Research Area:  Machine Learning

Abstract:

Facial expression recognition usually can be defined one of the important research in the field of AI and pattern recognition. Facial expression contains rich invisible information, which can help to understand human emotions and intentions, which has great research value. Aiming at solve problems that usually happened such as low recognition accuracy and weak generalization ability of traditional facial expression recognition methods, this paper introduces the theory of the convolution neural network and establishes the convolution neural network model to realize facial expression recognition. Using the crawler to crawl the network image data and using the Viola-Jones algorithm to detect the original data set, after screening, the face expression database is finally established. The convolution neural network model is applied to face expression recognition of the database. We can find that this method can effectively recognize facial expression, and provides a new way to solve this problem.

Keywords:  

Author(s) Name:  Mingjie Wang, Pengcheng Tan, Xin Zhang, Yu Kang, Canguo Jin and Jianying Cao

Publisher name:  IOP

DOI:  10.1088/1742-6596/1601/5/052027

Volume Information:  

Paper Link:   https://iopscience.iop.org/article/10.1088/1742-6596/1601/5/052027/meta