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

摘要：

微表情是人类在试图掩饰自己情感时所产生的面部细微变化，在测谎、安防、心理学治疗和微表情识别机器人等方面有着非常广泛的应用，因此微表情识别也开始得到重视。从微表情识别的主流的方法：卷积神经网络及其改进、光流法及其改进、局部二值模式及其改进方法进行分析，对现存的几种方法从使用的算法、准确率、各方法的优缺点、各方法的特点等几个角度进行对比总结；阐述微表情识别目前存在的问题，并对未来的发展方向进行展望。

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