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Facial expression recognition based on characteristics of block LGBP and sparse representation
Ma, Duo; Li, Ming; Nian, Fu-Zhong; Kong, Cui-Cui
刊名Journal of Computational Methods in Sciences and Engineering
2015-08-03
卷号15期号:3页码:537-547
关键词Textures character block Facial expression recognition Over-complete dictionaries Residual vectors Sparse representation
ISSN号14727978
DOI10.3233/JCM-150566
英文摘要Aiming at the difficulty of distinguishing texture feature in facial expressions recognition, this paper put forward a LGBP facial expression recognition algorithm based on the character blocking and sparse representation. The main contents are training the block images of different categories expression images and extracting the LGBP features of each sub-block. We construct a over-complete dictionary from which we get the discrepancy vector of each sub-block using sparse representation. Through finding the minimum residual vectors to achieve the recognition of different facial expressions. To some extent, the experimental results based on the JAFFF and Cohn-kanade facial expression database show that this algorithm can effectively overcome the influence of texture feature differences and have higher recognition rate. © 2015 - IOS Press and the authors.
WOS研究方向Engineering
语种英语
出版者IOS Press, Nieuwe Hemweg 6B, Amsterdam, 1013 BG, Netherlands
WOS记录号WOS:000219247500023
内容类型期刊论文
源URL[http://ir.lut.edu.cn/handle/2XXMBERH/112840]  
专题计算机与通信学院
作者单位School of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu; 730050, China
推荐引用方式
GB/T 7714
Ma, Duo,Li, Ming,Nian, Fu-Zhong,et al. Facial expression recognition based on characteristics of block LGBP and sparse representation[J]. Journal of Computational Methods in Sciences and Engineering,2015,15(3):537-547.
APA Ma, Duo,Li, Ming,Nian, Fu-Zhong,&Kong, Cui-Cui.(2015).Facial expression recognition based on characteristics of block LGBP and sparse representation.Journal of Computational Methods in Sciences and Engineering,15(3),537-547.
MLA Ma, Duo,et al."Facial expression recognition based on characteristics of block LGBP and sparse representation".Journal of Computational Methods in Sciences and Engineering 15.3(2015):537-547.
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