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Authors: Marco Cristani and Vittorio Murino

Affiliation: Università degli Studi of Verona, Italy

ISBN: 978-972-8865-74-0

Keyword(s): Background subtraction, mixture of Gaussian, video surveillance.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Tracking of People and Surveillance

Abstract: In the video surveillance literature, background (BG) subtraction is an important and fundamental issue. In this context, a consistent group of methods operates at region level, evaluating in fixed zones of interest pixel values’ statistics, so that a per-pixel foreground (FG) labeling can be performed. In this paper, we propose a novel hybrid, pixel/region, approach for background subtraction. The method, named Spatial-Time Adaptive Per Pixel Mixture Of Gaussian (S-TAPPMOG), evaluates pixel statistics considering zones of interest that change continuously over time, adopting a sampling mechanism. In this way, numerous classical BG issues can be efficiently faced: actually, it is possible to model the background information more accurately in the chromatic uniform regions exhibiting stable behavior, thus minimizing foreground camouflages. At the same time, it is possible to model successfully regions of similar color but corrupted by heavy noise, in order to minimize false FG detectio ns. Such approach, outperforming state of the art methods, is able to run in quasi-real time and it can be used at a basis for more structured background subtraction algorithms. (More)

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Paper citation in several formats:
Cristani M.; Murino V. and (2007). A SPATIAL SAMPLING MECHANISM FOR EFFECTIVE BACKGROUND SUBTRACTION.In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 403-410. DOI: 10.5220/0002058304030410

@conference{visapp07,
author={Marco Cristani and Vittorio Murino},
title={A SPATIAL SAMPLING MECHANISM FOR EFFECTIVE BACKGROUND SUBTRACTION},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={403-410},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002058304030410},
isbn={978-972-8865-74-0},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - A SPATIAL SAMPLING MECHANISM FOR EFFECTIVE BACKGROUND SUBTRACTION
SN - 978-972-8865-74-0
AU - Cristani, M.
AU - Murino, V.
PY - 2007
SP - 403
EP - 410
DO - 10.5220/0002058304030410

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