東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Anomaly detection in video surveillance

Wang, Xiaochun.

Linked to FindBook

Google Book

Amazon

博客來

Anomaly detection in video surveillance

Record Type:	Electronic resources : Monograph/item
Title/Author:	Anomaly detection in video surveillance/ by Xiaochun Wang.
Author:	Wang, Xiaochun.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xix, 384 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Anomaly detection (Computer security) -
Online resource:	https://doi.org/10.1007/978-981-97-3023-0
ISBN:	9789819730230

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

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

3269771
Anomaly detection (Computer security)

LC Class. No.: TA1634 / .W36 2024

Dewey Class. No.: 006.37

Anomaly detection in video surveillance
LDR:03261nmm a22003495a 4500 001 2387906
003 DE-He213
005 20240806130237.0
006 m d
007 cr nn 008maaau
008 250916s2024 si s 0 eng d
020 $a 9789819730230 $q (electronic bk.)
020 $a 9789819730223 $q (paper)
024 7 $a 10.1007/978-981-97-3023-0 $2 doi
035 $a 978-981-97-3023-0
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1634 $b .W36 2024
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQV $2 thema
082 0 4 $a 006.37 $2 23
090 $a TA1634 $b .W246 2024
100 1 $a Wang, Xiaochun. $3 3443948
245 1 0 $a Anomaly detection in video surveillance $h [electronic resource] / $c by Xiaochun Wang.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xix, 384 p. : $b ill. (some col.), digital ; $c 24 cm.
347 $a text file $b PDF $2 rda
490 1 $a Cognitive intelligence and robotics, $x 2520-1964
505 0 $a 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.
520 $a 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.
650 0 $a Anomaly detection (Computer security) $3 3269771
650 0 $a Computer vision. $3 540671
650 0 $a Video surveillance. $3 1375317
650 1 4 $a Computer Vision. $3 3538524
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Automated Pattern Recognition. $3 3538549
650 2 4 $a Theory and Algorithms for Application Domains. $3 3594704
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Cognitive intelligence and robotics. $3 3338190
856 4 0 $u https://doi.org/10.1007/978-981-97-3023-0
950 $a Computer Science (SpringerNature-11645)