Face Recognition with Supervised Spectral Regression And Multiple Kernel SVM

被引：0

作者：

Xiao, Yongliang ^{[1
]}

Xia, Limin ^{[1
]}

Zhang, Wei ^{[1
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China

来源：

2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 4 | 2010年

关键词：

face recognition; supervised learning; spectral regression; multiple kernel learnin; SVM; PCA;

D O I：

10.1109/ICACC.2010.5486908

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Face recognition plays an every important role in security surveillance, secure access and identity authentication. In this paper, we propose a novel face recognition method based on supervised learning. Our method consists in first extracting face feature using a supervised spectral regression, then we use multiple kernel SVM to classify face. Experimental results on Yale B face database and AR face database show the effectiveness of the proposed method.

引用

页码：343 / 346

页数：4

共 50 条

[31] Kernel Semi-supervised Marginal Fisher Analysis and its Application to Face Recognition
Lin, Yu'e
Liang, Xingzhu
Lin, Yurong
2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 946 - 950
[32] Supervised Curvelet-based face recognition using kernel locality preserving projections
The School of Software, Dalian University of Technology, Dalian 116024, China
J. Comput. Inf. Syst., 9 (3733-3740): : 3733 - 3740
[33] A Novel Multiple Kernel Sparse Representation based Classification for Face Recognition
Zheng, Hao
Ye, Qiaolin
Jin, Zhong
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2014, 8 (04): : 1463 - 1480
[34] Thermal-to-visible face recognition using multiple kernel learning
Hu, Shuowen
Gurram, Prudhvi
Kwon, Heesung
Chan, Alex L.
SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXIII, 2014, 9091
[35] Kernel collaborative face recognition
Wang, Dong
Lu, Huchuan
Yang, Ming-Hsuan
PATTERN RECOGNITION, 2015, 48 (10) : 3025 - 3037
[36] Performance optimisation of face recognition based on LBP with SVM and random forest classifier
Kumar, Ashutosh
Sharma, Gajanand
Pareek, Rajneesh
Sharma, Satyajeet
Dadheech, Pankaj
Gupta, Mukesh Kumar
INTERNATIONAL JOURNAL OF BIOMETRICS, 2023, 15 (3-4) : 389 - 408
[37] Face Recognition based on multi-class SVM
Zhao Lihong
Song Ying
Zhu Yushi
Zhang Cheng
Zheng Yi
CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 5871 - 5873
[38] SUPERVISED-LEARNING BASED FACE HALLUCINATION FOR ENHANCING FACE RECOGNITION
Su, Weng-Tai
Hsu, Chih-Chung
Lin, Chia-Wen
Lin, Weiyao
2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS, 2016, : 1751 - 1755
[39] Semi-supervised local ridge regression for local matching based face recognition
Yi, Yugen
Bi, Chao
Li, Xiaohui
Wang, Jianzhong
Kong, Jun
NEUROCOMPUTING, 2015, 167 : 132 - 146
[40] Patch based Semi-supervised Linear Regression for Single Sample Face Recognition
Liu, Fan
Ding, Yuhua
Yang, Sai
Xu, Feng
2017 IEEE THIRD INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM 2017), 2017, : 62 - 65

← 1 2 3 4 5 →