Mixture-of-Laplacian faces and its application to face recognition

Authors:
S. Noushath;Ashok Rao;G. Hemantha Kumar
Affiliations:
Dept of Studies in Computer Science, University of Mysore, Mysore, India;Dept of Electronics and Communication, SJ College of Engineering, Mysore, India;Dept of Studies in Computer Science, University of Mysore, Mysore, India
Venue:
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Year:
2007

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Abstract

The locality preserving projection (LPP), known as Laplacianfaces, was recently proposed as a transformation technique of mapping which optimally preserves the neighborhood structure of the dataset. In this paper, an efficient method for face recognition called mixture-of-Laplacianfaces (or LPP mixture model) is proposed, which obtains several sets of Laplacianfaces through Expectation-Maximization (EM) learning of Gaussian Mixture Models (GMM). Experiments carried out by using this on ORL, FERET and COIL-20 indicate superior performance as compared with method based on Laplacianfaces and other contemporary subspace methods.