Facial recognition method based on feature fusion and data enhancing

Abstract

Face expression recognition is a technique that recognizes the emotions of a person from a static picture or a dynamic video. So it has great potential application value in psychology, intelligent robotics, intelligent monitoring, virtual reality and synthetic animation. In this paper, we propose an innovative method of feature fusion in view of the low accuracy of the traditional method facial expression recognition algorithm in the real environmental. And the fusion features are predicted by using the support vector machine, which makes the detection of the model accurate rate reach 67% on FER2013, surpassing the single method. Furthermore, we use the GAN network to enhance the data, minimize the impact of irregular data on the results, and finally reach 72% accuracy.