Classroom monitoring system based on facial expression recognition

Facial expressions are important information that reflects human emotions. Recognizing dynamic expressions of students in class, 8 kinds of emotions are selected for application: positive emotions: “happy”; negative emotions: “disgust, Sadness, doubts, contempt, anger”; neutral emotion: “focus, surprise”. [1] In this design, the classroom performance scoring system in normal hours is split into four functions: wireless network list acquisition and verification, face recognition, emotion analysis, and scoring record storage. On this basis, SVM and Softmax are used. Facial expression recognition and a data storage database is designed to realize the function of an intelligent scoring system for classroom performance points. To solve this problem, an expression recognition method combining pyramid convolutional neural network and attention mechanism is proposed.