Exploiting multiple cues in motion segmentation based on background subtraction

This paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motion segmentation. In our first contribution, a case analysis of motion segmentation errors is presented taking into acco...

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Detalles Bibliográficos
Autores: Huerta Casado, Iván, Amato, Ariel, Roca Marva, Francesc Xavier, González, Jordi
Tipo de recurso: artículo
Fecha de publicación:2013
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/17494
Acceso en línea:https://hdl.handle.net/2117/17494
https://dx.doi.org/10.1016/j.neucom.2011.10.036
Access Level:acceso abierto
Palabra clave:Computer vision
Motion segmentation
Shadow segmentation
Visió per ordinador
Imatge -- Processament -- Tècniques digitals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Agents intel·ligents
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oai_identifier_str oai:upcommons.upc.edu:2117/17494
network_acronym_str ES
network_name_str España
repository_id_str
spelling Exploiting multiple cues in motion segmentation based on background subtractionHuerta Casado, IvánAmato, ArielRoca Marva, Francesc XavierGonzález, JordiComputer visionMotion segmentationShadow segmentationVisió per ordinadorImatge -- Processament -- Tècniques digitalsÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Agents intel·ligentsThis paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motion segmentation. In our first contribution, a case analysis of motion segmentation errors is presented taking into account the inaccuracies associated with different cues, namely colour, edge and intensity. Our second contribution is an hybrid architecture which copes with the main issues observed in the case analysis by fusing the knowledge from the aforementioned three cues and a temporal difference algorithm. On one hand, we enhance the colour and edge models to solve not only global and local illumination changes (i.e. shadows and highlights) but also the camouflage in intensity. In addition, local information is also exploited to solve the camouflage in chroma. On the other hand, the intensity cue is applied when colour and edge cues are not available because their values are beyond the dynamic range. Additionally, temporal difference scheme is included to segment motion where those three cues can not be reliably computed, for example in those background regions not visible during the training period. Lastly, our approach is extended for handling ghost detection. The proposed method obtains very accurate and robust motion segmentation results in multiple indoor and outdoor scenarios, while outperforming the most-referred state-of-art approaches.Peer Reviewed20132013-01-0120132013-01-23journal articlehttp://purl.org/coar/resource_type/c_6501AOhttp://purl.org/coar/version/c_b1a7d7d4d402bcceinfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/17494https://dx.doi.org/10.1016/j.neucom.2011.10.036reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/174942026-05-27T15:37:01Z
dc.title.none.fl_str_mv Exploiting multiple cues in motion segmentation based on background subtraction
title Exploiting multiple cues in motion segmentation based on background subtraction
spellingShingle Exploiting multiple cues in motion segmentation based on background subtraction
Huerta Casado, Iván
Computer vision
Motion segmentation
Shadow segmentation
Visió per ordinador
Imatge -- Processament -- Tècniques digitals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Agents intel·ligents
title_short Exploiting multiple cues in motion segmentation based on background subtraction
title_full Exploiting multiple cues in motion segmentation based on background subtraction
title_fullStr Exploiting multiple cues in motion segmentation based on background subtraction
title_full_unstemmed Exploiting multiple cues in motion segmentation based on background subtraction
title_sort Exploiting multiple cues in motion segmentation based on background subtraction
dc.creator.none.fl_str_mv Huerta Casado, Iván
Amato, Ariel
Roca Marva, Francesc Xavier
González, Jordi
author Huerta Casado, Iván
author_facet Huerta Casado, Iván
Amato, Ariel
Roca Marva, Francesc Xavier
González, Jordi
author_role author
author2 Amato, Ariel
Roca Marva, Francesc Xavier
González, Jordi
author2_role author
author
author
dc.subject.none.fl_str_mv Computer vision
Motion segmentation
Shadow segmentation
Visió per ordinador
Imatge -- Processament -- Tècniques digitals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Agents intel·ligents
topic Computer vision
Motion segmentation
Shadow segmentation
Visió per ordinador
Imatge -- Processament -- Tècniques digitals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Agents intel·ligents
description This paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motion segmentation. In our first contribution, a case analysis of motion segmentation errors is presented taking into account the inaccuracies associated with different cues, namely colour, edge and intensity. Our second contribution is an hybrid architecture which copes with the main issues observed in the case analysis by fusing the knowledge from the aforementioned three cues and a temporal difference algorithm. On one hand, we enhance the colour and edge models to solve not only global and local illumination changes (i.e. shadows and highlights) but also the camouflage in intensity. In addition, local information is also exploited to solve the camouflage in chroma. On the other hand, the intensity cue is applied when colour and edge cues are not available because their values are beyond the dynamic range. Additionally, temporal difference scheme is included to segment motion where those three cues can not be reliably computed, for example in those background regions not visible during the training period. Lastly, our approach is extended for handling ghost detection. The proposed method obtains very accurate and robust motion segmentation results in multiple indoor and outdoor scenarios, while outperforming the most-referred state-of-art approaches.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01
2013
2013-01-23
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AO
http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/17494
https://dx.doi.org/10.1016/j.neucom.2011.10.036
url https://hdl.handle.net/2117/17494
https://dx.doi.org/10.1016/j.neucom.2011.10.036
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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