis

    Science.gov (United States)

    Allain, Rhett

    2016-05-01

    We currently live in a world filled with videos. There are videos on YouTube, feature movies and even videos recorded with our own cameras and smartphones. These videos present an excellent opportunity to not only explore physical concepts, but also inspire others to investigate physics ideas. With video analysis, we can explore the fantasy world in science-fiction films. We can also look at online videos to determine if they are genuine or fake. Video analysis can be used in the introductory physics lab and it can even be used to explore the make-believe physics embedded in video games. This book covers the basic ideas behind video analysis along with the fundamental physics principles used in video analysis. The book also includes several examples of the unique situations in which video analysis can be used.

  10. 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.

  11. Feature tracking CMR reveals abnormal strain in preclinical arrhythmogenic right ventricular dysplasia/ cardiomyopathy: a multisoftware feasibility and clinical implementation study.

    Science.gov (United States)

    Bourfiss, Mimount; Vigneault, Davis M; Aliyari Ghasebeh, Mounes; Murray, Brittney; James, Cynthia A; Tichnell, Crystal; Mohamed Hoesein, Firdaus A; Zimmerman, Stefan L; Kamel, Ihab R; Calkins, Hugh; Tandri, Harikrishna; Velthuis, Birgitta K; Bluemke, David A; Te Riele, Anneline S J M

    2017-09-01

    Regional right ventricular (RV) dysfunction is the hallmark of Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C), but is currently only qualitatively evaluated in the clinical setting. Feature Tracking Cardiovascular Magnetic Resonance (FT-CMR) is a novel quantitative method that uses cine CMR to calculate strain values. However, most prior FT-CMR studies in ARVD/C have focused on global RV strain using different software methods, complicating implementation of FT-CMR in clinical practice. We aimed to assess the clinical value of global and regional strain using FT-CMR in ARVD/C and to determine differences between commercially available FT-CMR software packages. We analyzed cine CMR images of 110 subjects (39 overt ARVD/C [mutation+/phenotype+], 40 preclinical ARVD/C [mutation+/phenotype-] and 31 control) for global and regional (subtricuspid, anterior, apical) RV strain in the horizontal longitudinal axis using four FT-CMR software methods (Multimodality Tissue Tracking, TomTec, Medis and Circle Cardiovascular Imaging). Intersoftware agreement was assessed using Bland Altman plots. For global strain, all methods showed reduced strain in overt ARVD/C patients compared to control subjects (p  0.275). For regional strain, overt ARVD/C patients showed reduced strain compared to control subjects in all segments which reached statistical significance in the subtricuspid region for all software methods (p < 0.037), in the anterior wall for two methods (p < 0.005) and in the apex for one method (p = 0.012). Preclinical subjects showed abnormal subtricuspid strain compared to control subjects using one of the software methods (p = 0.009). Agreement between software methods for absolute strain values was low (Intraclass Correlation Coefficient = 0.373). Despite large intersoftware variability of FT-CMR derived strain values, all four software methods distinguished overt ARVD/C patients from control subjects by both global and subtricuspid

  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. 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.

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

    Science.gov (United States)

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

    2018-02-01

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

  15. 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.

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

    Science.gov (United States)

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

    2016-05-01

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

  17. NucliTrack: an integrated nuclei tracking application.

    Science.gov (United States)

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

    2017-10-15

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

  18. 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...

  19. The intra-observer reproducibility of cardiovascular magnetic resonance myocardial feature tracking strain assessment is independent of field strength

    International Nuclear Information System (INIS)

    Schuster, Andreas; Morton, Geraint; Hussain, Shazia T.

    2013-01-01

    Background: Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising novel method for quantification of myocardial wall mechanics from standard steady-state free precession (SSFP) images. We sought to determine whether magnetic field strength affects the intra-observer reproducibility of CMR-FT strain analysis. Methods: We studied 2 groups, each consisting of 10 healthy subjects, at 1.5 T or 3 T Analysis was performed at baseline and after 4 weeks using dedicated CMR-FT prototype software (Tomtec, Germany) to analyze standard SSFP cine images. Right ventricular (RV) and left ventricular (LV) longitudinal strain (Ell RV and Ell LV ) and LV long-axis radial strain (Err LAX ) were derived from the 4-chamber cine, and LV short-axis circumferential and radial strains (Ecc SAX , Err SAX ) from the short-axis orientation. Strain parameters were assessed together with LV ejection fraction (EF) and volumes. Intra-observer reproducibility was determined by comparing the first and the second analysis in both groups. Results: In all volunteers resting strain parameters were successfully derived from the SSFP images. There was no difference in strain parameters, volumes and EF between field strengths (p > 0.05). In general Ecc SAX was the most reproducible strain parameter as determined by the coefficient of variation (CV) at 1.5 T (CV 13.3% and 46% global and segmental respectively) and 3 T (CV 17.2% and 31.1% global and segmental respectively). The least reproducible parameter was Ell RV (CV 1.5 T 28.7% and 53.2%; 3 T 43.5% and 63.3% global and segmental respectively). Conclusions: CMR-FT results are similar with reasonable intra-observer reproducibility in different groups of volunteers at 1.5 T and 3 T. CMR-FT is a promising novel technique and our data indicate that results might be transferable between field strengths. However there is a considerable amount of segmental variability indicating that further refinements are needed before CMR

  20. Normal values for myocardial deformation within the right heart measured by feature-tracking cardiovascular magnetic resonance imaging.

    Science.gov (United States)

    Liu, Boyang; Dardeer, Ahmed M; Moody, William E; Edwards, Nicola C; Hudsmith, Lucy E; Steeds, Richard P

    2018-02-01

    Reproducible and repeatable assessment of right heart function is vital for monitoring congenital and acquired heart disease. There is increasing evidence for the additional value of myocardial deformation (strain and strain rate) in determining prognosis. This study aims to determine the reproducibility of deformation analyses in the right heart using cardiovascular magnetic resonance feature tracking (FT-CMR); and to establish normal ranges within an adult population. A cohort of 100 healthy subjects containing 10 males and 10 females from each decade of life between the ages of 20 and 70 without known congenital or acquired cardiovascular disease, hypertension, diabetes, dyslipidaemia or renal, hepatic, haematologic and systemic inflammatory disorders underwent FT-CMR assessment of right ventricular (RV) and right atrial (RA) myocardial strain and strain rate. RV longitudinal strain (Ell) was -21.9±3.24% (FW+S Ell) and -24.2±3.59% (FW-Ell). Peak systolic strain rate (S') was -1.45±0.39s -1 (FW+S) and -1.54±0.41s -1 (FW). Early diastolic strain rate (E') was 1.04±0.26s -1 (FW+S) and 1.04±0.33s -1 (FW). Late diastolic strain rate (A') was 0.94±0.33s -1 (FW+S) and 1.08±0.33s -1 (FW). RA peak strain was -21.1±3.76%. The intra- and inter-observer ICC for RV Ell (FW+S) was 0.92 and 0.80 respectively, while for RA peak strain was 0.92 and 0.89 respectively. Normal values of RV & RA deformation for healthy individuals using FT-CMR are provided with good RV Ell and RA peak strain reproducibility. Strain rate suffered from sub-optimal reproducibility and may not be satisfactory for clinical use. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2018-04-01

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

  2. 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.

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

    International Nuclear Information System (INIS)

    Nakamura, M; Matsuo, Y; Mukumoto, N; Iizuka, Y; Yokota, K; Mizowaki, T; Hiraoka, M; Nakao, M

    2016-01-01

    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.

  4. 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

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

    OpenAIRE

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

    2014-01-01

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

  6. 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.

  7. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

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

  8. Deception Detection in Videos

    OpenAIRE

    Wu, Zhe; Singh, Bharat; Davis, Larry S.; Subrahmanian, V. S.

    2017-01-01

    We present a system for covert automated deception detection in real-life courtroom trial videos. We study the importance of different modalities like vision, audio and text for this task. On the vision side, our system uses classifiers trained on low level video features which predict human micro-expressions. We show that predictions of high-level micro-expressions can be used as features for deception prediction. Surprisingly, IDT (Improved Dense Trajectory) features which have been widely ...

  9. 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.

