Face recognition using discriminant sparsity neighborhood preserving embedding

Authors:
Gui-Fu Lu;Zhong Jin;Jian Zou
Affiliations:
School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China and School of Computer Science and Information, AnHui Polytechnic University ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China and School of Computer Science and Information, AnHui Polytechnic University ...
Venue:
Knowledge-Based Systems
Year:
2012

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Abstract

In this paper, we propose an effective supervised dimensionality reduction technique, namely discriminant sparsity neighborhood preserving embedding (DSNPE), for face recognition. DSNPE constructs graph and corresponding edge weights simultaneously through sparse representation (SR). DSNPE explicitly takes into account the within-neighboring information and between-neighboring information. Further, by taking the advantage of the maximum margin criterion (MMC), the discriminating power of DSNPE is further boosted. Experiments on the ORL, Yale, AR and FERET face databases show the effectiveness of the proposed DSNPE.