A Micro-expression Recognition Algorithm for Students in Classroom Learning Based on Convolutional Neural Network

Abstract

In classroom teaching, the teachers should adjust the teaching strategy and improve the teaching effect based on the expression and learning state of each student. This paper mainly develops a micro-expression recognition algorithm for students in classroom learning, based on convolutional neural network (CNN) and automatic face detection. Specifically, the multitask deep convolution network (DNN) was adopted to detect the landmark points of human face, and a hybrid DNN was designed to extract the optical-flow features of micro-expression. The extracted features were improved through redundancy removal and dimensionality reduction. The rationality of our algorithm was proved through a comparative experiment on real-world databases and an application in classroom teaching. The research results provide a new direction for applying deep learning in face recognition.