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Weighting Estimation for Texture-Based Face Recognition Using the Fisher Discriminant
May/June 2011 (vol. 13 no. 3)
pp. 31-37
Raul Queiroz Feitosa, Pontifical Catholic University of Rio de Janeiro
Dário Augusto Borges Oliveira, Pontifical Catholic University of Rio de Janeiro
Álvaro de Lima Veiga-Filho, Pontifical Catholic University of Rio de Janeiro
Raphael Pithan Brito, Montreal Informática
José Luiz Buonomo de Pinho, Montreal Informática
Antonio Carlos Censi, Montreal Informática

Texture-based automatic face recognition (AFR) methods find global similarities between two faces by computing their local regional similarities. A novel method based on Fisher discriminant analysis is proposed to estimate each region's contribution to the global similarity score. Experimental results show that the method considerably improves recognition performance for texture-based AFR.

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Index Terms:
Biometrics, face recognition, local binary pattern, local phase quantization, software, scientific computing
Citation:
Raul Queiroz Feitosa, Dário Augusto Borges Oliveira, Álvaro de Lima Veiga-Filho, Raphael Pithan Brito, José Luiz Buonomo de Pinho, Antonio Carlos Censi, "Weighting Estimation for Texture-Based Face Recognition Using the Fisher Discriminant," Computing in Science and Engineering, vol. 13, no. 3, pp. 31-37, May-June 2011, doi:10.1109/MCSE.2010.150
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