Towards bridging the gap between motion capturing and biomechanical optimal control simulations
Tobias Gail, Ramona Hoffmann, Markus Miezal, Gabriele Bleser, Sigrid Leyendecker
Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics ECCOMAS Thematic Conference on Multibody Dynamics, June 29 - July 2, Barcelona, Spain

Abstract:

Within this work, we make a first attempt towards improving human motion capture by combining motion capturing measurements and optimal control simulations of a human steering motion. We start with measurements obtained from a stationary optical system, a widespread capturing technology in biomechanics and movement science, under laboratory conditions. From an optimal control point of view, the goal is to increase the realism of simulated human motion through measurements. From a motion capturing point of view, the goal is to compensate for measurement sparsity, errors or lacks through meaningful assumptions based on biomechanical simulation. Our preliminary results show that a fusion of physical laws, biomechanical simulation and real data within an optimal control simulation framework indeed have the potential to improve motion capture and synthesis with respect to some of their inherent problems.

Keywords:

optimal control simulation, optical motion capture, soft tissue artefacts, measurement sparsity

Towards bridging the gap between motion capturing and biomechanical optimal control simulations
(Hrsg.)
Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics ECCOMAS Thematic Conference on Multibody Dynamics, June 29 - July 2, Barcelona, Spain

Abstract:

Within this work, we make a first attempt towards improving human motion capture by combining motion capturing measurements and optimal control simulations of a human steering motion. We start with measurements obtained from a stationary optical system, a widespread capturing technology in biomechanics and movement science, under laboratory conditions. From an optimal control point of view, the goal is to increase the realism of simulated human motion through measurements. From a motion capturing point of view, the goal is to compensate for measurement sparsity, errors or lacks through meaningful assumptions based on biomechanical simulation. Our preliminary results show that a fusion of physical laws, biomechanical simulation and real data within an optimal control simulation framework indeed have the potential to improve motion capture and synthesis with respect to some of their inherent problems.

Keywords:

optimal control simulation, optical motion capture, soft tissue artefacts, measurement sparsity