Student micro expression recognition and emotion assessment based on the integrating of attention and VGG
In the intelligent classroom,it is of great significance to grasp the emotional state of student in real time for improv-ing the quality of teaching and personalized education.The channel attention mechanism is introduced to improve the VGG16 con-volutional neural network.Combined with the multilayer perceptron the VGG16_SE_MLP model is proposed for the classification and recognition of student micro-expression and emotion assessment.Firstly,the micro-expression dataset is preprocessed,then the feature is extracted,and the SE module is introduced behind the convolution layer,and the batch normalization layer is added to prevent overfitting;the extracted features and micro-expression class are calculated layer by layer through MLP;finally,the student emotion is evaluated.Experimental results show that the proposed method performs well in micro-expression classification and emo-tional assessment,providing a new idea for intelligent classroom.
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