Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 296407, 14 pages
Research Article

Detection and Recognition of Abnormal Running Behavior in Surveillance Video

1College of Computer and Software, Shenzhen University, Shenzhen 518060, China
2College of Mathematics and Computational Science, Shenzhen University, Shenzhen 518060, China

Received 15 January 2012; Accepted 14 February 2012

Academic Editor: Ming Li

Copyright © 2012 Ying-Ying Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abnormal running behavior frequently happen in robbery cases and other criminal cases. In order to identity these abnormal behaviors a method to detect and recognize abnormal running behavior, is presented based on spatiotemporal parameters. Meanwhile, to obtain more accurate spatiotemporal parameters and improve the real-time performance of the algorithm, a multitarget tracking algorithm, based on the intersection area among the minimum enclosing rectangle of the moving objects, is presented. The algorithm can judge and exclude effectively the intersection of multitarget and the interference, which makes the tracking algorithm more accurate and of better robustness. Experimental results show that the combination of these two algorithms can detect and recognize effectively the abnormal running behavior in surveillance videos.