4D human body posture estimation based on a motion capture system and a multi-rigid link model

Human motion analysis in various fields such as neurophysiology, clinical medicine, and sports sciences utilizes a multi-rigid link model of a human body for considering kinetics by solving inverse dynamics of a motion, in which a motion capture system with reflective markers are often used to measure the motion, and then the obtained motion are mapped onto the multi-rigid link model. However, algorithms for such a mapping from spatio-temporal positions of the markers to the corresponding posture of the model are not always fully disclosed. Moreover, a common difficulty for such algorithms is an error caused by displacements of the markers attached on the body surface, referred to as the skin motion error. In this study, we developed a simple algorithm that maps positions of the markers to the corresponding posture of a rigid link model, and examined accuracy of the algorithm by evaluating quantitatively differences between the measured and the estimated posture. We also analyzed the skin motion error. It is shown that magnitude of the error was determined not only by the amplitude of the skin motion, but also by the direction of the marker displacement relative to the frame of reference attached to each segment of the body.