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Robust Matrix Regression for Illumination and Occlusion Tolerant Face Recognition
2015
2015 IEEE International Conference on Computer Vision Workshop (ICCVW)
Face recognition (FR) via regression analysis based classification has been widely applied in the past several years. In the existing regression methods, the testing image is represented as a linear combination of the training samples and the error image is converted into vector which is characterized by l 1 -norm or l 2 -norm. Therefore the twodimensional structure of the error image is neglected in practice. In this paper, we operate on the two-dimensional image matrix directly, and propose a
doi:10.1109/iccvw.2015.118
dblp:conf/iccvw/XieYQT15
fatcat:m7ib3qf3avb57fzagvbhjts3ay