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

Yang LI  Junyong YE  Tongqing WANG  Shijian HUANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.9   pp.1711-1714
Publication Date: 2015/09/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Pattern Recognition
Keyword: 
sparse coding,  temporal changes,  spatial pyramid,  human action recognition,  

Full Text: PDF(346.5KB)
>>Buy this Article


Summary: 
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.