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A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes
Shiquan Wang; Kaiqi Huang; Tieniu Tan
2009
会议名称International Conference on Image Processing
会议录名称IEEE International Conference on Image Processing, 2009
页码1121-1124
会议日期2009
会议地点Cairo, Egypt
摘要We address the problem of action recognition. Our aim is to recognize single person activities in surveillance scenes. To meet the requirements of real scene action recognition, we present a compact motion representation for human activity recognition. With the employment of efficient features extracted from optical flow as the main part, together with global information, our motion representation is compact and discriminative. We also build a novel human action dataset(CASIA) in surveillance scene with three vertically different viewpoints and distant people. Experiments on CASIA dataset and WEIZMANN dataset show that our method can achieve satisfying recognition performance with low computational cost as well as robustness against both horizontal(panning) and vertical(tilting) viewpoint changes.
关键词Feature Extraction   image Motion Analysis   surveillance 
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12704
专题智能感知与计算研究中心
通讯作者Kaiqi Huang
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Shiquan Wang,Kaiqi Huang,Tieniu Tan. A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes[C],2009:1121-1124.
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