This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Conference on Pattern Recognition (ICPR'06) Volume 1
Face Verification Using GaborWavelets and AdaBoost
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
Mian Zhou, University of Reading, UK
Hong Wei, University of Reading, UK
This paper presents a new face verification algorithm based on Gabor wavelets and AdaBoost. In the algorithm, faces are represented by Gabor wavelet features generated by Gabor wavelet transform. Gabor wavelets with 5 scales and 8 orientations are chosen to form a family of Gabor wavelets. By convolving face images with these 40 Gabor wavelets, the original images are transformed into magnitude response images of Gabor wavelet features. The AdaBoost algorithm selects a small set of significant features from the pool of the Gabor wavelet features. Each feature is the basis for a weak classifier which is trained with face images taken from the XM2VTS database. The feature with the lowest classification error is selected in each iteration of the AdaBoost operation. We also address issues regarding computational costs in feature selection with AdaBoost. A support vector machine (SVM) is trained with examples of 20 features, and the results have shown a low false positive rate and a low classification error rate in face verification.
Citation:
Mian Zhou, Hong Wei, "Face Verification Using GaborWavelets and AdaBoost," icpr, vol. 1, pp.404-407, 18th International Conference on Pattern Recognition (ICPR'06) Volume 1, 2006
Usage of this product signifies your acceptance of the Terms of Use.