Download or read book Video Traffic Analysis for Abnormal Events Detection and Classification written by Arun Kumar H. D. and published by . This book was released on 2024-01-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Video Traffic Analysis for Abnormal Event Detection written by and published by . This book was released on 2010 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Video Tra c Analysis for Abnormal Events Detection and Classification written by Arun Kumar H. D. and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Abnormal Detection in Video Streams Via One class Learning Methods written by Tian Wang and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Download or read book Online Video Analysis for Abnormal Event Detection and Action Recognition written by Roberto Leyva and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Anomalous Event Detection from Surveillance Video written by Fan Jiang and published by LAP Lambert Academic Publishing. This book was released on 2011-02 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Online Video Analysis for Abnormal Event Detection and Action Recognition written by Marcial Roberto Leyva Fernandez and published by . This book was released on 2018 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intelligent Systems Design and Applications written by Ajith Abraham and published by Springer. This book was released on 2018-03-21 with total page 1076 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Video Based Machine Learning for Traffic Intersections written by Tania Banerjee and published by CRC Press. This book was released on 2023-10-17 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions. The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection. Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development. Key Features: Describes the development and challenges associated with Intelligent Transportation Systems (ITS) Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersection Has the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts
Download or read book Contextual Analysis of Videos written by Myo Thida and published by Springer Nature. This book was released on 2022-06-01 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Anomaly Detection in Video Surveillance written by Xiaochun Wang and published by Springer Nature. This book was released on with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multimedia Analysis Processing and Communications written by Lin Weisi and published by Springer Science & Business Media. This book was released on 2011-04-11 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has brought 24 groups of experts and active researchers around the world together in image processing and analysis, video processing and analysis, and communications related processing, to present their newest research results, exchange latest experiences and insights, and explore future directions in these important and rapidly evolving areas. It aims at increasing the synergy between academic and industry professionals working in the related field. It focuses on the state-of-the-art research in various essential areas related to emerging technologies, standards and applications on analysis, processing, computing, and communication of multimedia information. The target audience of this book is researchers and engineers as well as graduate students working in various disciplines linked to multimedia analysis, processing and communications, e.g., computer vision, pattern recognition, information technology, image processing, and artificial intelligence. The book is also meant to a broader audience including practicing professionals working in image/video applications such as image processing, video surveillance, multimedia indexing and retrieval, and so on. We hope that the researchers, engineers, students and other professionals who read this book would find it informative, useful and inspirational toward their own work in one way or another.
Download or read book Outlier Detection for Temporal Data written by Manish Gupta and published by Springer. This book was released on 2014-04-14 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neural networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers. Table of Contents: Preface / Acknowledgments / Figure Credits / Introduction and Challenges / Outlier Detection for Time Series and Data Sequences / Outlier Detection for Data Streams / Outlier Detection for Distributed Data Streams / Outlier Detection for Spatio-Temporal Data / Outlier Detection for Temporal Network Data / Applications of Outlier Detection for Temporal Data / Conclusions and Research Directions / Bibliography / Authors' Biographies
Download or read book Proceedings of the International Conference on Artificial Intelligence and Computer Vision AICV2020 written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-03-23 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.
Download or read book Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition SoCPaR 2020 written by Ajith Abraham and published by Springer Nature. This book was released on 2021-04-15 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the recent research on soft computing and pattern recognition and their various practical applications. It presents 62 selected papers from the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) and 35 papers from the 16th International Conference on Information Assurance and Security (IAS 2020), which was held online, from December 15 to 18, 2020. A premier conference in the field of artificial intelligence, SoCPaR-IAS 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Download or read book Leveraging Computer Vision to Biometric Applications written by Arvind Selwal and published by CRC Press. This book was released on 2024-10-07 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is an effective solution in a diverse range of real-life applications. With the advent of the machine and deep learning paradigms, this book adopts machine and deep learning algorithms to leverage digital image processing for designing accurate biometrical applications. In this aspect, it presents the advancements made in computer vision to biometric applications design approach using emerging technologies. It discusses the challenges of designing efficient and accurate biometric-based systems, which is a key issue that can be tackled via computer vision-based techniques. Key Features • Discusses real-life applications of emerging techniques in computer vision systems • Offers solutions on real-time computer vision and biometrics applications to cater to the needs of current industry • Presents case studies to offer ideas for developing new biometrics-based products • Offers problem-based solutions in the field computer vision and real-time biometric applications for secured human authentication • Works as a ready resource for professionals and scholars working on emerging topics of computer vision for biometrics. The book is for academic researchers, scholars and students in Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, management, academicians, researchers, scientists and industry people working on computer vision and biometrics applications.
Download or read book Anomaly Detection in Video Surveillance written by Xiaochun Wang and published by Springer. This book was released on 2024-07-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anomaly detection in video surveillance stands at the core of numerous real-world applications that have broad impact and generate significant academic and industrial value. The key advantage of writing the book at this point in time is that the vast amount of work done by computer scientists over the last few decades has remained largely untouched by a formal book on the subject, although these techniques significantly advance existing methods of image and video analysis and understanding by taking advantage of anomaly detection in the data mining community and visual analysis in the computer vision community. The proposed book provides a comprehensive coverage of the advances in video based anomaly detection, including topics such as the theories of anomaly detection and machine perception for the functional analysis of abnormal events in general, the identification of abnormal behaviour and crowd abnormal behaviour in particular, the current understanding of computer vision development, and the application of this present understanding towards improving video-based anomaly detection in theory and coding with OpenCV. The book also provides a perspective on deep learning on human action recognition and behaviour analysis, laying the groundwork for future advances in these areas. Overall, the chapters of this book have been carefully organized with extensive bibliographic notes attached to each chapter. One of the goals is to provide the first systematic and comprehensive description of the range of data-driven solutions currently being developed up to date for such purposes. Another is to serve a dual purpose so that students and practitioners can use it as a textbook while researchers can use it as a reference book. A final goal is to provide a comprehensive exposition of the topic of anomaly detection in video media from multiple points of view.
