Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes

@article{Yang2017NuclearNB,
  title={Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes},
  author={Jian Yang and Jianjun Qian and Lei Luo and Fanlong Zhang and Yicheng Gao},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2017},
  volume={39},
  pages={156-171}
}
Recently, regression analysis has become a popular tool for face recognition. Most existing regression methods use the one-dimensional, pixel-based error model, which characterizes the representation error individually, pixel by pixel, and thus neglects the two-dimensional structure of the error image. We observe that occlusion and illumination changes generally lead, approximately, to a low-rank error image. In order to make use of this low-rank structural information, this paper presents a… CONTINUE READING
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