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Author: Arun Kumar H. D.
Publisher:
ISBN: 9781835800812
Category :
Languages : en
Pages : 0
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Book Description
Author: Arun Kumar H. D.
Publisher:
ISBN: 9781835800812
Category :
Languages : en
Pages : 0
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Book Description
Author:
Publisher:
ISBN:
Category : Digital video
Languages : en
Pages : 78
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Book Description
Author: Xiaochun Wang
Publisher: Springer Nature
ISBN: 9819730236
Category :
Languages : en
Pages : 396
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Author: Arun Kumar H. D.
Publisher:
ISBN: 9781835800324
Category :
Languages : en
Pages : 0
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Author: Tian Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
One of the major research areas in computer vision is visual surveillance. The scientific challenge in this area includes the implementation of automatic systems for obtaining detailed information about the behavior of individuals and groups. Particularly, detection of abnormal individual movements requires sophisticated image analysis. This thesis focuses on the problem of the abnormal events detection, including feature descriptor design characterizing the movement information and one-class kernel-based classification methods. In this thesis, three different image features have been proposed: (i) global optical flow features, (ii) histograms of optical flow orientations (HOFO) descriptor and (iii) covariance matrix (COV) descriptor. Based on these proposed descriptors, one-class support vector machines (SVM) are proposed in order to detect abnormal events. Two online strategies of one-class SVM are proposed: The first strategy is based on support vector description (online SVDD) and the second strategy is based on online least squares one-class support vector machines (online LS-OC-SVM).
Author: Roberto Leyva
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Fan Jiang
Publisher: LAP Lambert Academic Publishing
ISBN: 9783844309645
Category :
Languages : en
Pages : 96
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Book Description
Content-based video analysis serves as the cornerstone for many applications: video understanding or summarization, multimedia information retrieval and data mining, etc. In our research, we aim to automatically detect anomalous events from surveillance videos (such as video monitoring traffic flow or pedestrian congestion in public spaces). Conceptually, what constitutes an anomaly varies in different video scenarios and is difficult to be defined in a general case. Our first solution is based on unsupervised clustering of object trajectories and anomalous trajectory identification in a probabilistic framework. Then we extend this solution to an arbitrary time length (any part of a complete trajectory) and multiple objects (multiple trajectories). Furthermore, we solve problems specifically in video scenarios where object trajectories cannot be extracted (e.g., crowd motion analysis). Our contributions include a novel hierarchical clustering algorithm and categorization of anomalous video events by spatiotemporal context.
Author: Marcial Roberto Leyva Fernandez
Publisher:
ISBN:
Category : Computer vision
Languages : en
Pages : 163
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Book Description
Author: Myo Thida
Publisher: Springer Nature
ISBN: 3031022491
Category : Technology & Engineering
Languages : en
Pages : 8
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Book Description
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. This book focusses on tracking individual targets and detecting abnormal behavior of a crowd in a complex scene. Firstly, this book surveys the state-of-the-art methods for tracking multiple targets in a complex scene and describes the authors' approach for tracking multiple targets. The proposed approach is to formulate the problem of multi-target tracking as an optimization problem of finding dynamic optima (pedestrians) where these optima interact frequently. A novel particle swarm optimization (PSO) algorithm that uses a set of multiple swarms is presented. Through particles and swarms diversification, motion prediction is introduced into the standard PSO, constraining swarm members to the most likely region in the search space. The social interaction among swarm and the output from pedestrians-detector are also incorporated into the velocity-updating equation. This allows the proposed approach to track multiple targets in a crowded scene with severe occlusion and heavy interactions among targets. The second part of this book discusses the problem of detecting and localising abnormal activities in crowded scenes. We present a spatio-temporal Laplacian Eigenmap method for extracting different crowd activities from videos. This method learns the spatial and temporal variations of local motions in an embedded space and employs representatives of different activities to construct the model which characterises the regular behavior of a crowd. This model of regular crowd behavior allows for the detection of abnormal crowd activities both in local and global context and the localization of regions which show abnormal behavior.
Author: Ajith Abraham
Publisher: Springer
ISBN: 3319763482
Category : Technology & Engineering
Languages : en
Pages : 1076
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Book Description
This book highlights recent research on intelligent systems design and applications. It presents 100 selected papers from the 17th International Conference on Intelligent Systems Design and Applications (ISDA 2017), which was held in Delhi, India from December 14 to 16, 2017. The ISDA is a premier conference in the field of Computational Intelligence and brings together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry and the real world. Including contributions by authors from over 30 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
