Robust Physics-based Motion Retargeting with Realistic Body Shapes

Mazen Al Borno, Ludovic Righetti, Michael J. Black, Scott L. Delp, Eugene Fiume, Javier Romero

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)81-92
Number of pages12
JournalComputer Graphics Forum
Issue number8
StatePublished - Dec 2018


  • CCS Concepts
  • Physical simulation
  • •Computing methodologies → Animation

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design


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