Drastic Anomaly Detection in Video Using Motion Direction Statistics

Author:

LIU Chang1,WANG Guijin1,NING Wenxin1,LIN Xinggang1

Affiliation:

1. Department of Electronic Engineering, Tsinghua University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference19 articles.

1. [1] T. Ding, M. Sznaier, and O.I. Camps, “Fast track matching and event detection,” CVPR, pp.1-8, June 2008.

2. [2] F. Jiang, Y. Wu, and A.K. Katsaggelos, “Abnormal event detection based on trajectory clustering by 2-depth greedy search,” Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, pp.2129-2132, March-April 2008.

3. [3] F. Cupillard, A. Avanzi, F. Bremond, and M. Thonnat, “Video understanding for metro surveillance,” Proc. IEEE International Conference on Networking, Sensing and Control, pp.186-191, March 2004.

4. [4] H. Zhong, J. Shi, and M. Visontai, “Detecting unusual activity in video,” CVPR, vol.2, pp.819-826, 2004.

5. [5] Y. Ke, R. Sukthankar, and M. Hebert, “Efficient visual event detection using volumetric features,” IEEE Computer Society, ICCV, pp.166-173, Washington, DC, USA, 2005.

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