Expression recognition based on wavelet decomposition and selected VLBP feature
基于小波分解和优选的VLBP特征的表情识别方法*

This paper proposed a new method of expression recognition based on wavelet decomposition and selected VLBP feature. This method enhanced original data by wavelet decomposition first, obtained several different frequency sub-images. Then extracted the features from these sub-images with different block size using VLBP operator. After that, selected features by contribution analysis algorithm of neural network. At last, recognized six expressions by support vector machine classifier. The experiments show that this method have higher recognition rate than pure VLBP feature extracted from original image. And tihs method can be used for real-time facial expression recognition because of its high speed.