|View-invariant Action Recognition in Surveillance Videos|
|Fang Zhang; Yunhong Wang; Zhaoxiang Zhang
|Conference Name||1st Asian Conference on Pattern Recognition
|Source Publication||ACPR 2011
|Conference Date||28th November 2011
|Conference Place||Beijing, China
|Abstract||Recently, human action recognition has been a popular and important topic in computer vision. However, except some conventional problems such as noise, low resolution etc., view-invariant recognition is one of the most challenging problems. In this paper, we focus on solve multi-view action recognition from surveillance video. To detect moving objects from complicated backgrounds, this paper employs improved Gaussian mixed model, which uses K-means clustering to initialize the model and it gets better motion detection results for surveillance videos. We demonstrate the silhouette representation “Envelope Shape” can solve the viewpoint problem in surveillance videos. The experiment results demonstrate that our human action recognition system is fast and efficient on CASIA activity analysis database.|
Hidden Markov Models
|Corresponding Author||Zhaoxiang Zhang|
Fang Zhang,Yunhong Wang,Zhaoxiang Zhang. View-invariant Action Recognition in Surveillance Videos[C],2011.
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