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Proceedings Paper

Face recognition using multiple maximum scatter difference discrimination dictionary learning
Author(s): Yanyong Zhu; Jiwen Dong; Hengjian Li
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Paper Abstract

Based on multiple maximum scatter difference discrimination Dictionary learning, a novel face recognition algorithm is proposed. Dictionary used for sparse coding plays a key role in sparse representation classification. In this paper, a multiple maximum scatter difference discriminated criterion is used for dictionary learning. During the process of dictionary learning, the multiple maximum scatter difference computes its discriminated vectors from both the range of the between class scatter matrix and the null space of the within-class scatter matrix. The proposed algorithm is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the AR database and Extended Yale Database B in comparison with existing basic sparse representation and other classification methods, it shows that the performance is a little better than the original sparse representation methods with lower complexity.

Paper Details

Date Published: 8 October 2015
PDF: 7 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96750H (8 October 2015); doi: 10.1117/12.2197395
Show Author Affiliations
Yanyong Zhu, Univ. of Jinan (China)
Jiwen Dong, Univ. of Jinan (China)
Hengjian Li, Univ. of Jinan (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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