Facial expression recognition is the basis of human emotion recognition, which has been a hot topic in pattern recognition and artificial intelligence. This paper summarizes the development process of facial expression recognition framework, mainly including the traditional expression feature extraction, expression classification method and deep learning-based expression recognition method, and then analyzes and compares the recognition rate and performance of various algorithms. Moreover, this paper introduces the commonly used datasets of facial expression recognition and the advantages and problems of each data set. In view of these problems, the techniques and methods for data enhancement are analyzed, such as generative adversarial network (GAN). Finally, the existing problems in the field of facial expression recognition are summarized and the prospect of future development is put forward.