Two dimensional laplacianfaces method for face recognition

Authors:
Niu Ben;Simon Chi Keung Shiu;Sankar Kumar Pal
Affiliations:
Department of Computing, Hong Kong Polytechnic University, Hong Kong, China;Department of Computing, Hong Kong Polytechnic University, Hong Kong, China;Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India
Venue:
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Year:
2006

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Abstract

In this paper we propose the two dimensional Laplacianfaces method for face recognition. The new algorithm is developed based on the two techniques, i.e., locality preserved embedding and image based projection. The two dimensional Laplacianfaces method is not only computationally more efficient but also more accurate than the one dimensional Laplacianfaces method in extracting the facial features for human face authentication. Extensive experiments are performed to test and evaluate the new algorithm using the Yale and the AR face databases. The experimental results indicate that the two dimensional Laplacianfaces method significantly outperforms the existing two dimensional Eigenfaces, the two dimensional Fisherfaces and the one dimensional Laplacianfaces methods under the various settings of experiment conditions.