detection and recognition of abnormal running behavior in surveillance video

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ID: 226816
2012
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Abstract
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.
Reference Key
zhu2012mathematicaldetection Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Ying-Ying Zhu;Yan-Yan Zhu;Wen Zhen-Kun;Wen-Sheng Chen;Qiang Huang
Journal journal of power sources
Year 2012
DOI
10.1155/2012/296407
URL
http://dx.doi.org/10.1155/2012/296407
Keywords
civil engineering (general)mathematics engineering (general)

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