基于二维和三维图像处理技术的在线学习评价研究

Tongyao Ju, Xiangping Shen, Jun Yu
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引用次数: 0

摘要

近年来,新冠肺炎疫情的爆发给全球人民的生命安全带来了严重威胁,也催生了一系列在线学习评估技术的发展。通过微信、腾讯课堂、网易云课堂等多种在线学习平台的研发,学校可以进行在线学习评估,这也促进了在线学习技术的快速发展。通过二维和三维识别技术,在线学习平台可以识别人脸和姿势的变化。基于二维和三维图像处理技术,我们可以对学生的在线学习进行评估,从而识别学生的学习状态和情绪。通过教学评价的粒化,在线学习平台可以对教学过程进行准确的评价和分析,可以实现对学生学习状态的实时教学评价,包括无人、多人、分心、疲劳等。通过相关算法,在线学习平台可以实现对学生头部姿势的评估,对学习疲劳进行实时预警。首先,本文分析了在线学习质量评估的框架。然后,对人脸识别和头姿识别技术进行了分析。最后,提出了一些建议。
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Study on the online learning evaluation based on 2D and 3D image processing technology
In recent years, the outbreak of the COVID-19 epidemic has posed a serious threat to the life safety of people around the world, which has also led to the development of a series of online learning assessment technologies. Through the research and development of a variety of online learning platforms such as WeChat, Tencent Classroom and Netease Cloud Classroom, schools can carry out online learning assessment, which also promotes the rapid development of online learning technology. Through 2D and 3D recognition technology, the online learning platform can recognize face and pose changes. Based on 2D and 3D image processing technology, we can evaluate students' online learning, which will identify students' learning state and emotion. Through the granulation of teaching evaluation, online learning platform can accurately evaluate and analyze the teaching process, which can realize real-time teaching evaluation of students' learning status, including no one, many people, distraction and fatigue. Through relevant algorithms, the online learning platform can realize the assessment of students' head posture, which will give real-time warning of learning fatigue. Firstly, this paper analyzes the framework of online learning quality assessment. Then, this paper analyzes the face recognition and head pose recognition technology. Finally, some suggestions are put forward.
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