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Journal of Electronic Imaging

Projection model snakes for tracking using a Monte Carlo approach
Author(s): Michael E. Welser; Scott Thomas Acton
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Paper Abstract

We propose a method that uses projection models in conjunction with a sequential Monte Carlo approach to track rigid targets. We specifically address the problems associated with tracking objects in scenarios characterized by cluttered images and high variability in target scale. The projection model snake is introduced in order to track a target boundary over a variety of scales by geometrically transforming the boundary to account for three-dimensional relative motion between the target and camera. The complete solution is a potent synergism of the projection model snake and a sequential Monte Carlo method. The projection model Monte Carlo method randomly generates the parameters of target motion and pose from empirically derived distributions. The resultant "particles" are then weighted according to a likelihood determined by the integration of the mean gradient magnitude around the target contour, yielding the expected target path and pose. We demonstrate the effectiveness of this approach for tracking dynamic targets in sequences with noise, clutter, occlusion, and scale variability.

Paper Details

Date Published: 1 April 2004
PDF: 15 pages
J. Electron. Imag. 13(2) doi: 10.1117/1.1687732
Published in: Journal of Electronic Imaging Volume 13, Issue 2
Show Author Affiliations
Michael E. Welser, Univ. of Virginia (United States)
Scott Thomas Acton, Univ. of Virginia (United States)


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