3D Tracking of Human Locomotion: A Tracking as Recognition Approach (ICPR 2002)
Abstract
Estimating mode (walking/running/standi) and phases of human locomotion is
impertant for video understanding. We present a new "tracking as
recognition" approach. A hierarchical finite state machine constructed
from 3D motion capture data serves as a prior motion model. Motion
templates are used as the observation model. Robustness is achieved by
making inferences in the prior motion model which resolves the short-term
ambiguity of the observations that may cause a regular tracking
formulation to fail. Experiments show very promising results on some
difficult sequences.
Maintained by
Philippos Mordohai