期刊
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
卷 36, 期 3, 页码 710-719出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2005.861864
关键词
human-action recognition; relevance vector machines (RVMs); salient regions; spatiotemporal actions; spatiotemporal saliency
This paper addresses the problem of human-action recognition by introducing a,sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time. The spatiotemporal salient points are detected by measuring the variations in the information content of pixel neighborhoods not only in space but also in time. An appropriate distance metric between two collections of spatiotemporal salient points is introduced, which is based on the chamfer distance and an iterative linear time-warping technique that deals with time expansion or time-compression issues. A classification scheme that is based on relevance vector machines and on the proposed distance measure is proposed. Results on real image sequences from a small database depicting people performing 19 aerobic exercises are presented.
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