The Method of Human Facial Expression Recognition Based on Wavelet Transformation and Weighted PCA
Hua Yu-ning · Transactions of Shenyang Ligong University · 2008
In this paper,a new method of human facial expression recognition based on weighted PCA is proposed.At first,the wavelet transformation is used to extract the effective feature for identification on the face area. Then the weighted features are combined with PCA.After that,the weighted subspaces for each class of training sample are calculated by minimizing the weighted reconstruction errors.Finally,the Mahalanobis distances from the tested samples to the weighted subspace are computed and the classified recognition is carried out according to the distances.Based on the human facial expressing database of CMU,the experiment shows that this method can increase the recognition rate significantly without increasing the computation,when compared with the traditional PCA.