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18 November 2019 BNU-LCSAD: a video database for classroom student action recognition
Bo Sun, Kaijie Zhao, Yongkang Xiao, Jun He, Lejun Yu, Yong Wu, Huanqing Yan
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Proceedings Volume 11187, Optoelectronic Imaging and Multimedia Technology VI; 111871V (2019) https://doi.org/10.1117/12.2539052
Event: SPIE/COS Photonics Asia, 2019, Hangzhou, China
Abstract
With the development and application of digital cameras, especially in education, a great number of digital video recordings are produced in classrooms. Taking Beijing Normal University as an example, 3.4 TB of videos are recorded every day in more than 200 classrooms. Such huge data is beneficial for us, computer vision researchers, to automatically recognize students' classroom actions and even evaluate the quality of classroom teaching. To focus action recognition on students, we propose Beijing Normal University Large-scale Classroom Student Action Database version 1.0(BNU-LCSAD) which is the first large-scale classroom student action database for student action recognition and consists of 10 classroom student action classes from digital camera recordings at BNU. We introduce the construct and label Processing of this database in detail. In Addition , we provide baseline of student action recognition results based our new database using C3D network.
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Bo Sun, Kaijie Zhao, Yongkang Xiao, Jun He, Lejun Yu, Yong Wu, and Huanqing Yan "BNU-LCSAD: a video database for classroom student action recognition", Proc. SPIE 11187, Optoelectronic Imaging and Multimedia Technology VI, 111871V (18 November 2019); https://doi.org/10.1117/12.2539052
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KEYWORDS
Databases
Video
Digital cameras
Digital video recorders
Computer vision technology
Machine vision
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