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Authors: Daniela Hall ; Rémi Emonet and James L. Crowley

Affiliation: INRIA Rhône-Alpes, France

Keyword(s): Tracking, performance optimization, automatic parameter regulation.

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.

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Paper citation in several formats:
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 (VISIGRAPP 2006) - Volume 2: VISAPP; ISBN 972-8865-40-6; ISSN 2184-4321, SciTePress, pages 20-26. DOI: 10.5220/0001372600200026

@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 (VISIGRAPP 2006) - Volume 2: VISAPP},
year={2006},
pages={20-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001372600200026},
isbn={972-8865-40-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP
TI - AN AUTOMATIC APPROACH FOR PARAMETER SELECTION IN SELF-ADAPTIVE TRACKING
SN - 972-8865-40-6
IS - 2184-4321
AU - Hall, D.
AU - Emonet, R.
AU - L. Crowley, J.
PY - 2006
SP - 20
EP - 26
DO - 10.5220/0001372600200026
PB - SciTePress