View-invariant Action Recognition in Surveillance Videos | |
Fang Zhang; Yunhong Wang; Zhaoxiang Zhang![]() | |
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
![]() |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/13277] ![]() |
专题 | 自动化研究所_类脑智能研究中心 |
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. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论