  10. Tracking the Correlation Between CpG Island Methylator Phenotype and Other Molecular Features and Clinicopathological Features in Human Colorectal Cancers: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Zong, Liang; Abe, Masanobu; Ji, Jiafu; Zhu, Wei-Guo; Yu, Duonan

    2016-03-10

    The controversy of CpG island methylator phenotype (CIMP) in colorectal cancers (CRCs) persists, despite many studies that have been conducted on its correlation with molecular and clinicopathological features. To drive a more precise estimate of the strength of this postulated relationship, a meta-analysis was performed. A comprehensive search for studies reporting molecular and clinicopathological features of CRCs stratified by CIMP was performed within the PubMed, EMBASE, and Cochrane Library. CIMP was defined by either one of the three panels of gene-specific CIMP markers (Weisenberger panel, classic panel, or a mixture panel of the previous two) or the genome-wide DNA methylation profile. The associations of CIMP with outcome parameters were estimated using odds ratio (OR) or weighted mean difference (WMD) or hazard ratios (HRs) with 95% confidence interval (CI) for each study using a fixed effects or random effects model. A total of 29 studies involving 9,393 CRC patients were included for analysis. We observed more BRAF mutations (OR 34.87; 95% CI, 22.49-54.06) and microsatellite instability (MSI) (OR 12.85 95% CI, 8.84-18.68) in CIMP-positive vs. -negative CRCs, whereas KRAS mutations were less frequent (OR 0.47; 95% CI, 0.30-0.75). Subgroup analysis showed that only the genome-wide methylation profile-defined CIMP subset encompassed all BRAF-mutated CRCs. As expected, CIMP-positive CRCs displayed significant associations with female (OR 0.64; 95% CI, 0.56-0.72), older age at diagnosis (WMD 2.77; 95% CI, 1.15-4.38), proximal location (OR 6.91; 95% CI, 5.17-9.23), mucinous histology (OR 3.81; 95% CI, 2.93-4.95), and poor differentiation (OR 4.22; 95% CI, 2.52-7.08). Although CIMP did not show a correlation with tumor stage (OR 1.10; 95% CI, 0.82-1.46), it was associated with shorter overall survival (HR 1.73; 95% CI, 1.27-2.37). The meta-analysis highlights that CIMP-positive CRCs take their own molecular feature, especially overlapping with BRAF mutations

  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. Video Quality Prediction over Wireless 4G

    KAUST Repository

    Lau, Chun Pong; Zhang, Xiangliang; Shihada, Basem

    2013-01-01

    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.

  13. Optimum location of external markers using feature selection algorithms for real-time tumor tracking in external-beam radiotherapy: a virtual phantom study.

    Science.gov (United States)

    Nankali, Saber; Torshabi, Ahmad Esmaili; Miandoab, Payam Samadi; Baghizadeh, Amin

    2016-01-08

    In external-beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation-based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two "Genetic" and "Ranker" searching procedures. The performance of these algorithms has been evaluated using four-dimensional extended cardiac-torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro-fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F-test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation-based feature selection algorithm, in

  14. Optimum location of external markers using feature selection algorithms for real‐time tumor tracking in external‐beam radiotherapy: a virtual phantom study

    Science.gov (United States)

    Nankali, Saber; Miandoab, Payam Samadi; Baghizadeh, Amin

    2016-01-01

    In external‐beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation‐based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two “Genetic” and “Ranker” searching procedures. The performance of these algorithms has been evaluated using four‐dimensional extended cardiac‐torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro‐fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F‐test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation‐based feature

  15. Extremely Selective Attention: Eye-Tracking Studies of the Dynamic Allocation of Attention to Stimulus Features in Categorization

    Science.gov (United States)

    Blair, Mark R.; Watson, Marcus R.; Walshe, R. Calen; Maj, Fillip

    2009-01-01

    Humans have an extremely flexible ability to categorize regularities in their environment, in part because of attentional systems that allow them to focus on important perceptual information. In formal theories of categorization, attention is typically modeled with weights that selectively bias the processing of stimulus features. These theories…

  16. 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

  17. Videos - The National Guard

    Science.gov (United States)

    Legislative Liaison Small Business Programs Social Media State Websites Videos Featured Videos On Every Front 2:17 Always Ready, Always There National Guard Bureau Diversity and Inclusion Play Button 1:04 National Guard Bureau Diversity and Inclusion The ChalleNGe Ep.5 [Graduation] Play Button 3:51 The

  18. Visual Analytics and Storytelling through Video

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-10-31

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

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

    International Nuclear Information System (INIS)

    Stueber, P; Wissel, T; Wagner, B; Bruder, R; Schweikard, A; Ernst, F

    2014-01-01

    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 feature

  20. 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

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

    Science.gov (United States)

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

    2017-10-01

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

  2. 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.

  3. Thermal Tracking of Sports Players

    DEFF Research Database (Denmark)

    Gade, Rikke; Moeslund, Thomas B.

    2014-01-01

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

  4. Dashboard Videos

    Science.gov (United States)

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

    2012-01-01

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

  5. Robust Object Tracking with a Hierarchical Ensemble Framework

    Science.gov (United States)

    2016-10-09

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

  6. Feasibility Study On Missile Launch Detection And Trajectory Tracking

    Science.gov (United States)

    2016-09-01

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

  7. 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....

  8. Video enhancement : content classification and model selection

    NARCIS (Netherlands)

    Hu, H.

    2010-01-01

    The purpose of video enhancement is to improve the subjective picture quality. The field of video enhancement includes a broad category of research topics, such as removing noise in the video, highlighting some specified features and improving the appearance or visibility of the video content. The

  9. Video sensor architecture for surveillance applications.

    Science.gov (United States)

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

    2012-01-01

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

  10. Video Sensor Architecture for Surveillance Applications

    Directory of Open Access Journals (Sweden)

    José E. Simó

    2012-02-01

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

  11. 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

  12. Intra- and inter-observer reproducibility of global and regional magnetic resonance feature tracking derived strain parameters of the left and right ventricle

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Björn, E-mail: bjoernschmidt1989@gmx.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Dick, Anastasia, E-mail: anastasia-dick@web.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Treutlein, Melanie, E-mail: melanie-treutlein@web.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Schiller, Petra, E-mail: petra.schiller@uni-koeln.de [Institute of Medical Statistics, Informatics and Epidemiology, University of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Bunck, Alexander C., E-mail: alexander.bunck@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Maintz, David, E-mail: david.maintz@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Baeßler, Bettina, E-mail: bettina.baessler@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany)

    2017-04-15

    Highlights: • Left and right ventricular CMR feature tracking is highly reproducible. • The only exception is radial strain and strain rate. • Sample size estimations are presented as a practical reference for future studies. - Abstract: Objectives: To investigate the reproducibility of regional and global strain and strain rate (SR) parameters of both ventricles and to determine sample sizes for all investigated strain and SR parameters in order to generate a practical reference for future studies. Materials and methods: The study population consisted of 20 healthy individuals and 20 patients with acute myocarditis. Cine sequences in three horizontal long axis views and a stack of short axis views covering the entire left and right ventricle (LV, RV) were retrospectively analysed using a dedicated feature tracking (FT) software algorithm (TOMTEC). For intra-observer analysis, one observer analysed CMR images of all patients and volunteers twice. For inter-observer analysis, three additional blinded observers analysed the same datasets once. Intra- and inter-observer reproducibility were tested in all patients and controls using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation. Results: Intra-observer reproducibility of global LV strain and SR parameters was excellent (range of ICCs: 0.81–1.00), the only exception being global radial SR with a poor reproducibility (ICC 0.23). On a regional level, basal and midventricular strain and SR parameters were more reproducible when compared to apical parameters. Inter-observer reproducibility of all LV parameters was slightly lower than intra-observer reproducibility, yet still good to excellent for all global and regional longitudinal and circumferential strain and SR parameters (range of ICCs: 0.66–0.93). Similar to the LV, all global RV longitudinal and circumferential strain and SR parameters showed an excellent reproducibility, (range of ICCs: 0.75–0

  13. Intra- and inter-observer reproducibility of global and regional magnetic resonance feature tracking derived strain parameters of the left and right ventricle

    International Nuclear Information System (INIS)

    Schmidt, Björn; Dick, Anastasia; Treutlein, Melanie; Schiller, Petra; Bunck, Alexander C.; Maintz, David; Baeßler, Bettina

    2017-01-01

    Highlights: • Left and right ventricular CMR feature tracking is highly reproducible. • The only exception is radial strain and strain rate. • Sample size estimations are presented as a practical reference for future studies. - Abstract: Objectives: To investigate the reproducibility of regional and global strain and strain rate (SR) parameters of both ventricles and to determine sample sizes for all investigated strain and SR parameters in order to generate a practical reference for future studies. Materials and methods: The study population consisted of 20 healthy individuals and 20 patients with acute myocarditis. Cine sequences in three horizontal long axis views and a stack of short axis views covering the entire left and right ventricle (LV, RV) were retrospectively analysed using a dedicated feature tracking (FT) software algorithm (TOMTEC). For intra-observer analysis, one observer analysed CMR images of all patients and volunteers twice. For inter-observer analysis, three additional blinded observers analysed the same datasets once. Intra- and inter-observer reproducibility were tested in all patients and controls using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation. Results: Intra-observer reproducibility of global LV strain and SR parameters was excellent (range of ICCs: 0.81–1.00), the only exception being global radial SR with a poor reproducibility (ICC 0.23). On a regional level, basal and midventricular strain and SR parameters were more reproducible when compared to apical parameters. Inter-observer reproducibility of all LV parameters was slightly lower than intra-observer reproducibility, yet still good to excellent for all global and regional longitudinal and circumferential strain and SR parameters (range of ICCs: 0.66–0.93). Similar to the LV, all global RV longitudinal and circumferential strain and SR parameters showed an excellent reproducibility, (range of ICCs: 0.75–0

  14. Video Vectorization via Tetrahedral Remeshing.

    Science.gov (United States)

    Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

    2017-02-09

    We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

  15. 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.

