Research of Micro-expression Recognition Model based on Feature Unit

Micro-expression which is the transient expression will be disclosed when people try to hide some kind of real inner emotions. Micro-expression changes so fast that few people detect its existence. As an effective behavioral clue, it is of great significance to understand the change of peoples true feelings. Based on this, image feature extraction in machine learning has made remarkable progress in the past two years. In order to improve the accuracy and practicability of micro-expression recognition, this paper deeply analyzed the practical micro-expression recognition method. Based on landmark detection. We construct a quantitative model and established a machine learning model of micro-expression judgment based on the comprehensive changes of eyes, mouth and eyebrows. This paper combine the feature unit and model application scene for judgement of micro-expression. This method reflect the design idea that the changes of face locality contributed to the overall micro-expression judgment, and helped to complete the high autonomous construction of the micro expression judgment model.