Motion and interaction with the environment are fundamentally
intertwined. Few people-tracking algorithms exploit
such interactions, and those that do assume that surface
geometry and dynamics are given. This paper concerns
the converse problem, i.e., the inference of contact and environment
properties from motion. For 3D human motion,
with a 12-segment articulated body model, we show how
one can estimate the forces acting on the body in terms
of internal forces (joint torques), gravity, and the parameters
of a contact model (e.g., the geometry and dynamics
of a spring-based model). This is tested on motion capture
data and video-based tracking data, with walking, jogging,
cartwheels, and jumping.
Marcus A. Brubaker Leonid Sigal David J. Fleet