  16. Video pedagogy

    OpenAIRE

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

    2016-01-01

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

  17. 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.

  18. 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.

  19. Myocardial deformation assessed by longitudinal strain. Chamber specific normative data for CMR-feature tracking from the German competence network for congenital heart defects

    International Nuclear Information System (INIS)

    Shang, Quanliang; Patel, Shivani; Danford, David A.; Kutty, Shelby; Steinmetz, Michael; Schuster, Andreas; Beerbaum, Philipp; Sarikouch, Samir

    2018-01-01

    Left ventricular two-dimensional global longitudinal strain (LS) is superior to ejection fraction (EF) as predictor of outcome. We provide reference data for atrial and ventricular global LS during childhood and adolescence by CMR feature tracking (FT). We prospectively enrolled 115 healthy subjects (56 male, mean age 12.4 ± 4.1 years) at a single institution. CMR consisted of standard two-dimensional steady-state free-precession acquisitions. CMR-FT was performed on ventricular horizontal long-axis images for derivation of right and left atrial (RA, LA) and right and left ventricular (RV, LV) peak global LS. End-diastolic volumes (EDVs) and EF were measured. Correlations were explored for LS with age, EDV and EF of each chamber. Mean±SD of LS (%) for RA, RV, LA and LV were 26.56±10.2, -17.96±5.4, 26.45±10.6 and -17.47±5, respectively. There was a positive correlation of LS in LA, LV, RA and RV with corresponding EF (all P<0.05); correlations with age were weak. Gender-wise differences were not significant for atrial and ventricular LS, strain rate and displacement. Inter- and intra-observer comparisons showed moderate agreements. Chamber-specific nomograms for paediatric atrial and ventricular LS are provided to serve as clinical reference, and to facilitate CMR-based deformation research. (orig.)

  20. 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.

  1. Myocardial deformation assessed by longitudinal strain. Chamber specific normative data for CMR-feature tracking from the German competence network for congenital heart defects

    Energy Technology Data Exchange (ETDEWEB)

    Shang, Quanliang [University of Nebraska College of Medicine, Children' s Hospital and Medical Center, Division of Pediatric Cardiology, Omaha, NE (United States); Central South University, Department of Radiology, Second Xiangya Hospital, Changsha, Hunan Province (China); Patel, Shivani; Danford, David A.; Kutty, Shelby [University of Nebraska College of Medicine, Children' s Hospital and Medical Center, Division of Pediatric Cardiology, Omaha, NE (United States); Steinmetz, Michael [Georg-August-University and German Centre for Cardiovascular Research (DZHK, Partner Site), Department of Paediatric Cardiology, Goettingen (Germany); Schuster, Andreas [Georg-August-University and German Centre for Cardiovascular Research (DZHK, Partner Site), Department of Cardiology and Pulmonology, Goettingen (Germany); Beerbaum, Philipp; Sarikouch, Samir [Hanover Medical School, Hanover (Germany)

    2018-03-15

    Left ventricular two-dimensional global longitudinal strain (LS) is superior to ejection fraction (EF) as predictor of outcome. We provide reference data for atrial and ventricular global LS during childhood and adolescence by CMR feature tracking (FT). We prospectively enrolled 115 healthy subjects (56 male, mean age 12.4 ± 4.1 years) at a single institution. CMR consisted of standard two-dimensional steady-state free-precession acquisitions. CMR-FT was performed on ventricular horizontal long-axis images for derivation of right and left atrial (RA, LA) and right and left ventricular (RV, LV) peak global LS. End-diastolic volumes (EDVs) and EF were measured. Correlations were explored for LS with age, EDV and EF of each chamber. Mean±SD of LS (%) for RA, RV, LA and LV were 26.56±10.2, -17.96±5.4, 26.45±10.6 and -17.47±5, respectively. There was a positive correlation of LS in LA, LV, RA and RV with corresponding EF (all P<0.05); correlations with age were weak. Gender-wise differences were not significant for atrial and ventricular LS, strain rate and displacement. Inter- and intra-observer comparisons showed moderate agreements. Chamber-specific nomograms for paediatric atrial and ventricular LS are provided to serve as clinical reference, and to facilitate CMR-based deformation research. (orig.)

  2. 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.

  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. Thermal tracking of sports players.

    Science.gov (United States)

    Gade, Rikke; Moeslund, Thomas B

    2014-07-29

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

  5. 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

  6. 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, ...

  7. 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.

  8. Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

    Science.gov (United States)

    Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

    2016-04-01

    Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

  9. Urbanism on Track : Application of tracking technologies in urbanism

    NARCIS (Netherlands)

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

    2008-01-01

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

  10. Left and right ventricular dyssynchrony and strains from cardiovascular magnetic resonance feature tracking do not predict deterioration of ventricular function in patients with repaired tetralogy of Fallot.

    Science.gov (United States)

    Jing, Linyuan; Wehner, Gregory J; Suever, Jonathan D; Charnigo, Richard J; Alhadad, Sudad; Stearns, Evan; Mojsejenko, Dimitri; Haggerty, Christopher M; Hickey, Kelsey; Valente, Anne Marie; Geva, Tal; Powell, Andrew J; Fornwalt, Brandon K

    2016-08-22

    Patients with repaired tetralogy of Fallot (rTOF) suffer from progressive ventricular dysfunction decades after their surgical repair. We hypothesized that measures of ventricular strain and dyssynchrony would predict deterioration of ventricular function in patients with rTOF. A database search identified all patients at a single institution with rTOF who underwent cardiovascular magnetic resonance (CMR) at least twice, >6 months apart, without intervening surgical or catheter procedures. Seven primary predictors were derived from the first CMR using a custom feature tracking algorithm: left (LV), right (RV) and inter-ventricular dyssynchrony, LV and RV peak global circumferential strains, and LV and RV peak global longitudinal strains. Three outcomes were defined, whose changes were assessed over time: RV end-diastolic volume, and RV and LV ejection fraction. Multivariate linear mixed models were fit to investigate relationships of outcomes to predictors and ten potential baseline confounders. One hundred fifty-three patients with rTOF (23 ± 14 years, 50 % male) were included. The mean follow-up duration between the first and last CMR was 2.9 ± 1.3 years. After adjustment for confounders, none of the 7 primary predictors were significantly associated with change over time in the 3 outcome variables. Only 1-17 % of the variability in the change over time in the outcome variables was explained by the baseline predictors and potential confounders. In patients with repaired tetralogy of Fallot, ventricular dyssynchrony and global strain derived from cine CMR were not significantly related to changes in ventricular size and function over time. The ability to predict deterioration in ventricular function in patients with rTOF using current methods is limited.

  11. 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-...

  12. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  13. Tracks: Nurses and the Tracking Network

    Centers for Disease Control (CDC) Podcasts

    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.

  14. 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.

  15. 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.

  16. Immersive video

    Science.gov (United States)

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

    1996-03-01

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

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. Parkinson's Disease Videos

    Medline Plus

    Full Text Available ... Is Initiated After Diagnosis? CareMAP: When Is It Time to Get Help? Unconditional Love CareMAP: Rest and Sleep: ... CareMAP: Mealtime and Swallowing: Part 1 ... of books, fact sheets, videos, podcasts, and more. To get started, use the search feature or check ...

  2. 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.

  3. 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.

  4. 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.

  5. Robust video object cosegmentation.

    Science.gov (United States)

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

    2015-10-01

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

  6. 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...

  7. 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…

  8. 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

  9. 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 ...

  10. 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

  11. 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...

  12. Video games.

    Science.gov (United States)

    Funk, Jeanne B

    2005-06-01

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

  13. 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.

