Hierarchy-based salient regions: A region detector based on hierarchies of partitions

Descripción del Articulo

This work received funding from FONDECYT-CONCYTEC (contract number 004-2016-FONDECYT), CAPES (PVE 125000/2014-00), FAPEMIG (PPM 00006-16), and CNPq (Universal 421521/2016-3 and PQ 307062/2016-3).
Detalles Bibliográficos
Autores: Otiniano-Rodríguez K., de A. Araújo A., Cámara-Chávez G., Cousty J., Guimarães S.J.F., Perret B.
Formato: objeto de conferencia
Fecha de Publicación:2019
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/633
Enlace del recurso:https://hdl.handle.net/20.500.12390/633
https://doi.org/10.1007/978-3-030-13469-3_52
Nivel de acceso:acceso abierto
Materia:State-of-the-art methods
Mathematical morphology
Feature detection
High quality
Salient region detections
Salient regions
Computer vision
https://purl.org/pe-repo/ocde/ford#2.02.00
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/633
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Hierarchy-based salient regions: A region detector based on hierarchies of partitions
title Hierarchy-based salient regions: A region detector based on hierarchies of partitions
spellingShingle Hierarchy-based salient regions: A region detector based on hierarchies of partitions
Otiniano-Rodríguez K.
State-of-the-art methods
Mathematical morphology
Feature detection
High quality
High quality
Salient region detections
Salient regions
Computer vision
https://purl.org/pe-repo/ocde/ford#2.02.00
title_short Hierarchy-based salient regions: A region detector based on hierarchies of partitions
title_full Hierarchy-based salient regions: A region detector based on hierarchies of partitions
title_fullStr Hierarchy-based salient regions: A region detector based on hierarchies of partitions
title_full_unstemmed Hierarchy-based salient regions: A region detector based on hierarchies of partitions
title_sort Hierarchy-based salient regions: A region detector based on hierarchies of partitions
author Otiniano-Rodríguez K.
author_facet Otiniano-Rodríguez K.
de A. Araújo A.
Cámara-Chávez G.
Cousty J.
Guimarães S.J.F.
Perret B.
author_role author
author2 de A. Araújo A.
Cámara-Chávez G.
Cousty J.
Guimarães S.J.F.
Perret B.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Otiniano-Rodríguez K.
de A. Araújo A.
Cámara-Chávez G.
Cousty J.
Guimarães S.J.F.
Perret B.
dc.subject.none.fl_str_mv State-of-the-art methods
topic State-of-the-art methods
Mathematical morphology
Feature detection
High quality
High quality
Salient region detections
Salient regions
Computer vision
https://purl.org/pe-repo/ocde/ford#2.02.00
dc.subject.es_PE.fl_str_mv Mathematical morphology
Feature detection
High quality
High quality
Salient region detections
Salient regions
Computer vision
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.00
description This work received funding from FONDECYT-CONCYTEC (contract number 004-2016-FONDECYT), CAPES (PVE 125000/2014-00), FAPEMIG (PPM 00006-16), and CNPq (Universal 421521/2016-3 and PQ 307062/2016-3).
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.isbn.none.fl_str_mv 9783030134686
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/633
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-13469-3_52
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85063063039
identifier_str_mv 9783030134686
2-s2.0-85063063039
url https://hdl.handle.net/20.500.12390/633
https://doi.org/10.1007/978-3-030-13469-3_52
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp01289600rp01292600rp00652400rp00651500rp01290600rp01291600Otiniano-Rodríguez K.de A. Araújo A.Cámara-Chávez G.Cousty J.Guimarães S.J.F.Perret B.2024-05-30T23:13:38Z2024-05-30T23:13:38Z20199783030134686https://hdl.handle.net/20.500.12390/633https://doi.org/10.1007/978-3-030-13469-3_522-s2.0-85063063039This work received funding from FONDECYT-CONCYTEC (contract number 004-2016-FONDECYT), CAPES (PVE 125000/2014-00), FAPEMIG (PPM 00006-16), and CNPq (Universal 421521/2016-3 and PQ 307062/2016-3).This article introduces a novel region detector based on hierarchies of partitions, so-called Hierarchy-Based Salient Regions (HBSR). This approach enables to combine the clues given by a high quality contour detector with a custom salient region detection procedure. The evaluation of the proposed method HBSR with a standard feature detection assessment framework shows that HBSR outperforms the state-of-the-art methods, in average. These promising results may lead to improvements in many computer vision tasks.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengSpringer VerlagLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)info:eu-repo/semantics/openAccessState-of-the-art methodsMathematical morphology-1Feature detection-1High quality-1High quality-1Salient region detections-1Salient regions-1Computer vision-1https://purl.org/pe-repo/ocde/ford#2.02.00-1Hierarchy-based salient regions: A region detector based on hierarchies of partitionsinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/633oai:repositorio.concytec.gob.pe:20.500.12390/6332024-05-30 15:22:28.959http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="81caa7ad-9216-4edb-a72c-68b55d04bc32"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Hierarchy-based salient regions: A region detector based on hierarchies of partitions</Title> <PublishedIn> <Publication> <Title>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</Title> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <DOI>https://doi.org/10.1007/978-3-030-13469-3_52</DOI> <SCP-Number>2-s2.0-85063063039</SCP-Number> <ISBN>9783030134686</ISBN> <Authors> <Author> <DisplayName>Otiniano-Rodríguez K.</DisplayName> <Person id="rp01289" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>de A. Araújo A.</DisplayName> <Person id="rp01292" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Cámara-Chávez G.</DisplayName> <Person id="rp00652" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Cousty J.</DisplayName> <Person id="rp00651" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Guimarães S.J.F.</DisplayName> <Person id="rp01290" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Perret B.</DisplayName> <Person id="rp01291" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Springer Verlag</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>State-of-the-art methods</Keyword> <Keyword>Mathematical morphology</Keyword> <Keyword>Feature detection</Keyword> <Keyword>High quality</Keyword> <Keyword>High quality</Keyword> <Keyword>Salient region detections</Keyword> <Keyword>Salient regions</Keyword> <Keyword>Computer vision</Keyword> <Abstract>This article introduces a novel region detector based on hierarchies of partitions, so-called Hierarchy-Based Salient Regions (HBSR). This approach enables to combine the clues given by a high quality contour detector with a custom salient region detection procedure. The evaluation of the proposed method HBSR with a standard feature detection assessment framework shows that HBSR outperforms the state-of-the-art methods, in average. These promising results may lead to improvements in many computer vision tasks.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.434441
Hierarchy-based salient regions: A region detector based on hierarchies of partitions
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

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