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Issue No.03 - May/June (2011 vol.13)
pp: 9-13
Marcelo Mansano , UEPG, Ponta Grossa
Alessandro Koerich , PUCPR, Curitiba
Alceu de Souza Britto, Jr. , PUCPR Pontifical Catholic University of Parana, Curitiba Curitiba
<p>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.</p>
Face recognition, facial expression recognition, feature selection, scientific computing, graphics and multimedia
Marcelo Mansano, Alessandro Koerich, Alceu de Souza Britto, Jr., "2D Principal Component Analysis for Face and Facial-Expression Recognition", Computing in Science & Engineering, vol.13, no. 3, pp. 9-13, May/June 2011, doi:10.1109/MCSE.2010.149
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