  14. Tracks: EPHT Massachusetts Case Study

    Centers for Disease Control (CDC) Podcasts

    This podcast highlights the Massachusetts Environmental Public Health Tracking Network and features commentary from Massachusetts Department of Public Health Associate Health Commissioner Suzanne Condon.

  15. An algorithm to track laboratory zebrafish shoals.

    Science.gov (United States)

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

    2018-05-01

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

  16. 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.

  17. 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.

  18. Is a Picture Worth a Thousand Words? Few Evidence-Based Features of Dietary Interventions Included in Photo Diet Tracking Mobile Apps for Weight Loss.

    Science.gov (United States)

    Hales, Sarah; Dunn, Caroline; Wilcox, Sara; Turner-McGrievy, Gabrielle M

    2016-11-01

    Apps using digital photos to track dietary intake and provide feedback are common, but currently there has been no research examining what evidence-based strategies are included in these apps. A content analysis of mobile apps for photo diet tracking was conducted, including whether effective techniques for interventions promoting behavior change, including self-regulation, for healthy eating (HE) are targeted. An initial search of app stores yielded 34 apps (n = 8 Android and Apple; n = 11 Android; n = 15 Apple). One app was removed (unable to download), and other apps (n = 4) were unable to be rated (no longer available). Remaining apps (n = 29) were downloaded, reviewed, and coded by 2 independent reviewers to determine the number of known effective self-regulation and other behavior change techniques included. The raters met to compare their coding of the apps, calculate interrater agreement, resolve any discrepancies, and come to a consensus. Six apps (21%) did not utilize any of the behavior change techniques examined. Three apps (10%) provided feedback to users via crowdsourcing or collective feedback from other users and professionals, 7 apps (24%) used crowdsourcing or collective feedback, 1 app (3%) used professionals, and 18 apps (62%) did not provide any dietary feedback to users. Few photo diet-tracking apps include evidence-based strategies to improve dietary intake. Use of photos to self-monitor dietary intake and receive feedback has the potential to reduce user burden for self-monitoring, yet photo diet tracking apps need to incorporate known effective behavior strategies for HE, including self-regulation. © 2016 Diabetes Technology Society.

  19. 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…

  20. 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…

  1. 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.

  2. Ranking Highlights in Personal Videos by Analyzing Edited Videos.

    Science.gov (United States)

    Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

    2016-11-01

    We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

  3. Developing and Integrating Advanced Movement Features Improves Automated Classification of Ciliate Species.

    Science.gov (United States)

    Soleymani, Ali; Pennekamp, Frank; Petchey, Owen L; Weibel, Robert

    2015-01-01

    Recent advances in tracking technologies such as GPS or video tracking systems describe the movement paths of individuals in unprecedented details and are increasingly used in different fields, including ecology. However, extracting information from raw movement data requires advanced analysis techniques, for instance to infer behaviors expressed during a certain period of the recorded trajectory, or gender or species identity in case data is obtained from remote tracking. In this paper, we address how different movement features affect the ability to automatically classify the species identity, using a dataset of unicellular microbes (i.e., ciliates). Previously, morphological attributes and simple movement metrics, such as speed, were used for classifying ciliate species. Here, we demonstrate that adding advanced movement features, in particular such based on discrete wavelet transform, to morphological features can improve classification. These results may have practical applications in automated monitoring of waste water facilities as well as environmental monitoring of aquatic systems.

  4. 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.

  5. Robust online tracking via adaptive samples selection with saliency detection

    Science.gov (United States)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

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

  6. 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.

  7. Precise object tracking under deformation

    International Nuclear Information System (INIS)

    Saad, M.H

    2010-01-01

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

  8. Mining Specific and General Features in Both Positive and Negative Relevance Feedback. QUT E-Discovery Lab at the TREC󈧍 Relevance Feedback Track

    Science.gov (United States)

    2009-11-01

    relevance feedback algo- rithm. Four methods, εMap [1], MapA , P10A, and StatAP [2], were used in the track to measure the performance of Phase 2 runs...εMap and StatAP were applied to the runs us- ing the testing set of only ClueWeb09 Category-B, whereas MapA and P10A were applied to those using the...whole ClueWeb09 English set. Because our experiments were based on only ClueWeb09 Category-B, measuring our per- formance by MapA and P10A might not

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

    OpenAIRE

    Collins, Emily; Freeman, Jonathan

    2014-01-01

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

  10. Video Golf

    Science.gov (United States)

    1995-01-01

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

  11. Precise Object Tracking under Deformation

    International Nuclear Information System (INIS)

    Saad, M.H.

    2010-01-01

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

  12. OAS :: Videos

    Science.gov (United States)

    subscriptions Videos Photos Live Webcast Social Media Facebook @oasofficial Facebook Twitter @oas_official Audios Photos Social Media Facebook Twitter Newsletters Press and Communications Department Contact us at Rights Actions against Corruption C Children Civil Registry Civil Society Contact Us Culture Cyber

  13. 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.

  14. VideoStory Embeddings Recognize Events when Examples are Scarce

    OpenAIRE

    Habibian, Amirhossein; Mensink, Thomas; Snoek, Cees G. M.

    2015-01-01

    This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call VideoStory, the correlati...

  15. Video2vec Embeddings Recognize Events when Examples are Scarce

    OpenAIRE

    Habibian, A.; Mensink, T.; Snoek, C.G.M.

    2017-01-01

    This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlatio...

  16. 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.

  17. Whose track is it anyway?

    DEFF Research Database (Denmark)

    Flora, Janne; Andersen, Astrid Oberborbeck

    2017-01-01

    tracked their hunting routes, registered animals caught and observed, and photographed and videoed important places, events, and other phenomena they found interesting and relevant to register. This essay describes the conception and implementation of Piniariarneq, and uses this experience as a lens...

  18. Neural network tracking and extension of positive tracking periods

    Science.gov (United States)

    Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

    2004-04-01

    Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

  19. 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.

  20. 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.

  1. Learning from Multiple Sources for Video Summarisation

    OpenAIRE

    Zhu, Xiatian; Loy, Chen Change; Gong, Shaogang

    2015-01-01

    Many visual surveillance tasks, e.g.video summarisation, is conventionally accomplished through analysing imagerybased features. Relying solely on visual cues for public surveillance video understanding is unreliable, since visual observations obtained from public space CCTV video data are often not sufficiently trustworthy and events of interest can be subtle. On the other hand, non-visual data sources such as weather reports and traffic sensory signals are readily accessible but are not exp...

  2. Registration of retinal sequences from new video-ophthalmoscopic camera.

    Science.gov (United States)

    Kolar, Radim; Tornow, Ralf P; Odstrcilik, Jan; Liberdova, Ivana

    2016-05-20

    Analysis of fast temporal changes on retinas has become an important part of diagnostic video-ophthalmology. It enables investigation of the hemodynamic processes in retinal tissue, e.g. blood-vessel diameter changes as a result of blood-pressure variation, spontaneous venous pulsation influenced by intracranial-intraocular pressure difference, blood-volume changes as a result of changes in light reflection from retinal tissue, and blood flow using laser speckle contrast imaging. For such applications, image registration of the recorded sequence must be performed. Here we use a new non-mydriatic video-ophthalmoscope for simple and fast acquisition of low SNR retinal sequences. We introduce a novel, two-step approach for fast image registration. The phase correlation in the first stage removes large eye movements. Lucas-Kanade tracking in the second stage removes small eye movements. We propose robust adaptive selection of the tracking points, which is the most important part of tracking-based approaches. We also describe a method for quantitative evaluation of the registration results, based on vascular tree intensity profiles. The achieved registration error evaluated on 23 sequences (5840 frames) is 0.78 ± 0.67 pixels inside the optic disc and 1.39 ± 0.63 pixels outside the optic disc. We compared the results with the commonly used approaches based on Lucas-Kanade tracking and scale-invariant feature transform, which achieved worse results. The proposed method can efficiently correct particular frames of retinal sequences for shift and rotation. The registration results for each frame (shift in X and Y direction and eye rotation) can also be used for eye-movement evaluation during single-spot fixation tasks.

  3. Fall detection in the elderly by head-tracking

    OpenAIRE

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

    2009-01-01

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

  4. Application results for an augmented video tracker

    Science.gov (United States)

    Pierce, Bill

    1991-08-01

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

  5. 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.

  6. Homography-based multiple-camera person-tracking

    Science.gov (United States)

    Turk, Matthew R.

