Statistics on Temporal Changes of Sparse Coding Coefficients in Spatial Pyramids for Human Action Recognition

DOI Web Site 参考文献7件
  • LI Yang
    Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University
  • YE Junyong
    Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University
  • WANG Tongqing
    Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University
  • HUANG Shijian
    Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University

抄録

Traditional sparse representation-based methods for human action recognition usually pool over the entire video to form the final feature representation, neglecting any spatio-temporal information of features. To employ spatio-temporal information, we present a novel histogram representation obtained by statistics on temporal changes of sparse coding coefficients frame by frame in the spatial pyramids constructed from videos. The histograms are further fed into a support vector machine with a spatial pyramid matching kernel for final action classification. We validate our method on two benchmarks, KTH and UCF Sports, and experiment results show the effectiveness of our method in human action recognition.

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