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Robust Physics-based Motion Retargeting with Realistic Body Shapes




Motion capture is often retargeted to new, and sometimes drastically different, characters. When the characters take on realistic human shapes, however, we become more sensitive to the motion looking right. This means adapting it to be consistent with the physical constraints imposed by different body shapes. We show how to take realistic 3D human shapes, approximate them using a simplified representation, and animate them so that they move realistically using physically-based retargeting. We develop a novel spacetime optimization approach that learns and robustly adapts physical controllers to new bodies and constraints. The approach automatically adapts the motion of the mocap subject to the body shape of a target subject. This motion respects the physical properties of the new body and every body shape results in a different and appropriate movement. This makes it easy to create a varied set of motions from a single mocap sequence by simply varying the characters. In an interactive environment, successful retargeting requires adapting the motion to unexpected external forces. We achieve robustness to such forces using a novel LQR-tree formulation. We show that the simulated motions look appropriate to each character’s anatomy and their actions are robust to perturbations.

Author(s): Mazen Al Borno and Ludovic Righetti and Michael J. Black and Scott L. Delp and Eugene Fiume and Javier Romero
Journal: Computer Graphics Forum
Volume: 37
Pages: 6:1--12
Year: 2018
Month: July

Department(s): Perceiving Systems
Bibtex Type: Article (article)
Paper Type: Journal

Links: pdf


  title = {Robust Physics-based Motion Retargeting with Realistic Body Shapes},
  author = {Borno, Mazen Al and Righetti, Ludovic and Black, Michael J. and Delp, Scott L. and Fiume, Eugene and Romero, Javier},
  journal = {Computer Graphics Forum},
  volume = {37},
  pages = {6:1--12},
  month = jul,
  year = {2018},
  month_numeric = {7}