Face recognition using multiple recognizers

In this paper we have presented a fusion of three face recognizers, LFA, LBA and KDDA, which combines the three confidence measure factors (CMFs) using a RBF neural network. This strategy is used to increase the accuracy of the face recognition system. The recognizer is tested on AT&T-ORL, AR an...

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Bibliographic Details
Published in2004 IEEE International Conference on Systems, Man and Cybernetics Vol. 3; pp. 2186 - 2190 vol.3
Main Authors Vatsa, M., Singh, R., Gupta, P.
Format Conference Proceeding
LanguageEnglish
Published Piscataway NJ IEEE 2004
Subjects
Algorithm design and analysis
Applied sciences
Artificial intelligence
Biometrics
Computer science
Computer science; control theory; systems
Control theory. Systems
Exact sciences and technology
Face detection
Face recognition
Humans
Image analysis
Image databases
Layout
Pattern recognition. Digital image processing. Computational geometry
Testing
Radial basis function
Face recognition
Image processing
Confidence
Image databank
Facies
Autoregressive model
Regression analysis
Pattern recognition
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ISBN0780385667
9780780385665
ISSN1062-922X
DOI10.1109/ICSMC.2004.1400652

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Summary:In this paper we have presented a fusion of three face recognizers, LFA, LBA and KDDA, which combines the three confidence measure factors (CMFs) using a RBF neural network. This strategy is used to increase the accuracy of the face recognition system. The recognizer is tested on AT&T-ORL, AR and IITK face database and the results are found to be more than 95%.
ISBN:0780385667
9780780385665
ISSN:1062-922X
DOI:10.1109/ICSMC.2004.1400652