Abstract

Motion capture is prevalent in the pipeline of realistic articulated character animation. To define accurate joint positions and joint orientations for the movement of a hierarchical human-like character without using a re-defined skeleton remains a challenge for motion capture studios. In this paper, we present a method for automatically estimating and determining the topology of a hierarchical human skeleton from optical motion capture data based on the human biomechanical information. Through the use of a novel per-frame based recursive method with joint angle minimization, human skeleton mapping from optical markers and joint angle estimation are achieved in real time.