CASIA OpenIR  > 09年以前成果
Face recognition with support vector machine
Zhang, SY; Qiao, H
2003
Conference NameIEEE International Conference on Robotics, Intelligent Systems and Signal Processing
Source Publication2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS
Conference DateOCT 08-13, 2003
Conference PlaceChangsha, PEOPLES R CHINA
AbstractThe 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.
KeywordRegression
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12850
Collection09年以前成果
Corresponding AuthorQiao, H
Recommended Citation
GB/T 7714
Zhang, SY,Qiao, H. Face recognition with support vector machine[C],2003.
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