›› 2012, Vol. ›› Issue (06): 1521-1526.

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Face image feature extraction method based on sparse tensor

ZHOU Chun-guang, SUN Ming-fang, WANG Su-jing, CHEN Qian, LIU Xiao-hua, LIU Yu-hao   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2011-12-21 Online:2012-11-01

Abstract: A Spare Tensor Principal Component Analysis (STPCA) for feature extraction based on Multi-linear Principal Component Analysis (MPCA) was proposed. This STPCA can obtain spare projection matrix by transforming the eigen-decomposition problem into linear regression problem. With the help of the spare projection matrix the effect of occlusion can be reduced in the process of feature extraction. Experiments on Georgia tech and AR face database show that the proposed method outperforms the MPCA method in terms of accuracy and the robustness to occlusion.

Key words: computer application, feature extraction, sparse representation, tensor subspace, face recognition

CLC Number: 

  • TP391.4
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