Laplacian Maximum Margin Criterion for Image Recognition

DOI: 10.4236/jcc.2015.311010   PDF   HTML   XML   2,405 Downloads   2,752 Views  

Abstract

Previous works have demonstrated that Laplacian embedding can well preserve the local intrinsic structure. However, it ignores the diversity and may impair the local topology of data. In this paper, we build an objective function to learn the local intrinsic structure that characterizes both the local similarity and diversity of data, and then combine it with global structure to build a scatter difference criterion. Experimental results in face recognition show the effectiveness of our proposed approach.

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Chen, F. , Wang, J. and Gao, Q. (2015) Laplacian Maximum Margin Criterion for Image Recognition. Journal of Computer and Communications, 3, 58-63. doi: 10.4236/jcc.2015.311010.

Conflicts of Interest

The authors declare no conflicts of interest.

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