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An improved sub-optimal video summarization algorithm

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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorCoelho, Luís
dc.contributor.authorCruz, Luis A. da Silva
dc.contributor.authorFerreira, Lino
dc.contributor.authorAssunção, Pedro A.
dc.date.accessioned2025-11-27T12:19:54Z
dc.date.available2025-11-27T12:19:54Z
dc.date.issued2010
dc.descriptionConference name - 52nd International Symposium, ELMAR-2010; Conference date - 15 September 2010 - 17 September 2010; Conference code - 82753
dc.description.abstractDuring the last few years the amount of digital video content has been increasing exponentially as a result of the proliferation of media sources like digital TV, streaming video internet sites like YouTube and wider availability of digital video cameras. The video data volume is so large that the only way a user can browse these libraries is through the use of timecondensation techniques. Video summarization achieves timecondensation by choosing a sub-set of frames of the original video creating a summary hopefully representative of the source video. The frame selection process can be directed according to different principles, based on either subjective or objective frame-relevance measures. Previous works have used dynamic programming (DP) and greedy approaches to choose the frames that make up the video summary. We present an algorithm that performs better than the greedy solution achieving a performance closer to DP's while keeping the greedy solution's simplicity.eng
dc.identifier.citationL. Coelho, L. A. Da Silva Cruz, L. Ferreira and P. A. Assunção, "An improved sub-optimal video summarization algorithm," Proceedings ELMAR-2010, Zadar, Croatia, 2010, pp. 135-138.
dc.identifier.isbn978-953-7044-11-4
dc.identifier.issn1334-2630
dc.identifier.urihttp://hdl.handle.net/10400.8/14752
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/abstract/document/5606100
dc.rights.uriN/A
dc.subjectVideo summarization
dc.subjecttime-condensation
dc.subjectgreedy algorithm
dc.subjectdynamic programming
dc.titleAn improved sub-optimal video summarization algorithmeng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2010-09
oaire.citation.conferencePlaceZadar, Croatia
oaire.citation.endPage138
oaire.citation.startPage135
oaire.citation.titleProceedings Elmar - International Symposium Electronics in Marine
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFerreira
person.familyNameAssunção
person.givenNameLino
person.givenNamePedro
person.identifier.ciencia-id061B-4DCB-78BE
person.identifier.ciencia-id6811-3984-C17B
person.identifier.orcid0000-0003-0648-6067
person.identifier.orcid0000-0001-9539-8311
person.identifier.ridAAA-4462-2020
person.identifier.ridA-4827-2017
person.identifier.scopus-author-id36881920000
person.identifier.scopus-author-id6701838347
relation.isAuthorOfPublication03a0439a-a3c2-4fb1-8239-10b98d64659a
relation.isAuthorOfPublication25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication.latestForDiscovery03a0439a-a3c2-4fb1-8239-10b98d64659a

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During the last few years the amount of digital video content has been increasing exponentially as a result of the proliferation of media sources like digital TV, streaming video internet sites like YouTube and wider availability of digital video cameras. The video data volume is so large that the only way a user can browse these libraries is through the use of timecondensation techniques. Video summarization achieves timecondensation by choosing a sub-set of frames of the original video creating a summary hopefully representative of the source video. The frame selection process can be directed according to different principles, based on either subjective or objective frame-relevance measures. Previous works have used dynamic programming (DP) and greedy approaches to choose the frames that make up the video summary. We present an algorithm that performs better than the greedy solution achieving a performance closer to DP's while keeping the greedy solution's simplicity.
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