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Research on face detection based on cascade support vector machine

2013-09-21
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A face detection algorithm based on cascade support vector machine is proposed for face detection in complex background grayscale images. The algorithm first uses a linear support vector machine for coarse screening to filter out a large number of non-face windows, and then uses a nonlinear support vector machine to classify the windows that pass through. Experimental comparison data shows that this method reduces the difficulty of classifier training, has low computational complexity, and greatly improves the detection speed. Keywords： face detection， support vector machine， pattern classification Face Detection Based on Cascade Support Vector Machine QIU Xiaojia ZHAO Xiuying WANG Jikui （Luoyang College Of Technology, Luoyang 471003, Henan） Abstract：An efficient method of face detection based on cascade Support Vector Machine （CSVM）is proposed in this paper. Firstly，a LSVM coarse filter with relatively lower computational complexity is applied to the whole input image to filter out most of the non-face， then follows the NOSVM classifier to make the final decision，so the detection process is speeded up. The experiment results show that the method can effectively detect faces under complicated background，and the processing time is shorter than using SVM alone.Keywords： face detection， support vector machine， pattern classification

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