关键词: 微表情识别, 卷积神经网络（CNN）, LBP-TOP算法, 光流法, 计算机视觉

Abstract:

Micro-expression is a subtle change of human face when trying to cover up their emotions. It is widely used in lie-detect, security, psychological therapy, micro-expression recognition robot and so on. Therefore, micro-expression recognition has been paid more attention. This paper analyzes the main methods of micro-expression recognition：convolution neural network and its improvement, optical flow method and its improvement, local binary pattern and its improved methods. The existing methods are compared and summarized from the algorithms, the accuracy, the advantages and disadvantages of each method, and the characteristics of various methods. Finally, the existing problems of micro-expression recognition are discussed, and the future development direction is prospected.

Key words: micro-expression recognition, Convolutional Neural Networks（CNN）, Local Binary Patterns from Three Orthogonal Planes（LBP-TOP）, optical flow, computer , vision