Studies Advanced in Development and Application of Facial Expression Recognition

Abstract

Facial expression is an important way to convey people's inner emotional changes, as the basis of emotional understanding and the prerequisite for computers to understand human emotions, expression recognition has attracted more and more research attention from academia and industry in recent years. Most of the early expression recognition methods relied on manual features such as texture, geometry, and contour. Thanks to the powerful feature representation capability of convolutional neural networks, deep learning-based face recognition technology has made breakthroughs in recognition accuracy and speed. This paper details the latest research progress in the field of face expression recognition, including the design ideas, key steps, advantages and disadvantages of representative methods. This paper also introduces the common face expression recognition datasets and quantitatively compares the results of different methods on these datasets. Finally, this paper discusses the problems in the face expression recognition research field and look forward to the future development.