DocumentCode :
1822650
Title :
Face recognition based on Gabor features
Author :
Bui, Len ; Tran, Dat ; Huang, Xu ; Chetty, Girija
Author_Institution :
Fac. of Inf. Sci. & Eng., Univ. of Canberra, Canberra, ACT, Australia
fYear :
2011
fDate :
4-6 July 2011
Firstpage :
264
Lastpage :
268
Abstract :
The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates.
Keywords :
Gabor filters; face recognition; feature extraction; principal component analysis; support vector machines; visual databases; AT&T database; AdaBoost algorithm; FERET database; Gabor features; Gabor filters; PCA; SVM; discriminative method; face recognition; feature vector extraction; meta-algorithm; principal component analysis; public face database; support vector machine; Face; Face recognition; Feature extraction; Kernel; Principal component analysis; Support vector machines; Training; AdaBoost; Gabor feature; Principal Component Analysis; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Information Processing (EUVIP), 2011 3rd European Workshop on
Conference_Location :
Paris
Print_ISBN :
978-1-4577-0072-9
Type :
conf
DOI :
10.1109/EuVIP.2011.6045542
Filename :
6045542
Link To Document :
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