Human Face Expression Recognition Based on Feature Fusion

Abstract

The Gabor wavelet is the important technique widely used in the areas of images recognition such as human face expression, it extract the more important grain features for face expression effective, but it does not take into account the relative changes in the important characteristics of each location of the point features. Aiming at recognizing the information of human face expression, fuse the geometry feature based on angle changes at key parts on face expression, and then a radial basis function (RBF) neural network is designed as the classifier to perform recognition. The results of the experiment in the human face expression database indicate that the recognition rate by the feature fusion is obviously superior to that of traditional method.