Issue No. 03 - May/June (2011 vol. 13)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCSE.2010.149
Luiz Oliveira , UFPR, Curitiba
Marcelo Mansano , UEPG, Ponta Grossa
Alessandro Koerich , PUCPR, Curitiba
Alceu de Souza Britto , PUCPR Pontifical Catholic University of Parana, Curitiba Curitiba
Although it shows enormous potential as a feature extractor, 2D principal component analysis produces numerous coefficients. Using a feature-selection algorithm based on a multiobjective genetic algorithm to analyze and discard irrelevant coefficients offers a solution that considerably reduces the number of coefficients, while also improving recognition rates.
face recognition, feature extraction, genetic algorithms, principal component analysis
L. Oliveira, M. Mansano, A. Koerich and A. de Souza Britto, "2D Principal Component Analysis for Face and Facial-Expression Recognition," in Computing in Science & Engineering, vol. 13, no. 3, pp. 9-13, 2012.