Robust methods for background extraction in video

Autores
Bruder, Martin; Roitman, Gustavo A.; Cernuschi-Frias, Bruno
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper a framework is presented to automatically extract a sequence of images of the background of a scene from a shaky film. That is, the input video sequence may have local and global motion but the output video must contain exclusively the static background scene. Applying robust procedures to this end is one of the main goals of this work, since the aim is to get a procedure not only resistant to low scale noise but to occasional high scale noise. The median is used as an estimate of the background, the median absolute deviation (MAD) is used to establish a threshold to locate foreground and M-estimation for regression is used to stabilize the video sequence.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Background subtraction
Robust estimation
Video stabilization
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/123728
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/123728
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Robust methods for background extraction in videoBruder, MartinRoitman, Gustavo A.Cernuschi-Frias, BrunoCiencias InformáticasBackground subtractionRobust estimationVideo stabilizationIn this paper a framework is presented to automatically extract a sequence of images of the background of a scene from a shaky film. That is, the input video sequence may have local and global motion but the output video must contain exclusively the static background scene. Applying robust procedures to this end is one of the main goals of this work, since the aim is to get a procedure not only resistant to low scale noise but to occasional high scale noise. The median is used as an estimate of the background, the median absolute deviation (MAD) is used to establish a threshold to locate foreground and M-estimation for regression is used to stabilize the video sequence.Sociedad Argentina de Informática e Investigación Operativa2012-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf83-95http://sedici.unlp.edu.ar/handle/10915/123728enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/8_ASAI_2012.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:21:31Zoai:sedici.unlp.edu.ar:10915/123728Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:21:32.249SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Robust methods for background extraction in video
title Robust methods for background extraction in video
spellingShingle Robust methods for background extraction in video
Bruder, Martin
Ciencias Informáticas
Background subtraction
Robust estimation
Video stabilization
title_short Robust methods for background extraction in video
title_full Robust methods for background extraction in video
title_fullStr Robust methods for background extraction in video
title_full_unstemmed Robust methods for background extraction in video
title_sort Robust methods for background extraction in video
dc.creator.none.fl_str_mv Bruder, Martin
Roitman, Gustavo A.
Cernuschi-Frias, Bruno
author Bruder, Martin
author_facet Bruder, Martin
Roitman, Gustavo A.
Cernuschi-Frias, Bruno
author_role author
author2 Roitman, Gustavo A.
Cernuschi-Frias, Bruno
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Background subtraction
Robust estimation
Video stabilization
topic Ciencias Informáticas
Background subtraction
Robust estimation
Video stabilization
dc.description.none.fl_txt_mv In this paper a framework is presented to automatically extract a sequence of images of the background of a scene from a shaky film. That is, the input video sequence may have local and global motion but the output video must contain exclusively the static background scene. Applying robust procedures to this end is one of the main goals of this work, since the aim is to get a procedure not only resistant to low scale noise but to occasional high scale noise. The median is used as an estimate of the background, the median absolute deviation (MAD) is used to establish a threshold to locate foreground and M-estimation for regression is used to stabilize the video sequence.
Sociedad Argentina de Informática e Investigación Operativa
description In this paper a framework is presented to automatically extract a sequence of images of the background of a scene from a shaky film. That is, the input video sequence may have local and global motion but the output video must contain exclusively the static background scene. Applying robust procedures to this end is one of the main goals of this work, since the aim is to get a procedure not only resistant to low scale noise but to occasional high scale noise. The median is used as an estimate of the background, the median absolute deviation (MAD) is used to establish a threshold to locate foreground and M-estimation for regression is used to stabilize the video sequence.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/123728
url http://sedici.unlp.edu.ar/handle/10915/123728
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/8_ASAI_2012.pdf
info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
83-95
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.22299

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