Face recognition based on feature selection strategy

被引：0

作者：

Tang, Hengliang ^{[1
,2
]}

Sun, Yanfeng ^{[1
]}

Zhu, Jie ^{[2
]}

Zhao, Mingru ^{[1
,2
]}

机构：

[1] Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Transportation Engineering, Beijing University of Technology, Beijing

[2] Beijing Key Laboratory of Intelligent Logistics System, School of Information, Beijing Wuzi University, Beijing

来源：

Journal of Information and Computational Science | 2014年 / 11卷 / 12期

关键词：

Face recognition; Feature extraction; Feature selection; Sparse representation;

D O I：

10.12733/jics20104386

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

In order to extract the effective and discriminant face features, a useful feature selection strategy is designed for face representation. The strategy can remove the facial redundancies, extract the discriminant features, promote the calculation efficiency, and also guarantee the feasibility of the recognition framework. Based on this, the sparse representation framework is improved to collect all the face features and match the recognition task. The experiments, tested on ORL, YALE, CMU-PIE and FERET face databases, demonstrate that the proposed method is effective and robust to facial pose, expression and illumination conditions to some extent. © 2014 Binary Information Press

引用

页码：4203 / 4210

页数：7

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