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A subspace approach to face detection with support vector machines

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3 Author(s)
Haizhou Ai ; Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China ; Lihang Ying ; Guangyou Xu

We present a subspace approach to face detection with support vector machines (SVMs). A linear SVM classifier is trained as a filter to produce a subspace in which a non-linear SVM classifier with Gaussian kernel is trained for face detection. This makes training easier and results in a very efficient face detection algorithm. Experimental results demonstrate their promising performance compared with some well-known existing detectors.

Published in:

Pattern Recognition, 2002. Proceedings. 16th International Conference on  (Volume:1 )

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