A simple and efficient eigenfaces method

Authors:
Carlos Gómez;Béatrice Pesquet-Popescu
Affiliations:
Signal and Image Processing Dept., Ecole Nationale Supérieure de Télécommunications, Paris, Cedex 13, France;Signal and Image Processing Dept., Ecole Nationale Supérieure de Télécommunications, Paris, Cedex 13, France
Venue:
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Year:
2007

Citing 3
Cited 1

Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

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Eigenfaces for recognition

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Abstract

This paper first presents a review of eigenface methods for face recognition and then introduces a new algorithm in this class. The main difference with previous approaches is the definition of the database. Classically, an image is exploited as a single vector, by concatenating its rows, while here we simply use all the rows as vectors during the training and the recognition stages. The new algorithm reduces the computational complexity of the classical eigenface method and also reaches a higher percentage of recognition. It is compared with other algorithms based on wavelets, aiming at reducing the computational burden. The most efficient wavelet families and other relevant parameters are discussed.