Robust and incremental active contour models for object tracking

Roger A. Samy; Jean-Francois Bonnet

doi:10.1117/12.213093

5 July 1995 Robust and incremental active contour models for object tracking

Roger A. Samy, Jean-Francois Bonnet

Proceedings Volume 2485, Automatic Object Recognition V; (1995) https://doi.org/10.1117/12.213093
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Roger A. Samy and Jean-Francois Bonnet "Robust and incremental active contour models for object tracking", Proc. SPIE 2485, Automatic Object Recognition V, (5 July 1995); https://doi.org/10.1117/12.213093

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