Static video summarization through Optimum-Path Forest clustering

Detalhes bibliográficos
Autor(a) principal: Martins, G. B. [UNESP]
Data de Publicação: 2014
Outros Autores: Afonso, L. C.S. [UNESP], Osaku, D., Almeida, Jurandy, Papa, J. P. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/168181
Resumo: This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.
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spelling Static video summarization through Optimum-Path Forest clusteringClusteringOptimum-path forestVideo summarizationThis paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.Department of Computing São Paulo State University UNESPInstitute of Science and Technology Federal University of São Paulo UNIFESPDepartment of Computer Science Federal University of São Carlos UFSCarDepartment of Computing São Paulo State University UNESPUniversidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Universidade Federal de São Carlos (UFSCar)Martins, G. B. [UNESP]Afonso, L. C.S. [UNESP]Osaku, D.Almeida, JurandyPapa, J. P. [UNESP]2018-12-11T16:40:07Z2018-12-11T16:40:07Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject893-900Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 893-900.1611-33490302-9743http://hdl.handle.net/11449/1681812-s2.0-84949130645Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)0,295info:eu-repo/semantics/openAccess2021-10-23T21:44:25Zoai:repositorio.unesp.br:11449/168181Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:17:03.928Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Static video summarization through Optimum-Path Forest clustering
title Static video summarization through Optimum-Path Forest clustering
spellingShingle Static video summarization through Optimum-Path Forest clustering
Martins, G. B. [UNESP]
Clustering
Optimum-path forest
Video summarization
title_short Static video summarization through Optimum-Path Forest clustering
title_full Static video summarization through Optimum-Path Forest clustering
title_fullStr Static video summarization through Optimum-Path Forest clustering
title_full_unstemmed Static video summarization through Optimum-Path Forest clustering
title_sort Static video summarization through Optimum-Path Forest clustering
author Martins, G. B. [UNESP]
author_facet Martins, G. B. [UNESP]
Afonso, L. C.S. [UNESP]
Osaku, D.
Almeida, Jurandy
Papa, J. P. [UNESP]
author_role author
author2 Afonso, L. C.S. [UNESP]
Osaku, D.
Almeida, Jurandy
Papa, J. P. [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade de São Paulo (USP)
Universidade Federal de São Carlos (UFSCar)
dc.contributor.author.fl_str_mv Martins, G. B. [UNESP]
Afonso, L. C.S. [UNESP]
Osaku, D.
Almeida, Jurandy
Papa, J. P. [UNESP]
dc.subject.por.fl_str_mv Clustering
Optimum-path forest
Video summarization
topic Clustering
Optimum-path forest
Video summarization
description This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01
2018-12-11T16:40:07Z
2018-12-11T16:40:07Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 893-900.
1611-3349
0302-9743
http://hdl.handle.net/11449/168181
2-s2.0-84949130645
identifier_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 893-900.
1611-3349
0302-9743
2-s2.0-84949130645
url http://hdl.handle.net/11449/168181
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
0,295
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 893-900
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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