Still and Video Image Analysis

Projection model snakes for tracking using a Monte Carlo approach

[+] Author Affiliations
Michael E. Welser, Scott T. Acton

Virginia Image and Video Analysis (VIVA), Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia?22904 E-mail: acton@virginia.edu

J. Electron. Imaging. 13(2), 384-398 (Apr 01, 2004). doi:10.1117/1.1687732
History: Received May 28, 2003; Revised October 7, 2003; Accepted October 23, 2003; Online April 01, 2004
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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. © 2004 SPIE and IS&T.

© 2004 SPIE and IS&T

Citation

Michael E. Welser and Scott T. Acton
"Projection model snakes for tracking using a Monte Carlo approach", J. Electron. Imaging. 13(2), 384-398 (Apr 01, 2004). ; http://dx.doi.org/10.1117/1.1687732


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