Robust of Low Rank Matrix and Collaborative Representation for Face Recognition
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Abstract
In this paper, we have introduced improvement Robustness method for face
recognition, which combine of the low-rank with collaborative representation. The
applications of this model are based on the truth that proposed method can effectively deal
with the face recognition across different illumination and occlusion, as well as the nature of
corrupted and occluded regions. The method is able to be applied directly on original face
image neither does it require feature selection, nor does it need many training samples.
Experiments have been performed on various benchmark face database. The proposed method
outperforms many state-of-the-art methods.
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