A novel PCA-based bayes classifier and face analysis

Authors:
Zhong Jin;Franck Davoine;Zhen Lou;Jingyu Yang
Affiliations:
Centre de Visió per Computador, Universitat Autònoma de Barcelona, Barcelona, Spain;HEUDIASYC – CNRS Mixed Research Unit, Compiègne University of Technology, Compiègne, France;Department of Computer Science, Nanjing University of Science and Technology, Nanjing, People’s Republic of China;Department of Computer Science, Nanjing University of Science and Technology, Nanjing, People’s Republic of China
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

Citing 2
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Abstract

The classical Bayes classifier plays an important role in the field of pattern recognition. Usually, it is not easy to use a Bayes classifier for pattern recognition problems in high dimensional spaces. This paper proposes a novel PCA-based Bayes classifier for pattern recognition problems in high dimensional spaces. Experiments for face analysis have been performed on CMU facial expression image database. It is shown that the PCA-based Bayes classifier can perform much better than the minimum distance classifier. And, with the PCA-based Bayes classifier, we can obtain a better understanding of data.