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An Effective Video Processing Pipeline for Crowd Pattern Analysis

Hao, Yu, Xu, Zhijie, Wang, Jing, Liu, Ying and Fan, Jiulun (2017) An Effective Video Processing Pipeline for Crowd Pattern Analysis. Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). ISSN 9780701702601

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Abstract

With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion “textures” from dynamic Spatio-Temporal Volume (STV) blocks formulated by live video streams has been proposed. This paper starts from introducing the common approach for STV construction and corresponding Spatio-Temporal Texture (STT) extraction techniques. Next the crowd motion information contained within the random STT slices are evaluated based on the information entropy theory to cull the static background and noises occupying most of the STV spaces. A preprocessing step using Gabor filtering for improving the STT sampling efficiency and motion fidelity has been devised and tested. The technique has been applied on benchmarking video databases for proof-of-concept and performance evaluation. Preliminary results have shown encouraging outcomes and promising potentials for its real-world crowd monitoring and control applications.

Item Type: Article
Contributors:
ContributionNameEmailORCID
UNSPECIFIEDHao, Yuy.hao@hud.ac.ukUNSPECIFIED
UNSPECIFIEDXu, Zhijiez.xu@hud.ac.uk0000-0002-0524-5926
UNSPECIFIEDWang, Jingj.wang2@hud.ac.ukUNSPECIFIED
UNSPECIFIEDLiu, Yinly_yolanda@sina.comUNSPECIFIED
UNSPECIFIEDFan, Jiulunjiulunf@xupt.edu.cnUNSPECIFIED
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Crowd pattern analysis; Spatio-Temporal Volume; Spatio-Temporal Texture; Gabor filtering; Information entropy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Schools: School of Computing and Engineering > High-Performance Intelligent Computing > Visualisation, Interaction and Vision
Related URLs:
Depositing User: Zhijie Xu
Date Deposited: 10 Oct 2017 08:33
Last Modified: 02 Nov 2017 13:49
URI: http://eprints.hud.ac.uk/id/eprint/33565

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