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《Journal of Tsinghua University(Science and Technology)》 2003-01
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Face detection based on hierarchical support vector machines

MA Yong, DING XiaoqingDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, China)  
Face detection in images with complex backgrounds has many applications such as face recognition and humancomputer interaction. However, most face detection methods have troubles with the training of the classifier and the computational complexity. A face detection method based on a hierarchical support vector machines (SVM) presents improved methods for both of these problems. The hierarchical SVM is a combination of several linear SVMs and a nonlinear SVM. In the detection stage, the linear SVMs are used to quickly exclude most nonfaces in the images while the nonlinear SVM is used to further verify possible face candidates. Experimentals using CarnegieMellon University and Nokia databases demonstrat that the hierarchical architecture of the classifier not only achieves high detection rate, but also reduces the computational complexity.
【Fund】: 国家自然科学基金资助项目(69972024)
【CateGory Index】: TP391.4
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