KEYWORDS: Action recognition, Video, 3D image processing, Deep learning, Machine learning, Feature extraction, Education and training, Analytical research
Classroom action recognition is a hot research in educational teaching environment combined with artificial intelligence technology, through which action recognition can quantify students' concentration in classroom. In this study, we propose an advanced 3D and 2D branching fusion action recognition model for recognizing students' actions in the classroom environment. The experimental results show that the classroom action recognition model has high accuracy and speed, and can accurately and quickly identify specific high-frequency classroom actions, which can then be effectively used for students' classroom concentration analysis. Accurate identification of students' classroom actions and quantification of their classroom attention can not only provide reference for teachers of relevant courses, but also provide data support for teaching quality assessment at school level, ultimately helping to improve the quality of classroom teaching.
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