DocumentCode :
1398359
Title :
2D Principal Component Analysis for Face and Facial-Expression Recognition
Author :
Oliveira, Luiz S. ; Koerich, Alessandro L. ; Mansano, Marcelo ; Britto, Alceu S., Jr.
Author_Institution :
Fed. Univ. of Parana, Curitiba, Brazil
Volume :
13
Issue :
3
fYear :
2011
Firstpage :
9
Lastpage :
13
Abstract :
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.
Keywords :
face recognition; feature extraction; genetic algorithms; principal component analysis; 2D principal component analysis; face recognition; facial-expression recognition; feature extractor; feature-selection algorithm; irrelevant coefficients; multiobjective genetic algorithm; recognition rates; Accuracy; Covariance matrix; Databases; Face; Face recognition; Feature extraction; Principal component analysis; Face recognition; facial expression recognition; feature selection; graphics and multimedia; scientific computing;
fLanguage :
English
Journal_Title :
Computing in Science & Engineering
Publisher :
ieee
ISSN :
1521-9615
Type :
jour
DOI :
10.1109/MCSE.2010.149
Filename :
5661748
Link To Document :
بازگشت