Face recognition with support vector machine

CASIA OpenIR > 09年以前成果

	Face recognition with support vector machine
	Zhang, SY; Qiao, H
	2003
会议名称	IEEE International Conference on Robotics, Intelligent Systems and Signal Processing
会议录名称	2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS
会议日期	OCT 08-13, 2003
会议地点	Changsha, PEOPLES R CHINA
摘要	The application of Support Vector Machines (SVMs) in face recognition is investigated in this paper. SVM is a classification algorithm recently developed by V. Vapnik and his team. Based on the underlying optimization and statistical learning theories, SVMs provide a new approach to the problem of pattern recognition. In this paper, both linear and nonlinear SVM training models are used in face recognition. Faces in different orientations are taken as training samples. Primary results show that nonlinear training machine is better than linear machine; the former one always has a much larger margin, which means that it has a much stronger ability in classification and recognition.
关键词	Regression
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12850
专题	09年以前成果
通讯作者	Qiao, H
推荐引用方式 GB/T 7714	Zhang, SY,Qiao, H. Face recognition with support vector machine[C],2003.