基于计算机视觉的课堂专注度分析:面部表情与头部姿态识别方法  

Computer vision based classroom focus analysis:facial expression and head posture recognition method

作　　者：庄瑶 ZHUANG Yao(Qingdao University,Qingdao,Shandong 266000,China)

机构地区：[1]青岛大学,山东青岛266000

出　　处：《计算机应用文摘》2025年第9期97-99,103,共4页

摘　　要：随着教育技术的不断发展,如何评估学生的课堂专注度已成为一个重要课题。基于计算机视觉技术,设计并实现了一套系统,通过识别和分析学生的面部表情及头部姿态来评估其课堂专注度。系统采用CNN模型进行表情识别,并利用OpenFace2.0工具检测头部姿态,结合两者的结果,实现对学生专注度的实时监控,并生成相关评估数据。系统采用分层设计,包括数据获取、内容识别和结果分析等模块,最终将评估结果反馈给学生和教师,以优化教学效果。实验结果表明,该系统能够准确识别表情和头部姿态,并有效评估学生的课堂表现。With the continuous development of educational technology,how to evaluate students̓classroom focus has become an important issue.Based on computer vision technology,a system was designed and implemented to evaluate students̓classroom focus by recognizing and analyzing their facial expressions and head posture.The system uses a CNN model for facial expression recognition and utilizes the OpenFace 2.0 tool to detect head posture.Combining the results of both,it achieves real-time monitoring of students̓concentration and generates relevant evaluation data.The system adopts a layered design,including modules such as data acquisition,content recognition,and result analysis,and ultimately feedback the evaluation results to students and teachers to optimize teaching effectiveness.The experimental results show that the system can accurately recognize facial expressions and head postures,and effectively evaluate students̓classroom performance.

关 键 词：计算机视觉 面部表情识别 头部姿态识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]