CASIA OpenIR  > 智能感知与计算研究中心
A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes
Shiquan Wang; Kaiqi Huang; Tieniu Tan
2009
Conference NameInternational Conference on Image Processing
Source PublicationIEEE International Conference on Image Processing, 2009
Pages1121-1124
Conference Date2009
Conference PlaceCairo, Egypt
AbstractWe 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.
KeywordFeature Extraction   image Motion Analysis   surveillance 
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12704
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
Recommended Citation
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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