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In this paper, Fisherface is extended for face recognition from one example image per person. Fisherface is one of the most successful face recognition methods. However, Fisherface requires several training images for each face, so it cannot be applied to face recognition applications where only one example image per person is available for training. To tackle this problem, Fisherface method is extended by utilizing 3D morphable model to derive multiple images of a face from one single image. Experimental results on ORL face database and UMIST face database show that face recognition method proposed in this paper makes impressive performance improvement compared with conventional eigenface methods.
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on (Volume:7 )
Date of Conference: 18-21 Aug. 2005