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An Approach to Detect Crowd Panic Behavior using Flow-based Feature

Hao, Yu, Xu, Zhijie, Wang, Jing, Liu, Ying and Fan, Jiulun (2016) An Approach to Detect Crowd Panic Behavior using Flow-based Feature. In: The 22nd International Conference on Automation and Computing, 7th - 8th September 2016, University of Essex. (In Press)

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Abstract

With the purpose of achieving automated detection of crowd abnormal behavior in public, this paper discusses the category of typical crowd and individual behaviors and their patterns. Popular image features for abnormal behavior detection are also introduced, including global flow based features such as optical flow, and local spatio-temporal based features such as Spatio-temporal Volume (STV). After reviewing some relative abnormal behavior detection algorithms, a brandnew approach to detect crowd panic behavior has been proposed based on optical flow features in this paper. During the experiments, all panic behaviors are successfully detected. In the end, the future work to improve current approach has been discussed.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
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Depositing User: Jing Wang
Date Deposited: 28 Jul 2016 13:24
Last Modified: 29 Jul 2016 06:38
URI: http://eprints.hud.ac.uk/id/eprint/29079

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