Independent Gabor Analysis of Discriminant Features Fusion for Face Recognition
Authors:
- 9 January 2009
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Signal Processing Letters
- Vol. 16 (2) , 97-100
Abstract
A discriminant feature fusion model is proposed for face recognition with large variations of pose, expression, lighting, etc. Discriminant features are extracted by the wavelet transform-based method from two source images. One source image is a holistic gray value image and the other is an illumination invariant geometric image. Face sample is reconstructed by the adaptive fused discriminant feature. Then a bank of Gabor filters is built to extract Gabor representations of the reconstructed samples. Finally higher-order statistical relationships among variables of samples are extracted for classifier. According to experiments, the model outperforms conventional algorithms under complex conditions (large variations of lighting, expression, accessory, etc.).Keywords
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