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

共 50 条

[31] A novel discriminant criterion based on feature fusion strategy for face recognition [J].

Chen, Wen-Sheng ;

Dai, Xiuli ;

Pan, Binbin ;

Huang, Taiquan .

NEUROCOMPUTING, 2015, 159 :67-77

[32] Face Recognition Based on Local Feature Analysis [J].

Qian, Zhi-ming ;

Su, Peng-yu ;

Xu, Dan .

ISCSCT 2008: INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND COMPUTATIONAL TECHNOLOGY, VOL 2, PROCEEDINGS, 2008, :264-267

[33] Adaptive BPSO based Feature Selection and Skin Detection based Background Removal for Enhanced Face Recognition [J].

Sattiraju, Mayukh ;

Vikram, Manikandan M. ;

Manikantan, K. ;

Ramachandran, S. .

2013 FOURTH NATIONAL CONFERENCE ON COMPUTER VISION, PATTERN RECOGNITION, IMAGE PROCESSING AND GRAPHICS (NCVPRIPG), 2013,

[34] Entropic-GWT Based Feature Extraction and LBPSO Based Feature Selection for Enhanced Face Recognition [J].

Sah, Rageeni ;

Shreeja, B., V ;

Manikantan, K. ;

Ramachandran, S. .

2015 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2015, :180-184

[35] Multi-Objective Particle Swarm Optimization-based Feature Selection for Face Recognition [J].

Larabi-Marie-Sainte, Souad ;

Ghouzali, Sanaa .

STUDIES IN INFORMATICS AND CONTROL, 2020, 29 (01) :99-109

[36] Feature Selection using Binary-ABC Algorithm for DWT-based Face Recognition [J].

Akhil, Malepati Bala Siva Sai ;

Aashish, P. ;

Manikantan, K. .

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2015, :30-36

[37] A Novel Feature Extraction Method Based on Collaborative Representation for Face Recognition [J].

Huang, Wei ;

Wang, Xiaohui ;

Li, Jianzhong ;

Jin, Zhong .

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2015, 29 (04)

[38] Using rough set in feature selection and reduction in face recognition problem [J].

Bac, LH ;

Tuan, NA .

ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2005, 3518 :226-233

[39] Feature Selection Optimized by Discrete Particle Swarm Optimization for Face Recognition [J].

Yan, Yanjun ;

Kamath, Ganapathi ;

Osadciw, Lisa Ann .

OPTICS AND PHOTONICS IN GLOBAL HOMELAND SECURITY V AND BIOMETRIC TECHNOLOGY FOR HUMAN IDENTIFICATION VI, 2009, 7306

[40] Face Feature Selection and Recognition Using Separability Criterion and Binary Particle Swarm Optimization Algorithm [J].

Yin Hongtao ;

Fu Ping ;

Sun Zhen .

CHINESE JOURNAL OF ELECTRONICS, 2014, 23 (02) :361-365

← 1 2 3 4 5 →