Face recognition system by fast and incremental learning method

被引:0
作者
Kang, Woo-Sung [1 ]
Na, Jin Hee [1 ]
Ahn, Ho Seok [1 ]
Choi, Jin Young [1 ]
机构
[1] Seoul Natl Univ, Sch Elect Engn & Comp Sic, Automat & Syst Res Inst, Seoul, South Korea
来源
2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13 | 2006年
关键词
face recognition; fast training; incremental learning;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces the face recognition system architecture based on intelligent macro core for face recognition. And we propose a novel classification method based on Support Vector Domain Description(SVDD). It enables the proposed system to be trained rapidly and improve the recognition rate gradually by learning face incrementally. In order to verify the performance of our scheme in real world, experiments are carried out under various illumination condition. The experimental results show that the proposed system can improve the recognition rate gradually by fast and incremental learning method.
引用
收藏
页码:2105 / +
页数:2
相关论文
共 11 条
[1]  
[Anonymous], 1997, P IEEE C COMP VIS PA
[2]  
BOTTOU L, 1994, INT C PATT RECOG, P77, DOI 10.1109/ICPR.1994.576879
[3]   A tutorial on Support Vector Machines for pattern recognition [J].
Burges, CJC .
DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 2 (02) :121-167
[4]  
Freund Y., 1995, Computational Learning Theory. Second European Conference, EuroCOLT '95. Proceedings, P23
[5]   A comparison of methods for multiclass support vector machines [J].
Hsu, CW ;
Lin, CJ .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (02) :415-425
[6]  
JOIFFE IT, 1986, PRINCIPAL COMPONENT
[7]   Neural network-based face detection [J].
Rowley, HA ;
Baluja, S ;
Kanade, T .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1998, 20 (01) :23-38
[8]  
SCHOLKOPF B, 1999, ADV KERNEL METHODS S, P255
[9]   Support vector domain description [J].
Tax, DMJ ;
Duin, RPW .
PATTERN RECOGNITION LETTERS, 1999, 20 (11-13) :1191-1199
[10]  
VAPNIK V, 1998, STAT LEARNIGN THEORY