Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation

Depth inclusion as an important parameter for dynamic selective visual attention is presented in this article. The model introduced in this paper is based on two previously developed models, dynamic selective visual attention and visual stereoscopy, giving rise to the so-called dynamic stereoscopic...

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Detalles Bibliográficos
Autores: López Bonal, María Teresa, Fernández Caballero, Antonio, Saiz Valverde, Sergio
Tipo de recurso: artículo
Fecha de publicación:2008
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/2091
Acceso en línea:http://hdl.handle.net/10578/2091
Access Level:acceso abierto
Palabra clave:Ingenierías
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spelling Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentationLópez Bonal, María TeresaFernández Caballero, AntonioSaiz Valverde, SergioIngenieríasDepth inclusion as an important parameter for dynamic selective visual attention is presented in this article. The model introduced in this paper is based on two previously developed models, dynamic selective visual attention and visual stereoscopy, giving rise to the so-called dynamic stereoscopic selective visual attention method. The three models are based on the accumulative computation problem-solving method. This paper shows how software reusability enables enhancing results in vision research (video segmentation) by integrating earlier works. In this article, the first results obtained for synthetic sequences are included to show the effectiveness of the integration of motion and shape features with depth parameter in video segmentation.201220122008info:eu-repo/semantics/articletext/plainapplication/pdfhttp://hdl.handle.net/10578/2091reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaEspañolinfo:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/20912026-05-27T07:36:41Z
dc.title.none.fl_str_mv Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
title Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
spellingShingle Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
López Bonal, María Teresa
Ingenierías
title_short Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
title_full Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
title_fullStr Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
title_full_unstemmed Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
title_sort Dynamic stereoscopic selective visual attention (dssva): integrating motion and shape with depth in video segmentation
dc.creator.none.fl_str_mv López Bonal, María Teresa
Fernández Caballero, Antonio
Saiz Valverde, Sergio
author López Bonal, María Teresa
author_facet López Bonal, María Teresa
Fernández Caballero, Antonio
Saiz Valverde, Sergio
author_role author
author2 Fernández Caballero, Antonio
Saiz Valverde, Sergio
author2_role author
author
dc.subject.none.fl_str_mv Ingenierías
topic Ingenierías
description Depth inclusion as an important parameter for dynamic selective visual attention is presented in this article. The model introduced in this paper is based on two previously developed models, dynamic selective visual attention and visual stereoscopy, giving rise to the so-called dynamic stereoscopic selective visual attention method. The three models are based on the accumulative computation problem-solving method. This paper shows how software reusability enables enhancing results in vision research (video segmentation) by integrating earlier works. In this article, the first results obtained for synthetic sequences are included to show the effectiveness of the integration of motion and shape features with depth parameter in video segmentation.
publishDate 2008
dc.date.none.fl_str_mv 2008
2012
2012
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10578/2091
url http://hdl.handle.net/10578/2091
dc.language.none.fl_str_mv Español
language_invalid_str_mv Español
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/plain
application/pdf
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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