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Proceedings Paper

Robust and incremental active contour models for object tracking
Author(s): Roger A. Samy; Jean-Francois Bonnet
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Paper Abstract

This paper addresses object tracking problems in an image sequence using an active contour model called '(rho) -snake'. This model is the result of the combination of classical snakes and elements from the robust estimators theory. Snakes are energy-minimizing curves with global constraints that segment deforming shapes. The theory of robust estimators provides a framework that makes parameter estimation free from outliers. We have introduced (rho) - snakes to use these two techniques to achieve a goal: tracking a moving shape along an image sequence without being influenced by erroneous information of images. Attempting to imporve this new technique, we present parallel processing and a faster way of implementing (rho) - snakes. We also have defined robust energies, both spatial and temporal. As these energies include prediction, they fit our problem: tracking poor contrasted and fast moving object in a noisy IR sequence.

Paper Details

Date Published: 5 July 1995
PDF: 10 pages
Proc. SPIE 2485, Automatic Object Recognition V, (5 July 1995); doi: 10.1117/12.213093
Show Author Affiliations
Roger A. Samy, Societe Anonyme de Telecommunications (France)
Jean-Francois Bonnet, Societe Anonyme de Telecommunications (France)
Univ. Rene Descarte (France)

Published in SPIE Proceedings Vol. 2485:
Automatic Object Recognition V
Firooz A. Sadjadi, Editor(s)

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