Probabilistic exemplar-based pattern tracking

Details Probabilistic exemplar-based pattern tracking Probabilistic exemplar-based pattern tracking

2007-01-23

2007-01-23

Mehta, Bhavesh M. (Department: 2624)

Image analysis

Applications

Target tracking or detecting

C382S225000, C382S228000

Reexamination Certificate

active

11298798

ABSTRACT:
The present invention involves a new system and method for probabilistic exemplar-based tracking of patterns or objects. Tracking is accomplished by first extracting a set of exemplars from training data. The exemplars are then clustered using conventional statistical techniques. Such clustering techniques include k-medoids clustering which is based on a distance function for determining the distance or similarity between the exemplars. A dimensionality for each exemplar cluster is then estimated and used for generating a probabilistic likelihood function for each exemplar cluster. Any of a number of conventional tracking algorithms is then used in combination with the exemplars and the probabilistic likelihood functions for tracking patterns or objects in a sequence of images, or in a space, or frequency domain.

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