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Authors: Oleg Granichin ; Lev Gurevich and Alexander Vakhitov

Affiliation: St. Petersburg State University, Russian Federation

Abstract: An application of simultaneous perturbation stochastic approximation (SPSA) algorithm with two measurements per iteration to the problem of object tracking on video is discussed. The upper bound of mean square estimation error is determined in case of once differentiable functional and almost arbitrary noises. Weak restrictions on uncertainty allow to use random sampling instead of full pixelwise difference calculation. The experiments show significant increase in performance of object tracking comparing to the classical Lucas-Kanade algorithm. The results can be generalized to improve more recent kernel-based tracking methods.

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Paper citation in several formats:
Granichin, O.; Gurevich, L. and Vakhitov, A. (2009). Minimum Tracking with SPSA and Applications to Image Registration. In Proceedings of the International Workshop on Networked embedded and control system technologies: European and Russian R&D cooperation (ICINCO 2009) - Workshop NESTER; ISBN 978-989-674-004-7, SciTePress, pages 66-74. DOI: 10.5220/0002271300660074

@conference{workshop nester09,
author={Oleg Granichin. and Lev Gurevich. and Alexander Vakhitov.},
title={Minimum Tracking with SPSA and Applications to Image Registration},
booktitle={Proceedings of the International Workshop on Networked embedded and control system technologies: European and Russian R&D cooperation (ICINCO 2009) - Workshop NESTER},
year={2009},
pages={66-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002271300660074},
isbn={978-989-674-004-7},
}

TY - CONF

JO - Proceedings of the International Workshop on Networked embedded and control system technologies: European and Russian R&D cooperation (ICINCO 2009) - Workshop NESTER
TI - Minimum Tracking with SPSA and Applications to Image Registration
SN - 978-989-674-004-7
AU - Granichin, O.
AU - Gurevich, L.
AU - Vakhitov, A.
PY - 2009
SP - 66
EP - 74
DO - 10.5220/0002271300660074
PB - SciTePress