Emotion recognition from color facial images based on multilinear image analysis and Log-Gabor filters

A novel approach is proposed for emotion recognition from low resolution color facial images. The 3D color images are unfolded to 2D matrix based on multilinear algebra. Then, the features are extracted from them by Log-Gabor filters. The optimum features are selected based on mutual information. These features are classified using linear discriminant analysis (LDA) classifier. Experimental results carry out that the proposed method has large improvement in emotion recognition for 3D color facial images. Furthermore, the color subspace has a great impact in the rate of emotion recognition from low resolution images.

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