A Classroom Atmosphere Management System for Analyzing Human Behaviors in Class Activities
Yu-Te Ku, Han-Yen Yu, Yi-Chi Chou · 2019
Deep learning can considerably improve the processing of human behavior signals. This paper presents a system that used computer vision processing of human behavior signals to analyze the behaviors of students in class activities. CIassFu system can be used in physical and online teaching environments. It used image sensors to capture student class behaviors, analyzing classroom atmosphere and the level of teacher-student interaction. The system presents objective data on a teaching setting, which can be used to assess students' learning conditions more effectively and enhance teacher-student interactions.