Human modeling and real-time motion reconstruction for micro-sensor motion capture

With the rapid advancement of micro-sensor motion capture, human modeling and motion reconstruction in realtime have become more and more important. The human model must be accurate enough for representing motions but also simple to realize real-time application. In this paper, we build a human model for micro-sensor motion capture (MMocap) and reconstruct 3D human motion using data from MMocap in real-time. The human model is composed of bones and joints, driven by motion parameters from micro-sensor motion capture, resulting in the real-time 3D motion animation. The motion parameters include quaternion and position of each bone. Quaternions are used to represent orientation of bones. Positions are calculated from forward kinematics. The experimental results have shown that the proposed human model is of good fidelity and low delay for real-time micro-sensor data-driven motion capture.