基于协作表示的增强型分类

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI:10.1109/ICINFA.2014.6932697

Zhonghua Liu, Xuhui Zhao, Tao Huang, J. Pu, Yanna Si

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引用次数: 4

摘要

近年来，稀疏表示受到了广泛的关注。提出了基于稀疏表示的分类算法，并成功应用于人脸识别。然而，稀疏性的重要性在SRC中被过分强调，而协同表示(CR)的使用在SRC中被忽视了。在现实中，是协作表示而不是11范数稀疏性使SRC在人脸识别中变得强大。在基于协作表示的分类方法(CRC)的基础上，提出了一种增强的基于协作表示的分类方法(ECRC)。在人脸数据库上的实验结果证明了该方法的有效性。

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Enhanced collaborative representation based Classification

Sparse representation has attracted great attention in past years. Sparse Representation-based Classification (SRC) algorithm was developed and successfully used in face recognition. However, the importance of sparsity is much emphasized in SRC and the use of collaborative representation (CR) in SRC is ignored. In reality, it is the collaborative representation but not the l1-norm sparsity that makes SRC powerful for face recogntion. Based on collaborative representation based classification (CRC) method, we proposed an enhanced collaborative representation based classification (ECRC). Experimental results on face databases demonstrate the effectiveness of our method.

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2014 IEEE International Conference on Information and Automation (ICIA)

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