Mode-based multi-hypothesis tracking using parametric contours

Details Mode-based multi-hypothesis tracking using parametric contours Mode-based multi-hypothesis tracking using parametric contours

2007-06-12

2007-06-12

Bella, Matthew C. (Department: 2624)

Image analysis

Applications

Target tracking or detecting

Reexamination Certificate

active

11282365

ABSTRACT:
A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.

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patent: 6826292 (2004-11-01), Tao et al.
patent: 6999599 (2006-02-01), Rui et al.

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