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Proceedings Paper

Violence detection based on histogram of optical flow orientation
Author(s): Zhijie Yang; Tao Zhang; Jie Yang; Qiang Wu; Li Bai; Lixiu Yao
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Paper Abstract

In this paper, we propose a novel approach for violence detection and localization in a public scene. Currently, violence detection is considerably under-researched compared with the common action recognition. Although existing methods can detect the presence of violence in a video, they cannot precisely locate the regions in the scene where violence is happening. This paper will tackle the challenge and propose a novel method to locate the violence location in the scene, which is important for public surveillance. The Gaussian Mixed Model is extended into the optical flow domain in order to detect candidate violence regions. In each region, a new descriptor, Histogram of Optical Flow Orientation (HOFO), is proposed to measure the spatial-temporal features. A linear SVM is trained based on the descriptor. The performance of the method is demonstrated on the publicly available data sets, BEHAVE and CAVIAR.

Paper Details

Date Published: 24 December 2013
PDF: 4 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 906718 (24 December 2013); doi: 10.1117/12.2051390
Show Author Affiliations
Zhijie Yang, Shanghai Jiao Tong Univ. (China)
Tao Zhang, Shanghai Jiao Tong Univ. (China)
Jie Yang, Shanghai Jiao Tong Univ. (China)
Qiang Wu, Univ. of Technology, Sydney (Australia)
Li Bai, Univ. of Nottingham (United Kingdom)
Lixiu Yao, Shanghai Jiao Tong Univ. (China)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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