AN AUTOMATIC APPROACH FOR PARAMETER SELECTION IN SELF-ADAPTIVE TRACKING

Daniela Hall, Rémi Emonet, James L. Crowley

2006

Abstract

In this article we propose an automatic approach for parameter selection of a tracking system. We show that such a self-adaptive tracking system achieves better tracking performance than a system with manually tuned parameters. Our approach requires little supervision by a user which makes this approach ideally suited for commercial applications. The self-adaptive component makes the system less sensitive to changing environmental conditions. Components for tracking, auto-critical evaluation and automatic parameter regulation serve to detect performance drops that trigger the parameter regulation process. The self-adaptive components require a quality measure based on a statistical scene reference model. We propose an automatic approach for the generation of such a reference model and compare several learning approaches. The experiments show that the auto-regulation of parameters significantly enhances the performance of the tracking system.

References

  1. Caporossi, A., Hall, D., Reignier, P., and Crowley, J. (2004). Robust visual tracking from dynamic control
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Paper Citation


in Harvard Style

Hall D., Emonet R. and L. Crowley J. (2006). AN AUTOMATIC APPROACH FOR PARAMETER SELECTION IN SELF-ADAPTIVE TRACKING . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 20-26. DOI: 10.5220/0001372600200026


in Bibtex Style

@conference{visapp06,
author={Daniela Hall and Rémi Emonet and James L. Crowley},
title={AN AUTOMATIC APPROACH FOR PARAMETER SELECTION IN SELF-ADAPTIVE TRACKING},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={20-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001372600200026},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - AN AUTOMATIC APPROACH FOR PARAMETER SELECTION IN SELF-ADAPTIVE TRACKING
SN - 972-8865-40-6
AU - Hall D.
AU - Emonet R.
AU - L. Crowley J.
PY - 2006
SP - 20
EP - 26
DO - 10.5220/0001372600200026