Quantifying the grace of motion based on S-shaped features of hand trajectory
Yuki Inazu, Etsuko Ueda · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2020
This research focuses on “gracefulness” and aim for the extraction and modeling of the graceful motion feature using classical dance. We are performing grace feature extraction by extracting S-shaped curves from hand trajectories. We considered that the S-shaped trajectories due to hand trajectories include both those created by changes in position and orientation of dancers and those created by the dancer’s arm movements. In this paper, we report on the grace features extraction by converting motion data acquired by motion capture into data in which only limbs move, and extracting frames in which arms move. We compared the correlation between hand trajectory shapes of motion data acquired by motion capture and motion data moving the arms, and impression evaluation results. As a result, we showed that using only the motion of moving the arm resulted in feature quantity that matched impression evaluations.