Extraction of semantic objects from still images

Pardo, Alvaro

Resumen:

In this work, we study the extraction of semantic objects from still images. We combine different ideas to extract them in a structured manner together with a perceptual metric that ranks them according with its perceptual relevance. The algorithm has four steps, the regularization of the initial segmentation using probability diffusion [1], simplification of the segmentation via region merging, computation of the perceptual metric based on [2] and construction of the structure that represents the image (the binary partition tree [3]).


Detalles Bibliográficos
2002
Image segmentation
Feature extraction
Still images
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/21219
Acceso abierto
Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
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author Pardo, Alvaro
author_facet Pardo, Alvaro
author_role author
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collection COLIBRI
dc.creator.none.fl_str_mv Pardo, Alvaro
dc.date.accessioned.none.fl_str_mv 2019-07-03T16:36:04Z
dc.date.available.none.fl_str_mv 2019-07-03T16:36:04Z
dc.date.issued.es.fl_str_mv 2002
dc.date.submitted.es.fl_str_mv 20190703
dc.description.abstract.none.fl_txt_mv In this work, we study the extraction of semantic objects from still images. We combine different ideas to extract them in a structured manner together with a perceptual metric that ranks them according with its perceptual relevance. The algorithm has four steps, the regularization of the initial segmentation using probability diffusion [1], simplification of the segmentation via region merging, computation of the perceptual metric based on [2] and construction of the structure that represents the image (the binary partition tree [3]).
dc.description.es.fl_txt_mv Postprint
dc.identifier.citation.es.fl_str_mv Pardo, A. Extraction of semantic objects from still images [en línea] International Conference on Image Processing, 2002. doi 10.1109/ICIP.2002.1038966
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/21219
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv IEEE
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Image segmentation
Feature extraction
Still images
dc.title.none.fl_str_mv Extraction of semantic objects from still images
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
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description Postprint
eu_rights_str_mv openAccess
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identifier_str_mv Pardo, A. Extraction of semantic objects from still images [en línea] International Conference on Image Processing, 2002. doi 10.1109/ICIP.2002.1038966
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
network_name_str COLIBRI
oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/21219
publishDate 2002
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
spelling 2019-07-03T16:36:04Z2019-07-03T16:36:04Z200220190703Pardo, A. Extraction of semantic objects from still images [en línea] International Conference on Image Processing, 2002. doi 10.1109/ICIP.2002.1038966https://hdl.handle.net/20.500.12008/21219PostprintIn this work, we study the extraction of semantic objects from still images. We combine different ideas to extract them in a structured manner together with a perceptual metric that ranks them according with its perceptual relevance. The algorithm has four steps, the regularization of the initial segmentation using probability diffusion [1], simplification of the segmentation via region merging, computation of the perceptual metric based on [2] and construction of the structure that represents the image (the binary partition tree [3]).Made available in DSpace on 2019-07-03T16:36:04Z (GMT). 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- Universidad de la Repúblicafalse
spellingShingle Extraction of semantic objects from still images
Pardo, Alvaro
Image segmentation
Feature extraction
Still images
status_str publishedVersion
title Extraction of semantic objects from still images
title_full Extraction of semantic objects from still images
title_fullStr Extraction of semantic objects from still images
title_full_unstemmed Extraction of semantic objects from still images
title_short Extraction of semantic objects from still images
title_sort Extraction of semantic objects from still images
topic Image segmentation
Feature extraction
Still images
url https://hdl.handle.net/20.500.12008/21219