DocumentCode :
2716532
Title :
Face Recognition using Gaborface-based 2DPCA and (2D)2PCA Classification with Ensemble and Multichannel Model
Author :
Wang, Lin ; Li, Yongping ; Wang, Chengbo ; Zhang, Hongzhou
Author_Institution :
Shanghai Inst. of Appl. Phys., Chinese Acad. of Sci., Shanghai
fYear :
2007
fDate :
1-5 April 2007
Firstpage :
1
Lastpage :
6
Abstract :
This paper introduces Gaborface-based 2DPCA and (2D)2PCA classification method based on 2D Gaborface matrices rather than transformed ID feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is proved with the experimental results on the ORL and Yale databases. In particular, the MGFR-based (2D)2 PCA method achieves 100% recognition accuracy for ORL database, and 98.89% accuracy for Yale database with five training samples per class
Keywords :
face recognition; image representation; matrix algebra; pattern classification; principal component analysis; visual databases; Gaborface matrices; Gaborface-based 2DPCA; ORL database; PCA classification; Yale database; ensemble Gaborface representation; face recognition; feature vectors; multichannel Gaborface representation; multichannel model; recognition accuracy; Computational intelligence; Convolution; Databases; Face recognition; Filter bank; Gabor filters; Image coding; Image sampling; Principal component analysis; Sampling methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Security and Defense Applications, 2007. CISDA 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0700-1
Type :
conf
DOI :
10.1109/CISDA.2007.368128
Filename :
4219075
Link To Document :
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