Contextual Analysis of Videos (Record no. 86053)

000 -LEADER
fixed length control field 04624nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-031-02249-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730165024.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2013 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031022494
-- 978-3-031-02249-4
082 04 - CLASSIFICATION NUMBER
Call Number 620
100 1# - AUTHOR NAME
Author Thida, Myo.
245 10 - TITLE STATEMENT
Title Contextual Analysis of Videos
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2013.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XCVI, 8 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Image, Video, and Multimedia Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Literature Review -- Tracking Multiple Targets Using Particle Swarm Optimization -- Abnormality Detection in Crowded Scenes -- Conclusion -- Bibliography -- Authors' Biographies.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Eng, How-lung.
700 1# - AUTHOR 2
Author 2 Monekosso, Dorothy.
700 1# - AUTHOR 2
Author 2 Remagnino, Paolo.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02249-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Technology and Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical and Electronic Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1559-8144
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-- ZDB-2-SXSC

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