    2009-01-01

    Multiple video cameras are cheaply installed overlooking an area of interest. While computerized single-camera tracking is well-developed, multiple-camera tracking is a relatively new problem. The main multi-camera problem is to give the same tracking label to all projections of a real-world target. This is called the consistent labelling problem. Khan and Shah (2003) introduced a method to use field of view lines to perform multiple-camera tracking. The method creates inter-camera meta-target associations when objects enter at the scene edges. They also said that a plane-induced homography could be used for tracking, but this method was not well described. Their homography-based system would not work if targets use only one side of a camera to enter the scene. This paper overcomes this limitation and fully describes a practical homography-based tracker. A new method to find the feet feature is introduced. The method works especially well if the camera is tilted, when using the bottom centre of the target's bounding-box would produce inaccurate results. The new method is more accurate than the bounding-box method even when the camera is not tilted. Next, a method is presented that uses a series of corresponding point pairs "dropped" by oblivious, live human targets to find a plane-induced homography. The point pairs are created by tracking the feet locations of moving targets that were associated using the field of view line method. Finally, a homography-based multiple-camera tracking algorithm is introduced. Rules governing when to create the homography are specified. The algorithm ensures that homography-based tracking only starts after a non-degenerate homography is found. The method works when not all four field of view lines are discoverable; only one line needs to be found to use the algorithm. To initialize the system, the operator must specify pairs of overlapping cameras. Aside from that, the algorithm is fully automatic and uses the natural movement of

  7. 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.

  8. Blind prediction of natural video quality.

    Science.gov (United States)

    Saad, Michele A; Bovik, Alan C; Charrier, Christophe

    2014-03-01

    We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.

  9. 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.

  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. 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

  12. Visual hashing of digital video : applications and techniques

    NARCIS (Netherlands)

    Oostveen, J.; Kalker, A.A.C.M.; Haitsma, J.A.; Tescher, A.G.

    2001-01-01

    his paper present the concept of robust video hashing as a tool for video identification. We present considerations and a technique for (i) extracting essential perceptual features from a moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently

  13. Action recognition in depth video from RGB perspective: A knowledge transfer manner

    Science.gov (United States)

    Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

    2018-03-01

    Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

  14. Understanding learning within a commercial video game: A case study

    OpenAIRE

    Fowler, Allan

    2015-01-01

    There has been an increasing interest in the debate on the value and relevance using video games for learning. Some of the interest stems from frustration with current educational methods. However, some of this interest also stems from the observations of large numbers of children that play video games. This paper finds that children can learn basic construction skills from playing a video game called World of Goo. The study also employed novel eye-tracking technology to measure endogenous ey...

  15. 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...

  16. 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…

  17. 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.

  18. Airborne Video Surveillance

    National Research Council Canada - National Science Library

    Blask, Steven

    2002-01-01

    The DARPA Airborne Video Surveillance (AVS) program was established to develop and promote technologies to make airborne video more useful, providing capabilities that achieve a UAV force multiplier...

  19. 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

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

    OpenAIRE

    King, DL; Delfabbro, PH; Griffiths, MD

    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 ...

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

    DEFF Research Database (Denmark)

    2014-01-01

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

  2. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... YouTube Videos » NEI YouTube Videos: Amblyopia Listen 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: ...

  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. A video authentication technique

    International Nuclear Information System (INIS)

    Johnson, C.S.

    1987-01-01

    Unattended video surveillance systems are particularly vulnerable to the substitution of false video images into the cable that connects the camera to the video recorder. New technology has made it practical to insert a solid state video memory into the video cable, freeze a video image from the camera, and hold this image as long as desired. Various techniques, such as line supervision and sync detection, have been used to detect video cable tampering. The video authentication technique described in this paper uses the actual video image from the camera as the basis for detecting any image substitution made during the transmission of the video image to the recorder. The technique, designed for unattended video systems, can be used for any video transmission system where a two-way digital data link can be established. The technique uses similar microprocessor circuitry at the video camera and at the video recorder to select sample points in the video image for comparison. The gray scale value of these points is compared at the recorder controller and if the values agree within limits, the image is authenticated. If a significantly different image was substituted, the comparison would fail at a number of points and the video image would not be authenticated. The video authentication system can run as a stand-alone system or at the request of another system

  5. Particle tracking

    International Nuclear Information System (INIS)

    Mais, H.; Ripken, G.; Wrulich, A.; Schmidt, F.

    1986-02-01

    After a brief description of typical applications of particle tracking in storage rings and after a short discussion of some limitations and problems related with tracking we summarize some concepts and methods developed in the qualitative theory of dynamical systems. We show how these concepts can be applied to the proton ring HERA. (orig.)

  6. 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...

  7. Cardiac Magnetic Resonance Feature Tracking Biventricular Two-Dimensional and Three-Dimensional Strains to Evaluate Ventricular Function in Children After Repaired Tetralogy of Fallot as Compared with Healthy Children.

    Science.gov (United States)

    Berganza, Fernando M; de Alba, Cesar Gonzalez; Özcelik, Nazire; Adebo, Dilachew

    2017-03-01

    Cardiac magnetic resonance imaging is an important tool to evaluate cardiac anatomy and ventricular size and function after repaired tetralogy of Fallot. Magnetic resonance tissue tagging is the gold standard for evaluation of myocardial strain. However, myocardial tagging strain requires tagged images to be obtained prospectively, during the scan and with limited temporal resolution. Cardiac magnetic resonance feature tracking is a new tool that allows the retrospective analysis of cine images. There is limited experience with cardiac magnetic resonance feature tracking strain analysis in children. The medical records of patients with repaired tetralogy of Fallot that had a cardiac magnetic resonance (CMR) study from December 2013 to June 2015 were reviewed. The control group included patients who underwent a CMR with normal cardiac anatomy and ventricular function. Global longitudinal, circumferential and radial strain parameters (2D and 3D) were obtained by retrospectively contouring cine images from ventricular short axis, two chamber and four chamber views using post-processing software (Circle CVi 42 , Calgary, Canada). The correlation between conventional ventricular function parameters and ventricular strain was performed using Pearson's correlation. The mean age of tetralogy of Fallot and control subjects was 12.4 and 14.1 years, respectively. In patients after repaired tetralogy of Fallot, the mean left ventricular global 2D and 3D circumferential strains were -17.4 ± 2.9 and -10.1 ± 3, respectively. The mean indexed right ventricular end-diastolic volume was 135.4 cc m 2  ± 46 compared to 75.7 cc m 2  ± 17 in control subjects (P = 0.0001, CI 95%). Left ventricular global circumferential 3D strain showed a statistically significant difference in patients after TOF repair compared to normal subjects (-10.1 ± 3 vs. -14.71 ± 1.9, P = 0.00001). A strong correlation between left ventricular global circumferential 3D strain and right

  8. No-reference pixel based video quality assessment for HEVC decoded video

    DEFF Research Database (Denmark)

    Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

    2017-01-01

    the quantization step used in the Intra coding is estimated. We map the obtained HEVC features using an Elastic Net to predict subjective video quality scores, Mean Opinion Scores (MOS). The performance is verified on a dataset consisting of HEVC coded 4 K UHD (resolution equal to 3840 x 2160) video sequences...

  9. 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.

  10. Video Surveillance of Epilepsy Patients using Color Image Processing

    DEFF Research Database (Denmark)

    Bager, Gitte; Vilic, Kenan; Alving, Jørgen

    2007-01-01

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

  11. 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...

  12. Video Retrieval Berdasarkan Teks dan Gambar

    Directory of Open Access Journals (Sweden)

    Rahmi Hidayati

    2013-01-01

    Abstract Retrieval video has been used to search a video based on the query entered by user which were text and image. This system could increase the searching ability on video browsing and expected to reduce the video’s retrieval time. The research purposes were designing and creating a software application of retrieval video based on the text and image on the video. The index process for the text is tokenizing, filtering (stopword, stemming. The results of stemming to saved in the text index table. Index process for the image is to create an image color histogram and compute the mean and standard deviation at each primary color red, green and blue (RGB of each image. The results of feature extraction is stored in the image table The process of video retrieval using the query text, images or both. To text query system to process the text query by looking at the text index tables. If there is a text query on the index table system will display information of the video according to the text query. To image query system to process the image query by finding the value of the feature extraction means red, green means, means blue, red standard deviation, standard deviation and standard deviation of blue green. If the value of the six features extracted query image on the index table image will display the video information system according to the query image. To query text and query images, the system will display the video information if the query text and query images have a relationship that is query text and query image has the same film title.   Keywords—  video, index, retrieval, text, image

  13. 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.

  14. 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.

