Behavior Recognition of Teachers and Students in the Smart Classroom Based on Deep Learning

With the development of the concept of education evaluation, it is a key issue to effectively and accurately detect and analyze the behavior categories of teachers and students in the classroom. Firstly, this paper investigates the common behavior categories of students and teachers in the classroom. And on this basis, we sorts out 7 major behavior categories that students are usually involved in the classroom. Then, computer vision and artificial intelligence techniques are introduced to design an intelligent classroom behavior recognition system for teachers and students. Finally, the system is applied to various types of datasets for testing to verify the effectiveness of the system. Based on computer vision and artificial intelligence technology, the detection and analysis of students learning behavior in classroom can provide timely data support for teachers to grasp students' classroom learning status, optimize teaching design and implementation.