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3D Tracking of Human Locomotion: a Tracking as Recognition Approach

Tao Zhao and Ram Nevatia
{taozhao|nevatia} (at) iris (o) usc (o) edu
ICPR 2002 (International Conference on Pattern Recognition), Quebec city, Quebec, Canada, Aug., 2002.

Abstract

Estimating mode (walking/running/standing) and phases of human locomotion is important for video understanding. We present a new ˇ±tracking as recognitionˇ± 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.

First level of the locomotion model
Second level of the locomotion model

Result A:
AVI video for the sequence (MPEG4).

Result B:

AVI video for the sequence (MPEG4).
* The orientations when the human is standing are not estimated reliably.

Pose rendered from new viewpoints:

Download PDF file of the paper.