Abstract
In this preliminary work, we propose a system prototype for Thai Dance training. This paper considers the problem of teaching traditional dances from Thailand. This is particularly useful given the lack of teachers and tools for teaching dances. In order to build a software tool helping people learn Thai dances, the main problems are (i) how to represent the dance gestures and movements of the dance to teach, (ii) how to display it for the learner and how to rate the performance of the learner and provide him useful feedback. Fortunately, Natural User Interfaces (NUI) enables users to interact with a system in a natural and intuitive way. For instance, a user can interact with the system by his body through postures and movements. In this study, we developed a working prototype of a system teaching users traditional Thai dances. The system requires Kinect-based device to enable real-time skeleton tracking. For the reference postures/movements dataset, we collected dance movement from experts by Motion Capture System and used the collected data to represent the dance in the system. Moreover, the system is designed such that it rates the user’s performance and provides helpful and real-time feedback to the user.
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Muangmoon, Oo., Sureephong, P., Tabia, K. (2017). Dance Training Tool Using Kinect-Based Skeleton Tracking and Evaluating Dancer’s Performance. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10351. Springer, Cham. https://doi.org/10.1007/978-3-319-60045-1_4
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DOI: https://doi.org/10.1007/978-3-319-60045-1_4
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