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Facial feature extraction and selection by Gabor wavelets and boosting

Zhou, M. and Wei, H. (2009) Facial feature extraction and selection by Gabor wavelets and boosting. In: The 2nd International Congress on Image and Signal Processing, Tianjin, China, https://doi.org/10.1109/CISP.2009.5304650 .

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To link to this item DOI: 10.1109/CISP.2009.5304650

Abstract/Summary

In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.

Item Type:Conference or Workshop Item (Paper)
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:15082
Uncontrolled Keywords:Gabor wavelet features , boosting algorithm , face verification , facial feature extraction

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