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作 者:李小兰 孙金瑞 冉长双 肖玲敏 李洪进 Li Xiaolan;Sun Jinrui;Ran Changshuang;Xiao Limin;Li Hongjin(School of Medical Information Engineering,Zunyi Medical University,Zunyi 563000,China)
机构地区:[1]遵义医科大学医学信息工程学院,贵州遵义563000
出 处:《无线互联科技》2022年第1期79-81,共3页Wireless Internet Technology
基 金:贵州省科技计划项目;项目名称:基于区块链技术的共享电子病历系统研究;项目编号:黔科合平台人才【2018】5772-050。
摘 要:人脸表情识别技术一直以来都是人机交互领域的热门技术、关键技术。近些年来,人脸表情识别在教学质量分析、心理分析得到了广泛关注。特别是教学质量分析,通过对课堂上学生的表情分析,可以得到课堂教学质量、效率等关键信息。要针对课堂上的学生识别人脸表情并进行表情分析,在课堂上所能得到的人脸图像大多是非正面的,为了更好地得到教学质量信息,就要对正面和非正面的人脸图像进行人脸表情识别。鉴于此,文章首先介绍了人脸表情识别技术、表情特征提取和分类方法,然后介绍了非正面人脸表情识别技术以及现有的非正面人脸数据库,最后总结了教学质量分析中人脸表情识别方法的研究现状,并对进一步的教学分析研究和发展方向进行了展望。Facial expression recognition technology has always been a hot technology and key technology in the field of humancomputer interaction. In recent years, facial expression recognition has been widely concerned in teaching quality analysis and psychological analysis. Especially the analysis of teaching quality, through the expres-sion analysis of students in the classroom, we can get the key information of classroom teaching quality, efficiency and so on. In order to recognize the facial expression and analyze the facial expression of the students in the classroom, most of the facial images can be obtained in the classroom. In order to get the information of teaching quality better, face expression recognition should be carried out on positive and nonpositive face images. In view of this, the facial expression recognition technology, facial expression feature extraction and classification method are first introduced, then the nonpositive facial expression recognition technology and the existing non-positive face database are introduced. Finally, the research status of facial expression recognition method in teaching quality analysis is summarized, and the further teaching analysis research and development direction are prospected.
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