Worawat Choensawat

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This paper aims at description and reproduction of the body motion of stylized traditional dances by using fundamental elements of Labanotation while keeping the quality of body movement of CG character animation. We propose and implement a dynamic template technique enabling users to notate stylized traditional dances and reproducing it in 3D CG animation(More)
This paper presents a full-body motion-control game interface based on a Kinect device. A set of postures and motions for controlling game characters is presented, and the posture-detection algorithm for each posture is implemented by using a rule-based technique with rule-and-threshold optimization. Our experiments show that the proposed optimization can(More)
This paper presents a computer-aided tool for automatically generating Labanotation scores from motion capture data named GenLaban. GenLaban can be implemented with a low-cost equipment but an efficient method that allows users converting body motions to scores. The key components of GenLaban are the analysis of body motions, the quantization of body(More)
The recent East Asian economic crisis is a lesson one can learn from the absence of effective early warning systems. To serve as a sound early warning signal, the accuracy of a failure prediction model is as important as its robustness over time. This study analyses financial and ownership variables using principal component analysis. It can reduce huge(More)
Labanotation [Hutchinson, 2005] is a graphical notation scheme for describing human body movement that has been widely accepted for the purpose of recording human movements in the fields of choreography and dance education, mainly in Western dance communities. Labanotation is rich in symbols, and by using the full set of symbol s almost all of our body(More)
The purpose of this research is to show movement characteristics of bodies during dance performance. We examined bodily characteristics of dancers when moving and conforming to other dancers. Specifically, we analyzed paired dancer movements through motion capture and compared all body-part characteristics based on data derived from cross-correlation(More)