Temporal-and Spatial-Driven Video Summarization Using Optimum-Path Forest

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade de São Paulo (USP)
dc.date.accessioned2018-11-26T17:39:43Z
dc.date.available2018-11-26T17:39:43Z
dc.date.created2018-11-26T17:39:43Z
dc.date.issued2016-01-01
dc.identifier2016 29th Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi). New York: Ieee, p. 335-339, 2016.
dc.identifier1530-1834
dc.identifierhttp://hdl.handle.net/11449/163001
dc.identifier10.1109/SIBGRAPI.2016.50
dc.identifierWOS:000405493800044
dc.description.abstractVideo summarization aims at generating reduced representations for fast and effective video retrieval and classification. In this paper, we cope with such problem by proposing a temporal-and spatial-driven approach that makes use of the Optimum-Path Forest (OPF) clustering to automatic find the number of keyframes, as well as to extract them to compose the final summary. The experiments in two public datasets show OPF can outperform very recent results, thus achieving a performance comparable to some state-of-the-art techniques.
dc.languageeng
dc.publisherIeee
dc.relation2016 29th Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi)
dc.rightsAcesso aberto
dc.sourceWeb of Science
dc.subjectOptimum-Path Forest
dc.subjectVideo Summarization
dc.titleTemporal-and Spatial-Driven Video Summarization Using Optimum-Path Forest
dc.typeActas de congresos


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