Computer Science ›› 2016, Vol. 43 ›› Issue (9): 305-309.doi: 10.11896/j.issn.1002-137X.2016.09.061

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Method of Low Resolution Facial Fatigue Expression Recognition Based on Sparse Representation

ZHANG Ling, TIAN Xiao-lu, LUO Yuan, CHANG Jie and WU Yong   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In order to effectively improve the performance of facial fatigue expression recognition on the low resolution image,a method of fatigue facial expression recognition based on sparse representation was proposed.Firstly,the reliability analysis method of Kendall coefficient of concordance is used to construct the low-resolution facial fatigue expression database TIREDFACE.Secondly,the sparse representation of the low resolution facial fatigue expression images of the identified test samples in the database is sought,and then the compressed sensing theory is used to seek their sparsest solution.Finally,according to the sparsest solution,the low-resolution facial fatigue expression classification is performed.Experimental results on TIREDFACE database show that the low resolution facial fatigue expression perfor-mance obtained by this method is much better than the linear classifier,the nearest neighbor (NN),support vector machine (SVM) and the nearest subspace (NS).Therefore,the proposed method on the low resolution facial fatigue expression recognition tasks achieves better performance and high accuracy.

Key words: Sparse representation,Compressed sensing,Fatigue expression,Sparse representation-based classification(SRC),Kendall coefficient of concordance

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