View-invariant Action Recognition in Surveillance Videos
文献类型：会议论文
| 作者 | Fang Zhang; Yunhong Wang; Zhaoxiang Zhang
|
| 出版日期 | 2011-11-28 |
| 会议日期 | 28th November 2011 |
| 会议地点 | Beijing, China |
| 关键词 | Videos Gaussian Distribution Surveillance Shape Humans Hidden Markov Models Databases |
| 英文摘要 | 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. |
| 会议录 | ACPR 2011
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13277]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Zhaoxiang Zhang |
| 推荐引用方式 GB/T 7714 | Fang Zhang,Yunhong Wang,Zhaoxiang Zhang. View-invariant Action Recognition in Surveillance Videos[C]. 见:. Beijing, China. 28th November 2011. |
入库方式： OAI收割
来源：自动化研究所
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