Generating natural hand motion in playing a piano

Generating natural motion of an articulated object with higher DOF (e.g., humanoid robot and robot hand) is a crucial issue in robotics and computer graphics fields. Use of the motion capture data is one of the solutions, but it requires expensive device and time-consuming measurement. In this paper, we propose a method for generating natural hand motion to play a piano from the inputted music score. The proposed method uses inverse kinematics while considering naturalness of hand poses. We revisit background of the inverse kinematics based on the maximum likelihood estimation and use the prior model of the hand pose to achieve the naturalness. We evaluate the effectiveness of the proposed method using voluntary survey.