Computer Science ›› 2017, Vol. 44 ›› Issue (7): 270-274.doi: 10.11896/j.issn.1002-137X.2017.07.048

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Human Action Recognition Based on Fisher Discrimination Dictionary Learning

JI Chong, WANG Sheng and LU Jian-feng   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Human action recognition is a hot computer vision research field,and has broad application prospects.This paper explored the application of Fisher discrimination based dictionary learning on human action recognition.First,local spatial-temporal features are extracted from the video sequences and random projection is used to reduce dimension.Then,Fisher discrimination based dictionary learning is performed on the reduced motion features.Last,a new classification scheme is proposed using both reconstruction error and representation coefficients.Experimental results confirm the efficiency and robustness of the proposed scheme.

Key words: Sparse representation,Human action recognition,Motion features,Fisher discrimination criterion

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