Generalized Model-Based Human Motion Recognition with Body Partition Index Maps
Computer Graphics Forum
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In this paper, a novel concept of segmental singular value decomposition (SegSVD) is proposed to represent a motion pattern with a hierarchical structure. The similarity measure based on the SegSVD representation is also proposed. SegSVD is capable of capturing the temporal information of the time series. It is effective in matching patterns in a time series in which the start and end points of the patterns are not known in advance. We evaluate the performance of our method on both isolated motion classification and continuous motion recognition for dance movements. Experiments show that our method outperforms existing work in terms of higher recognition accuracy.