  15. Recommendations for recognizing video events by concept vocabularies

    Science.gov (United States)

    2014-06-01

    represents a video in terms of low-level audiovisual features [16,38,50,35,15,19,37]. In general, these methods first extract from the video various types of...interpretable, but is also reported to outperform the state-of-the-art low-level audiovisual features in recognizing events [31,33]. Rather than training...concept detector accuracy. As a consequence, the vocabulary concepts do not necessarily have a semantic interpreta- tion needed to explain the video content

  16. Rare Disease Video Portal

    OpenAIRE

    Sánchez Bocanegra, Carlos Luis

    2011-01-01

    Rare Disease Video Portal (RD Video) is a portal web where contains videos from Youtube including all details from 12 channels of Youtube. Rare Disease Video Portal (RD Video) es un portal web que contiene los vídeos de Youtube incluyendo todos los detalles de 12 canales de Youtube. Rare Disease Video Portal (RD Video) és un portal web que conté els vídeos de Youtube i que inclou tots els detalls de 12 Canals de Youtube.

  17. 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

  18. Making tracks

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1986-10-15

    In many modern tracking chambers, the sense wires, rather than being lined up uniformly, are grouped into clusters to facilitate the pattern recognition process. However, with higher energy machines providing collisions richer in secondary particles, event reconstruction becomes more complicated. A Caltech / Illinois / SLAC / Washington group developed an ingenious track finding and fitting approach for the Mark III detector used at the SPEAR electron-positron ring at SLAC (Stanford). This capitalizes on the detector's triggering, which uses programmable logic circuits operating in parallel, each 'knowing' the cell patterns for all tracks passing through a specific portion of the tracker (drift chamber)

  19. Video conferencing made easy

    Science.gov (United States)

    Larsen, D. Gail; Schwieder, Paul R.

    1993-02-01

    Network video conferencing is advancing rapidly throughout the nation, and the Idaho National Engineering Laboratory (INEL), a Department of Energy (DOE) facility, is at the forefront of the development. Engineers at INEL/EG&G designed and installed a very unique DOE videoconferencing system, offering many outstanding features, that include true multipoint conferencing, user-friendly design and operation with no full-time operators required, and the potential for cost effective expansion of the system. One area where INEL/EG&G engineers made a significant contribution to video conferencing was in the development of effective, user-friendly, end station driven scheduling software. A PC at each user site is used to schedule conferences via a windows package. This software interface provides information to the users concerning conference availability, scheduling, initiation, and termination. The menus are 'mouse' controlled. Once a conference is scheduled, a workstation at the hubs monitors the network to initiate all scheduled conferences. No active operator participation is required once a user schedules a conference through the local PC; the workstation automatically initiates and terminates the conference as scheduled. As each conference is scheduled, hard copy notification is also printed at each participating site. Video conferencing is the wave of the future. The use of these user-friendly systems will save millions in lost productivity and travel cost throughout the nation. The ease of operation and conference scheduling will play a key role on the extent industry uses this new technology. The INEL/EG&G has developed a prototype scheduling system for both commercial and federal government use.

  20. Video conferencing made easy

    Science.gov (United States)

    Larsen, D. Gail; Schwieder, Paul R.

    1993-01-01

    Network video conferencing is advancing rapidly throughout the nation, and the Idaho National Engineering Laboratory (INEL), a Department of Energy (DOE) facility, is at the forefront of the development. Engineers at INEL/EG&G designed and installed a very unique DOE videoconferencing system, offering many outstanding features, that include true multipoint conferencing, user-friendly design and operation with no full-time operators required, and the potential for cost effective expansion of the system. One area where INEL/EG&G engineers made a significant contribution to video conferencing was in the development of effective, user-friendly, end station driven scheduling software. A PC at each user site is used to schedule conferences via a windows package. This software interface provides information to the users concerning conference availability, scheduling, initiation, and termination. The menus are 'mouse' controlled. Once a conference is scheduled, a workstation at the hubs monitors the network to initiate all scheduled conferences. No active operator participation is required once a user schedules a conference through the local PC; the workstation automatically initiates and terminates the conference as scheduled. As each conference is scheduled, hard copy notification is also printed at each participating site. Video conferencing is the wave of the future. The use of these user-friendly systems will save millions in lost productivity and travel cost throughout the nation. The ease of operation and conference scheduling will play a key role on the extent industry uses this new technology. The INEL/EG&G has developed a prototype scheduling system for both commercial and federal government use.

  1. PVR system design of advanced video navigation reinforced with audible sound

    NARCIS (Netherlands)

    Eerenberg, O.; Aarts, R.; De With, P.N.

    2014-01-01

    This paper presents an advanced video navigation concept for Personal Video Recording (PVR), based on jointly using the primary image and a Picture-in-Picture (PiP) image, featuring combined rendering of normal-play video fragments with audio and fast-search video. The hindering loss of audio during

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

    African Journals Online (AJOL)

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

  3. 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.

  4. Snapshot spectral and polarimetric imaging; target identification with multispectral video

    Science.gov (United States)

    Bartlett, Brent D.; Rodriguez, Mikel D.

    2013-05-01

    As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

  5. Methods and Algorithms for Detecting Objects in Video Files

    Directory of Open Access Journals (Sweden)

    Nguyen The Cuong

    2018-01-01

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

  6. Semantic-based surveillance video retrieval.

    Science.gov (United States)

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

    2007-04-01

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

  7. Why tracks

    International Nuclear Information System (INIS)

    Burchart, J.; Kral, J.

    1979-01-01

    A comparison is made of two methods of determining the age of rocks, ie., the krypton-argon method and the fission tracks method. The former method is more accurate but is dependent on the temperature and on the grain size of the investigated rocks (apatites, biotites, muscovites). As for the method of fission tracks, the determination is not dependent on grain size. This method allows dating and the determination of uranium concentration and distribution in rocks. (H.S.)

  8. Video Spectroscopy with the RSpec Explorer

    Science.gov (United States)

    Lincoln, James

    2018-01-01

    The January 2018 issue of "The Physics Teacher" saw two articles that featured the RSpec Explorer as a supplementary lab apparatus. The RSpec Explorer provides live video spectrum analysis with which teachers can demonstrate how to investigate features of a diffracted light source. In this article I provide an introduction to the device…

  9. 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.

  10. Video motion detection for physical security applications

    International Nuclear Information System (INIS)

    Matter, J.C.

    1990-01-01

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

  11. Temporal Segmentation of MPEG Video Streams

    Directory of Open Access Journals (Sweden)

    Janko Calic

    2002-06-01

    Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

  12. REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

    Directory of Open Access Journals (Sweden)

    M. S. Temiz

    2012-07-01

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

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

    Science.gov (United States)

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

    2012-12-01

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

  14. Hardware accelerator design for tracking in smart camera

    Science.gov (United States)

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

    2011-10-01

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

  15. Moving Shadow Detection in Video Using Cepstrum

    Directory of Open Access Journals (Sweden)

    Fuat Cogun

    2013-01-01

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

  16. 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.

  17. No-Reference Video Quality Assessment using MPEG Analysis

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

    2013-01-01

    We present a method for No-Reference (NR) Video Quality Assessment (VQA) for decoded video without access to the bitstream. This is achieved by extracting and pooling features from a NR image quality assessment method used frame by frame. We also present methods to identify the video coding...... and estimate the video coding parameters for MPEG-2 and H.264/AVC which can be used to improve the VQA. The analysis differs from most other video coding analysis methods since it is without access to the bitstream. The results show that our proposed method is competitive with other recent NR VQA methods...

  18. Effects of Low- Versus High-Fidelity Simulations on the Cognitive Burden and Performance of Entry-Level Paramedicine Students: A Mixed-Methods Comparison Trial Using Eye-Tracking, Continuous Heart Rate, Difficulty Rating Scales, Video Observation and Interviews.

    Science.gov (United States)

    Mills, Brennen W; Carter, Owen B-J; Rudd, Cobie J; Claxton, Louise A; Ross, Nathan P; Strobel, Natalie A

    2016-02-01

    High-fidelity simulation-based training is often avoided for early-stage students because of the assumption that while practicing newly learned skills, they are ill suited to processing multiple demands, which can lead to "cognitive overload" and poorer learning outcomes. We tested this assumption using a mixed-methods experimental design manipulating psychological immersion. Thirty-nine randomly assigned first-year paramedicine students completed low- or high-environmental fidelity simulations [low-environmental fidelity simulations (LF(en)S) vs. high-environmental fidelity simulation (HF(en)S)] involving a manikin with obstructed airway (SimMan3G). Psychological immersion and cognitive burden were determined via continuous heart rate, eye tracking, self-report questionnaire (National Aeronautics and Space Administration Task Load Index), independent observation, and postsimulation interviews. Performance was assessed by successful location of obstruction and time-to-termination. Eye tracking confirmed that students attended to multiple, concurrent stimuli in HF(en)S and interviews consistently suggested that they experienced greater psychological immersion and cognitive burden than their LF(en)S counterparts. This was confirmed by significantly higher mean heart rate (P cognitive burden but this has considerable educational merit.

