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Authors: J. M. Berthommé ; T. Chateau and M. Dhome

Affiliation: LASMEA, France

ISBN: 978-989-8565-04-4

Keyword(s): Kernel Selection, Information Theory, Nonparametric Tracking.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Motion, Tracking and Stereo Vision ; Tracking and Visual Navigation

Abstract: This paper presents a method to select kernels for the subsampling of nonparametric models used in realtime object tracking in video streams. We propose a method based on mutual information, inspired by the CMIM algorithm (Fleuret, 2004) for the selection of binary features. This builds, incrementally, a model of appearance of the object to follow, based on representative and independant kernels taken from points of that object. Experiments show gains, in terms of accuracy, compared to other sampling strategies.

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Paper citation in several formats:
M. Berthommé, J.; Chateau, T. and Dhome, M. (2012). KERNEL SELECTION BY MUTUAL INFORMATION FOR NONPARAMETRIC OBJECT TRACKING.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 373-376. DOI: 10.5220/0003833603730376

@conference{visapp12,
author={J. M. Berthommé. and T. Chateau. and M. Dhome.},
title={KERNEL SELECTION BY MUTUAL INFORMATION FOR NONPARAMETRIC OBJECT TRACKING},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={373-376},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003833603730376},
isbn={978-989-8565-04-4},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - KERNEL SELECTION BY MUTUAL INFORMATION FOR NONPARAMETRIC OBJECT TRACKING
SN - 978-989-8565-04-4
AU - M. Berthommé, J.
AU - Chateau, T.
AU - Dhome, M.
PY - 2012
SP - 373
EP - 376
DO - 10.5220/0003833603730376

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