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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Sparse Representation with Regularization Term for Face Recognition
verfasst von : Jian Ji, Huafeng Ji, Mengqi Bai
Erschienen in: Computer Vision
Verlag: Springer Berlin Heidelberg
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In recent years there has been a growing interest in the study of sparse representation based classification (SRC) which has obtained great success in face recognition. However, SRC is overly dependent on the size of training samples while overlooking the correlation information that is critical to the real-world face recognition problems. Besides, some method considers the correlation information but overlooks the discriminating ability of sparsity. In this paper, we propose a new method called trace norm sparse representation based classification (TSRC) which introduces a regularization term in the SRC model from both ℓ
1
-norm and ℓ
2
-norm, which is flexible and can obtain satisfactory results. Experimental results on 2 face databases clearly show that the proposed TSRC method outperforms many state-of-the-art face recognition methods.