An Adaptive Fusion Architecture for Target Tracking

Authors:
Gareth Loy;Luke Fletcher;Nicholas Apostoloff;Alexander Zelinsky
Affiliations:
-;-;-;-
Venue:
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Year:
2002

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Abstract

A vision system is demonstrated that adaptively allocates computational resources over multiple cues to robustly track a target in 3D. The system uses a particle filter to maintain multiple hypotheses of the target location. Bayesian probability theory provides the framework for sensor fusion, and resource scheduling is used to intelli-gently allocate the limited computational resources available across the suite of cues. The system is shown to track a person in 3D space moving in a cluttered environment.