Chiung-Yao Fang, Min-Han Kuo, Greg-C Lee, and Sei-Wang Chen
Smart classroom, gesture recognition, object segmentation
This paper presents a student gesture recognition system employed in a theatre classroom, which is a subsystem belonging to Classroom 2.0. In this study, a PTZ camera is set up at the front of the classroom to capture video sequences. The system first pre-processes the input sequence to locate the main line of the theatre classroom and to extract the candidates from the foreground pixels. Subsequently, motion and color information is utilized to identify the foreground pixels, which are regarded as the seeds of growth for the foreground regions. The system combines the foreground regions to segment the objects, which represent individual students. Six student gestures, which include raising the right hand, raising the left hand, raising two hands, lying prone, standing up and normal, are classified based on the relationship between the regions in similar objects. The experimental results demonstrate that the proposed method is robust and efficient.
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