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A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm

This paper presents a region-based method for background subtraction. It relies on color histograms, texture information, and successive division of candidate rectangular image regions to model the background and detect motion. Our proposed algorithm uses this principle and combines it with Gaussian...

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Detalles Bibliográficos
Autores principales: Varcheie, Parisa Darvish Zadeh, Sills-Lavoie, Michael, Bilodeau, Guillaume-Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3244003/
https://www.ncbi.nlm.nih.gov/pubmed/22205857
http://dx.doi.org/10.3390/s100201041
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author Varcheie, Parisa Darvish Zadeh
Sills-Lavoie, Michael
Bilodeau, Guillaume-Alexandre
author_facet Varcheie, Parisa Darvish Zadeh
Sills-Lavoie, Michael
Bilodeau, Guillaume-Alexandre
author_sort Varcheie, Parisa Darvish Zadeh
collection PubMed
description This paper presents a region-based method for background subtraction. It relies on color histograms, texture information, and successive division of candidate rectangular image regions to model the background and detect motion. Our proposed algorithm uses this principle and combines it with Gaussian Mixture background modeling to produce a new method which outperforms the classic Gaussian Mixture background subtraction method. Our method has the advantages of filtering noise during image differentiation and providing a selectable level of detail for the contour of the moving shapes. The algorithm is tested on various video sequences and is shown to outperform state-of-the-art background subtraction methods.
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spelling pubmed-32440032011-12-28 A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm Varcheie, Parisa Darvish Zadeh Sills-Lavoie, Michael Bilodeau, Guillaume-Alexandre Sensors (Basel) Article This paper presents a region-based method for background subtraction. It relies on color histograms, texture information, and successive division of candidate rectangular image regions to model the background and detect motion. Our proposed algorithm uses this principle and combines it with Gaussian Mixture background modeling to produce a new method which outperforms the classic Gaussian Mixture background subtraction method. Our method has the advantages of filtering noise during image differentiation and providing a selectable level of detail for the contour of the moving shapes. The algorithm is tested on various video sequences and is shown to outperform state-of-the-art background subtraction methods. Molecular Diversity Preservation International (MDPI) 2010-01-28 /pmc/articles/PMC3244003/ /pubmed/22205857 http://dx.doi.org/10.3390/s100201041 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Varcheie, Parisa Darvish Zadeh
Sills-Lavoie, Michael
Bilodeau, Guillaume-Alexandre
A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title_full A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title_fullStr A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title_full_unstemmed A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title_short A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm
title_sort multiscale region-based motion detection and background subtraction algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3244003/
https://www.ncbi.nlm.nih.gov/pubmed/22205857
http://dx.doi.org/10.3390/s100201041
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