  19. Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery

    Directory of Open Access Journals (Sweden)

    Yalong Ma

    2016-03-01

    Full Text Available Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs, more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG and Discrete Cosine Transform (DCT features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness.

  20. Robust Visual Tracking Using the Bidirectional Scale Estimation

    Directory of Open Access Journals (Sweden)

    An Zhiyong

    2017-01-01

    Full Text Available Object tracking with robust scale estimation is a challenging task in computer vision. This paper presents a novel tracking algorithm that learns the translation and scale filters with a complementary scheme. The translation filter is constructed using the ridge regression and multidimensional features. A robust scale filter is constructed by the bidirectional scale estimation, including the forward scale and backward scale. Firstly, we learn the scale filter using the forward tracking information. Then the forward scale and backward scale can be estimated using the respective scale filter. Secondly, a conservative strategy is adopted to compromise the forward and backward scales. Finally, the scale filter is updated based on the final scale estimation. It is effective to update scale filter since the stable scale estimation can improve the performance of scale filter. To reveal the effectiveness of our tracker, experiments are performed on 32 sequences with significant scale variation and on the benchmark dataset with 50 challenging videos. Our results show that the proposed tracker outperforms several state-of-the-art trackers in terms of robustness and accuracy.

  1. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer ... me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ANetwork ...

  2. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos ...

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

    National Research Council Canada - National Science Library

    Brashear , Jr, Thomas J

    2005-01-01

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

  4. 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...... in which 25 educators as part of a digital fabrication and design program were able to critically reflect on their teaching practice....

  5. Video2vec Embeddings Recognize Events When Examples Are Scarce.

    Science.gov (United States)

    Habibian, Amirhossein; Mensink, Thomas; Snoek, Cees G M

    2017-10-01

    This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlations between the words are utilized to learn a more effective representation by optimizing a joint objective balancing descriptiveness and predictability. We show how learning the Video2vec embedding using a multimodal predictability loss, including appearance, motion and audio features, results in a better predictable representation. We also propose an event specific variant of Video2vec to learn a more accurate representation for the words, which are indicative of the event, by introducing a term sensitive descriptiveness loss. Our experiments on three challenging collections of web videos from the NIST TRECVID Multimedia Event Detection and Columbia Consumer Videos datasets demonstrate: i) the advantages of Video2vec over representations using attributes or alternative embeddings, ii) the benefit of fusing video modalities by an embedding over common strategies, iii) the complementarity of term sensitive descriptiveness and multimodal predictability for event recognition. By its ability to improve predictability of present day audio-visual video features, while at the same time maximizing their semantic descriptiveness, Video2vec leads to state-of-the-art accuracy for both few- and zero-example recognition of events in video.

  6. 77 FR 64342 - Announcement of Requirements and Registration for Caregivers Video Challenge

    Science.gov (United States)

    2012-10-19

    ... marketing a commercial business, brand name, product or other trademark mentioned or featured in the Video.... By entering the challenge, contestants agree to make the original digital file of their Video...

  7. A Coincidental Sound Track for "Time Flies"

    Science.gov (United States)

    Cardany, Audrey Berger

    2014-01-01

    Sound tracks serve a valuable purpose in film and video by helping tell a story, create a mood, and signal coming events. Holst's "Mars" from "The Planets" yields a coincidental soundtrack to Eric Rohmann's Caldecott-winning book, "Time Flies." This pairing provides opportunities for upper elementary and…

  8. The Children's Video Marketplace.

    Science.gov (United States)

    Ducey, Richard V.

    This report examines a growing submarket, the children's video marketplace, which comprises broadcast, cable, and video programming for children 2 to 11 years old. A description of the tremendous growth in the availability and distribution of children's programming is presented, the economics of the children's video marketplace are briefly…

  9. Video Self-Modeling

    Science.gov (United States)

    Buggey, Tom; Ogle, Lindsey

    2012-01-01

    Video self-modeling (VSM) first appeared on the psychology and education stage in the early 1970s. The practical applications of VSM were limited by lack of access to tools for editing video, which is necessary for almost all self-modeling videos. Thus, VSM remained in the research domain until the advent of camcorders and VCR/DVD players and,…

  10. Online Tracking

    Science.gov (United States)

    ... can disable blocking on those sites. Tagged with: computer security , cookies , Do Not Track , personal information , privacy June ... email Looking for business guidance on privacy and ... The Federal Trade Commission (FTC) is the nation’s consumer protection agency. The FTC works to prevent fraudulent, deceptive ...

  11. Robust efficient video fingerprinting

    Science.gov (United States)

    Puri, Manika; Lubin, Jeffrey

    2009-02-01

    We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

  12. Development of Automated Tracking System with Active Cameras for Figure Skating

    Science.gov (United States)

    Haraguchi, Tomohiko; Taki, Tsuyoshi; Hasegawa, Junichi

    This paper presents a system based on the control of PTZ cameras for automated real-time tracking of individual figure skaters moving on an ice rink. In the video images of figure skating, irregular trajectories, various postures, rapid movements, and various costume colors are included. Therefore, it is difficult to determine some features useful for image tracking. On the other hand, an ice rink has a limited area and uniform high intensity, and skating is always performed on ice. In the proposed system, an ice rink region is first extracted from a video image by the region growing method, and then, a skater region is extracted using the rink shape information. In the camera control process, each camera is automatically panned and/or tilted so that the skater region is as close to the center of the image as possible; further, the camera is zoomed to maintain the skater image at an appropriate scale. The results of experiments performed for 10 training scenes show that the skater extraction rate is approximately 98%. Thus, it was concluded that tracking with camera control was successful for almost all the cases considered in the study.

  13. Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

    Science.gov (United States)

    Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

    2008-02-01

    Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

  14. Multi person detection and tracking based on hierarchical level-set method

    Science.gov (United States)

    Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

    2018-04-01

    In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

  15. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  16. A Benchmark and Simulator for UAV Tracking

    KAUST Repository

    Mueller, Matthias; Smith, Neil; Ghanem, Bernard

    2016-01-01

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

  17. A Benchmark and Simulator for UAV Tracking

    KAUST Repository

    Mueller, Matthias

    2016-09-16

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

  18. VBR video traffic models

    CERN Document Server

    Tanwir, Savera

    2014-01-01

    There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.

  19. Flip Video for Dummies

    CERN Document Server

    Hutsko, Joe

    2010-01-01

    The full-color guide to shooting great video with the Flip Video camera. The inexpensive Flip Video camera is currently one of the hottest must-have gadgets. It's portable and connects easily to any computer to transfer video you shoot onto your PC or Mac. Although the Flip Video camera comes with a quick-start guide, it lacks a how-to manual, and this full-color book fills that void! Packed with full-color screen shots throughout, Flip Video For Dummies shows you how to shoot the best possible footage in a variety of situations. You'll learn how to transfer video to your computer and then edi

  20. Moving Target Detection and Active Tracking with a Multicamera Network

    Directory of Open Access Journals (Sweden)

    Long Zhao

    2014-01-01

    Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.

  1. Video Texture Synthesis Based on Flow-Like Stylization Painting

    Directory of Open Access Journals (Sweden)

    Qian Wenhua

    2014-01-01

    Full Text Available The paper presents an NP-video rendering system based on natural phenomena. It provides a simple nonphotorealistic video synthesis system in which user can obtain a flow-like stylization painting and infinite video scene. Firstly, based on anisotropic Kuwahara filtering in conjunction with line integral convolution, the phenomena video scene can be rendered to flow-like stylization painting. Secondly, the methods of frame division, patches synthesis, will be used to synthesize infinite playing video. According to selection examples from different natural video texture, our system can generate stylized of flow-like and infinite video scenes. The visual discontinuities between neighbor frames are decreased, and we also preserve feature and details of frames. This rendering system is easy and simple to implement.

  2. Compressed normalized block difference for object tracking

    Science.gov (United States)

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

    2018-04-01

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

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

    OpenAIRE

    Safadi, Firas

    2015-01-01

    The work presented in this dissertation revolves around the problem of designing artificial intelligence (AI) for video games. This problem becomes increasingly challenging as video games grow in complexity. With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of these environments is pressing. Although machine learning techniques are being successfully applied in a multitude of d...

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

    KAUST Repository

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

    2018-01-01

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

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

    KAUST Repository

    Müller, Matthias

    2018-03-28

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

  6. Video redaction: a survey and comparison of enabling technologies

    Science.gov (United States)

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

    2017-09-01

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

  7. Video game characteristics, happiness and flow as predictors of addiction among video game players: a pilot study

    OpenAIRE

    Hull, DC; Williams, GA; Griffiths, MD

    2013-01-01

    Aims:\\ud Video games provide opportunities for positive psychological experiences such as flow-like phenomena during play and general happiness that could be associated with gaming achievements. However, research has shown that specific features of game play may be associated with problematic behaviour associated with addiction-like experiences. The study was aimed at analysing whether certain structural characteristics of video games, flow, and global happiness could be predictive of video g...

