Students Status Analysis and Class Teaching Effect Evaluation System Based on the Analysis of Monitoring Video

摘要

Students status analysis is important to the teaching effect evaluation and improvement. In this paper, we propose a method to acquire the status of students by analyzing the monitoring video processing. We use the HD cameras in front of the classroom to capture the real time class video and transmit it to the servers for processing. For students status analysis, we firstly extract the student area by foreground and background segmentation and then use the skin color detection and AdaBoost classifier to find the faces of students. At last pattern recognition method is used to find the student's status. The statistical results of status could be given to the teachers for improving their teaching effect.