Proceedings of the Korean Society of Broadcast Engineers Conference (한국방송∙미디어공학회:학술대회논문집)
- 2009.01a
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- Pages.592-595
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- 2009
FACE DETECTION USING SKIN-COLOR MODEL AND SUPPORT VECTOR MACHINE
- Seld, Yoko (Department of Information Systems Science Graduate School of Engineering, Utsunomiya University) ;
- Yuyama, Ichiro (Department of Information Systems Science Graduate School of Engineering, Utsunomiya University) ;
- Hasegawa, Hiroshi (Department of Information Systems Science Graduate School of Engineering, Utsunomiya University) ;
- Watanabe, Yu (Department of Information Systems Science Graduate School of Engineering, Utsunomiya University)
- Published : 2009.01.12
Abstract
In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.