Patch Based Face Recognition via Fast Collaborative Representation Based Classification and Expression Insensitive Two-Stage Voting

Author(s):  
Decheng Yang ◽  
Weiting Chen ◽  
Jiangtao Wang ◽  
Yan Xu
2013 ◽  
Vol 756-759 ◽  
pp. 3590-3595
Author(s):  
Liang Zhang ◽  
Ji Wen Dong

Aiming at solving the problems of occlusion and illumination in face recognition, a new method of face recognition based on Kernel Principal Components Analysis (KPCA) and Collaborative Representation Classifier (CRC) is developed. The KPCA can obtain effective discriminative information and reduce the feature dimensions by extracting faces nonlinear structures features, the decisive factor. Considering the collaboration among the samples, the CRC which synthetically consider the relationship among samples is used. Experimental results demonstrate that the algorithm obtains good recognition rates and also improves the efficiency. The KCRC algorithm can effectively solve the problem of illumination and occlusion in face recognition.


Author(s):  
Xiao Dong ◽  
Huaxiang Zhang ◽  
Jiande Sun ◽  
Wenbo Wan

2018 ◽  
Vol 75 (5) ◽  
pp. 2304-2314
Author(s):  
Xincan Fan ◽  
Kaiyang Liu ◽  
Haibo Yi

2016 ◽  
Vol 45 (3) ◽  
pp. 967-979 ◽  
Author(s):  
Taisong Jin ◽  
Zhiling Liu ◽  
Zhengtao Yu ◽  
Xiaoping Min ◽  
Lingling Li

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