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Multi-view Gymnastic Activity Recognition with Fused HMM
Ying Wang; Kaiqi Huang; Tieniu Tan
2007
Conference Namethe 8th Asian Conference on Computer Vision
Source Publicationthe 8th Asian Conference on Computer Vision
Pages667-677
Conference Date2007
Conference PlaceTokyo, Japan
AbstractMore and more researchers focus their studies on multi-view activity recognition, because a fixed view could not provide enough information for recognition. In this paper, we use multi-view features to recognize six kinds of gymnastic activities. Firstly, shape-based features are extracted from two orthogonal cameras in the form of 脗\Re transform. Then a multi-view approach based on Fused HMM is proposed to combine different features for similar gymnastic activity recognition. Compared with other activity models, our method achieves better performance even in the case of frame loss.
KeywordMulti-view Gymnastic Activity Recognition
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12716
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
Ying Wang,Kaiqi Huang,Tieniu Tan. Multi-view Gymnastic Activity Recognition with Fused HMM[C],2007:667-677.
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