Video based face recognition using multiple classifiers

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 spatial-temporal information contained in a video sequence. A high recognition rate (98.6%) is achieved on the XM2VTS face video database.