关键词: 微表情识别, 分层时空特征, 细粒度

Abstract:

Micro-expression recognition is still a challenging task due to its short duration of less than 0.5?s, involuntariness, and low intensity. The hierarchical spatio-temporal feature descriptor is improved, and a new fine-grained hierarchical spatio-temporal feature micro-expression recognition method is proposed. Firstly, the spatio-temporal features of each level in the micro-expression video clip are extracted, and the projection matrix is used to establish the relationship between the spatio-temporal features and the micro-expressions, and then the regions that contribute to the recognition task are selected. Then it counts the layer with the overall maximum contribution, and performs the intersection operation between the selected blocks at the lower layer and the selected blocks in the previous layer to achieve the purpose of removing the spatial redundancy of the hierarchical spatio-temporal features and improving the discrimination of the micro-expression features. Experiments on CASME[Ⅱ] show that the proposed method can fine-grain the micro-expression area and obtain better recognition results.

Key words: micro-expression recognition, hierarchical spatio-temporal feature, fine-grained