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초록

Human dance is difficult to learn since there is no effective way to imitate an expert’s motion, a sequence of complicated body movements, without taking an actual class. In this paper, we propose a dance learning system using human depth information. In the proposed system, a set of example motions are captured from various expert dancers through a marker-free motion capture and archived into a motion database server for online dance lessons. Given the end-user devices such as tablet and kiosk PCs, a student can learn a desired motion selected from the database and send one’s own motion to an instructor for online feedback. During this learning process, our system provides a posture-based motion search and multi-mode views to support the efficient exchange of motion data between the student and instructor under a networked environment. The experimental results demonstrate that our system is capable to improve the student’s dance skills over a given period of time.

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