题名 | A scalable real-time computer vision system for student posture detection in smart classrooms |
作者 | |
通讯作者 | Zhou, Ding |
发表日期 | 2023-11-01
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DOI | |
发表期刊 | |
ISSN | 1360-2357
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EISSN | 1573-7608
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卷号 | 29期号:1页码:917-937 |
摘要 | Technological advancements have ushered in a new era of global educational development. Artificial Intelligence (AI) holds the potential to enhance teaching effectiveness and foster educational innovation. By utilizing student posture as a proxy, computer vision technology can accurately gauge levels of student engagement. While previous efforts have focused on refining posture classification models, this study uniquely addresses the comprehensive implementation of a real-time posture detection workflow, encompassing software, hardware, and network aspects. The proposed posture detection system leverages surveillance cameras equipped with cutting-edge computer vision technology, specifically employing the Open Visual Inference & Neural Network Optimization (Open VINO) model for precise student posture detection. Data transmission is facilitated using the Message Queuing Telemetry Transport (MQTT) protocol, effectively establishing a seamless posture detection workflow within the classroom setting. To validate the system, video recordings from a real teaching environment (a fifth-grade class in the Chinese compulsory education system) were analyzed, resulting in posture classifications with impressive accuracies of 0.933 for standing, 0.772 for sitting, and 0.959 for hand-raising. Achieving a frame processing time ranging from 109 to 758 milliseconds, the system efficiently delivers real-time posture data to educators. Consequently, the posture detection system developed in this study possesses the capability to intelligently monitor student postures in the classroom, with the potential to enhance teaching quality in smart classrooms. |
关键词 | |
相关链接 | [来源记录] |
收录类别 | |
语种 | 英语
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学校署名 | 第一
; 通讯
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资助项目 | Centre for Future Education Research at the Southern University of Science and Technology[FE22Z004]
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WOS研究方向 | Education & Educational Research
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WOS类目 | Education & Educational Research
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WOS记录号 | WOS:001107671900002
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出版者 | |
Scopus记录号 | 2-s2.0-85177670256
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来源库 | Web of Science
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引用统计 | |
成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/629023 |
专题 | 工学院_系统设计与智能制造学院 |
作者单位 | Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen 518055, Peoples R China |
第一作者单位 | 系统设计与智能制造学院 |
通讯作者单位 | 系统设计与智能制造学院 |
第一作者的第一单位 | 系统设计与智能制造学院 |
推荐引用方式 GB/T 7714 |
Huang, Jiawei,Zhou, Ding. A scalable real-time computer vision system for student posture detection in smart classrooms[J]. EDUCATION AND INFORMATION TECHNOLOGIES,2023,29(1):917-937.
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APA |
Huang, Jiawei,&Zhou, Ding.(2023).A scalable real-time computer vision system for student posture detection in smart classrooms.EDUCATION AND INFORMATION TECHNOLOGIES,29(1),917-937.
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MLA |
Huang, Jiawei,et al."A scalable real-time computer vision system for student posture detection in smart classrooms".EDUCATION AND INFORMATION TECHNOLOGIES 29.1(2023):917-937.
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