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Anomaly detection in video surveillance

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Anomaly detection in video surveillanceby Xiaochun Wang.
作者:	Wang, Xiaochun.
出版者:	Singapore :Springer Nature Singapore :2024.
面頁冊數:	xix, 384 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Anomaly detection (Computer security)
電子資源:	https://doi.org/10.1007/978-981-97-3023-0
ISBN:	9789819730230$q(electronic bk.)

Anomaly detection in video surveillance
Wang, Xiaochun.

Anomaly detection in video surveillance[electronic resource] /by Xiaochun Wang. - Singapore :Springer Nature Singapore :2024. - xix, 384 p. :ill. (some col.), digital ;24 cm. - Cognitive intelligence and robotics,2520-1964. - Cognitive intelligence and robotics..

Chapter 1 Introduction -- Chapter 2 Mathematical Preliminaries for Video Anomaly Detection Techniques -- Chapter 3 Probability Based Video Anomaly Detection Approaches -- Chapter 4 k-Nearest Neighbor Based Video Anomaly Detection Approaches -- Chapter 5 Gaussian Mixture Model Based Video Anomaly Detection.

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.

ISBN: 9789819730230$q(electronic bk.)

Standard No.: 10.1007/978-981-97-3023-0doiSubjects--Topical Terms:

797123
Anomaly detection (Computer security)

LC Class. No.: TA1634 / .W36 2024

Dewey Class. No.: 006.37

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