Online Motion Synthesis Framework using a Simple Mass Model based on Predictive Coding

Abstract

Hybrid-based character animation utilizing the motion capture data and a simplified physics model allows synthesizing the motion data without losing its naturalness of the original motion. However, using both the physical model and the motion data requires professional insights, experiences, and extra efforts such as preprocessing or off-line optimization. To handle the issue, we propose a new type of motion synthesis framework. The proposed framework combines multiple information sources that generate the reference motion based on the motion capture data and physical constraints based on the physical model. To verify the proposed framework, we define a mass-spring model to represent each skeletal joint of a human character model along with a small amount of motion capture data, a human walking motion.