  8. Hybrid markerless tracking of complex articulated motion in golf swings.

    Science.gov (United States)

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

    2014-04-01

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

  9. Dynamic quantitative analysis of adherent cell cultures by means of lens-free video microscopy

    Science.gov (United States)

    Allier, C.; Vincent, R.; Navarro, F.; Menneteau, M.; Ghenim, L.; Gidrol, X.; Bordy, T.; Hervé, L.; Cioni, O.; Bardin, S.; Bornens, M.; Usson, Y.; Morales, S.

    2018-02-01

    We present our implementation of lens-free video microscopy setup for the monitoring of adherent cell cultures. We use a multi-wavelength LED illumination together with a dedicated holographic reconstruction algorithm that allows for an efficient removal of twin images from the reconstructed phase image for densities up to those of confluent cell cultures (>500 cells/mm2). We thereby demonstrate that lens-free video microscopy, with a large field of view ( 30 mm2) can enable us to capture the images of thousands of cells simultaneously and directly inside the incubator. It is then possible to trace and quantify single cells along several cell cycles. We thus prove that lens-free microscopy is a quantitative phase imaging technique enabling estimation of several metrics at the single cell level as a function of time, for example the area, dry mass, maximum thickness, major axis length and aspect ratio of each cell. Combined with cell tracking, it is then possible to extract important parameters such as the initial cell dry mass (just after cell division), the final cell dry mass (just before cell division), the average cell growth rate, and the cell cycle duration. As an example, we discuss the monitoring of a HeLa cell cultures which provided us with a data-set featuring more than 10 000 cell cycle tracks and more than 2x106 cell morphological measurements in a single time-lapse.

  10. Using Interactive Video Instruction To Enhance Public Speaking Instruction.

    Science.gov (United States)

    Cronin, Michael W.; Kennan, William R.

    Noting that interactive video instruction (IVI) should not and cannot replace classroom instruction, this paper offers an introduction to interactive video instruction as an innovative technology that can be used to expand pedagogical opportunities in public speaking instruction. The paper: (1) defines the distinctive features of IVI; (2) assesses…

  11. Mediating Tourist Experiences. Access to Places via Shared Videos

    DEFF Research Database (Denmark)

    Tussyadiah, Iis; Fesenmaier, D.R.

    2009-01-01

    The emergence of new media using multimedia features has generated a new set of mediators for tourists' experiences. This study examines two hypotheses regarding the roles that online travel videos play as mediators of tourist experiences. The results confirm that online shared videos can provide...

  12. Video-Aided GPS/INS Positioning and Attitude Determination

    National Research Council Canada - National Science Library

    Brown, Alison; Silva, Randy

    2006-01-01

    ... precise positioning and attitude information to be maintained, even during periods of extended GPS dropouts. This relies on information extracted from the video images of reference points and features to continue to update the inertial navigation solution. In this paper, the principles of the video-update method aredescribed.

  13. Hierarchical online appearance-based tracking for 3D head pose, eyebrows, lips, eyelids, and irises

    NARCIS (Netherlands)

    Orozco, Javier; Rudovic, Ognjen; Gonzalez Garcia, Jordi; Pantic, Maja

    In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can

  14. 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...... to automatically extract the cyclic motion pattern, in walking and running represented as steps, and analyse the frequency. Experiments are performed with one subject in two different tests, each at 5, 8, 10, and 12 km/h. The results of our proposed video-based method is compared to concurrent measurements...

  15. The live service of video geo-information

    Science.gov (United States)

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

    2016-03-01

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

  16. MPEG-2 Compressed-Domain Algorithms for Video Analysis

    Directory of Open Access Journals (Sweden)

    Hesseler Wolfgang

    2006-01-01

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

  17. An Overview of Structural Characteristics in Problematic Video Game Playing.

    Science.gov (United States)

    Griffiths, Mark D; Nuyens, Filip

    2017-01-01

    There are many different factors involved in how and why people develop problems with video game playing. One such set of factors concerns the structural characteristics of video games (i.e., the structure, elements, and components of the video games themselves). Much of the research examining the structural characteristics of video games was initially based on research and theorizing from the gambling studies field. The present review briefly overviews the key papers in the field to date. The paper examines a number of areas including (i) similarities in structural characteristics of gambling and video gaming, (ii) structural characteristics in video games, (iii) narrative and flow in video games, (iv) structural characteristic taxonomies for video games, and (v) video game structural characteristics and game design ethics. Many of the studies carried out to date are small-scale, and comprise self-selected convenience samples (typically using self-report surveys or non-ecologically valid laboratory experiments). Based on the small amount of empirical data, it appears that structural features that take a long time to achieve in-game are the ones most associated with problematic video game play (e.g., earning experience points, managing in-game resources, mastering the video game, getting 100% in-game). The study of video games from a structural characteristic perspective is of benefit to many different stakeholders including academic researchers, video game players, and video game designers, as well as those interested in prevention and policymaking by making the games more socially responsible. It is important that researchers understand and recognize the psycho-social effects and impacts that the structural characteristics of video games can have on players, both positive and negative.

  18. Identifying hidden voice and video streams

    Science.gov (United States)

    Fan, Jieyan; Wu, Dapeng; Nucci, Antonio; Keralapura, Ram; Gao, Lixin

    2009-04-01

    Given the rising popularity of voice and video services over the Internet, accurately identifying voice and video traffic that traverse their networks has become a critical task for Internet service providers (ISPs). As the number of proprietary applications that deliver voice and video services to end users increases over time, the search for the one methodology that can accurately detect such services while being application independent still remains open. This problem becomes even more complicated when voice and video service providers like Skype, Microsoft, and Google bundle their voice and video services with other services like file transfer and chat. For example, a bundled Skype session can contain both voice stream and file transfer stream in the same layer-3/layer-4 flow. In this context, traditional techniques to identify voice and video streams do not work. In this paper, we propose a novel self-learning classifier, called VVS-I , that detects the presence of voice and video streams in flows with minimum manual intervention. Our classifier works in two phases: training phase and detection phase. In the training phase, VVS-I first extracts the relevant features, and subsequently constructs a fingerprint of a flow using the power spectral density (PSD) analysis. In the detection phase, it compares the fingerprint of a flow to the existing fingerprints learned during the training phase, and subsequently classifies the flow. Our classifier is not only capable of detecting voice and video streams that are hidden in different flows, but is also capable of detecting different applications (like Skype, MSN, etc.) that generate these voice/video streams. We show that our classifier can achieve close to 100% detection rate while keeping the false positive rate to less that 1%.

  19. Photogrammetric Applications of Immersive Video Cameras

    Science.gov (United States)

    Kwiatek, K.; Tokarczyk, R.

    2014-05-01

    The paper investigates immersive videography and its application in close-range photogrammetry. Immersive video involves the capture of a live-action scene that presents a 360° field of view. It is recorded simultaneously by multiple cameras or microlenses, where the principal point of each camera is offset from the rotating axis of the device. This issue causes problems when stitching together individual frames of video separated from particular cameras, however there are ways to overcome it and applying immersive cameras in photogrammetry provides a new potential. The paper presents two applications of immersive video in photogrammetry. At first, the creation of a low-cost mobile mapping system based on Ladybug®3 and GPS device is discussed. The amount of panoramas is much too high for photogrammetric purposes as the base line between spherical panoramas is around 1 metre. More than 92 000 panoramas were recorded in one Polish region of Czarny Dunajec and the measurements from panoramas enable the user to measure the area of outdoors (adverting structures) and billboards. A new law is being created in order to limit the number of illegal advertising structures in the Polish landscape and immersive video recorded in a short period of time is a candidate for economical and flexible measurements off-site. The second approach is a generation of 3d video-based reconstructions of heritage sites based on immersive video (structure from immersive video). A mobile camera mounted on a tripod dolly was used to record the interior scene and immersive video, separated into thousands of still panoramas, was converted from video into 3d objects using Agisoft Photoscan Professional. The findings from these experiments demonstrated that immersive photogrammetry seems to be a flexible and prompt method of 3d modelling and provides promising features for mobile mapping systems.

  20. Video Toroid Cavity Imager

    Energy Technology Data Exchange (ETDEWEB)

    Gerald, Rex E. II; Sanchez, Jairo; Rathke, Jerome W.

    2004-08-10

    A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.