Video based face recognition using multiple classifiers

Authors:
Xiaoou Tang;Zhifeng Li
Affiliations:
Department of Information Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;Department of Information Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Venue:
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Year:
2004

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Abstract

The main advantage of the video based face recognition method is that more information is available in a video sequence than in a single image. In order to take advantage of the large amount of information in the video sequence, we develop a multiple classifiers fusion based video face recognition algorithm. The method preserves all the spatialtemporal information contained in a video sequence. A high recognition rate (98.6%) is achieved on the XM2VTS face video database.