Facial micro-expression recognition method based on CNN and transformer mixed model

The existing methods for facial microexpression recognition have the problem of low efficiency and accuracy. Therefore, a facial micro-expression recognition method based on a hybrid model of CNN and transformer is proposed. Extract facial hierarchical features using a hybrid model of CNN and transformer, and use them as inputs to a deep network. At the same time, the facial microexpression image area is segmented and the image is smoothed through threshold to obtain the feature vectors of the facial microexpression. These feature vectors are input into a CNN and transformer hybrid model to achieve recognition of facial microexpressions. The experimental results show that the proposed method can recognise facial microexpressions in complete or incomplete images, and the recognition state delay is controlled below 5 ms. In addition, compared to traditional methods, this method has a higher average recognition accuracy, up to 98%.