Search:
Computing and Library Services - delivering an inspiring information environment

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: Proceedings 22nd International Conference on Automation and Computing. IEEE. ISBN 9781862181328

[img]
Preview
PDF - Accepted Version
Download (846kB) | Preview

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: Book Chapter
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
Related URLs:
Depositing User: Jing Wang
Date Deposited: 28 Jul 2016 13:24
Last Modified: 19 Dec 2016 12:21
URI: http://eprints.hud.ac.uk/id/eprint/29079

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©