首页|基于面部表情识别的学生课堂状态分析系统

基于面部表情识别的学生课堂状态分析系统

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近年来,随着计算机视觉的发展,人机交互技术也逐渐应用于教育领域,助力推动教育数字化转型.针对传统课堂中教师无法照顾到每一位学生对知识的掌握程度,制约教学质量的问题,利用Jetson Nano开发套件设计了一种基于面部表情识别的学生课堂状态分析系统,该系统实时检测每个学生面部表情的变化信息并及时反馈给教师,进而帮助教师了解学生的课堂状态,及时调整授课方式,提高教学质量.该系统结构包括摄像头实时采集模块、人脸检测模块、基于深度学习的面部表情识别模型等.所设计的学生课堂状态分析系统识别准确率高、实时性好,对于建设智慧课堂具有很高的应用和推广价值.
Student Classroom State Analysis System Based on Facial Expression Recognition
In view of the problem that teachers cannot take care of each student's grasp of knowledge in the traditional classroom,which restricts the teaching quality,this paper uses Jetson Nano development kit to design a student classroom state analysis system based on facial expression recognition.The system detects the change information of each student's facial expression in real time and timely feeds back to the teacher.Furthermore,it can help teachers to understand stu-dents'classroom status,adjust teaching methods in time and improve teaching quality.The system structure includes real-time camera acquisition module,face detection module,facial expression recognition module based on deep learning.

computer visionfacial expression recognitionstudent classroom state analysis system

赵佳辉、冯晓祥

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上海大学通信与信息工程学院,上海 200444

计算机视觉 面部表情识别 学生课堂状态分析系统

国家自然科学基金

61771299

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(5)
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