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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPAW/3PJ69JP
Repositorysid.inpe.br/sibgrapi/2017/09.05.00.08
Last Update2017:09.05.00.08.16 gui.bmartins3@gmail.com
Metadatasid.inpe.br/sibgrapi/2017/09.05.00.08.16
Metadata Last Update2020:02.20.22.06.47 administrator
Citation KeyMartinsAlmePapa:2017:ViPrAn
TitleVideo processing and analysis through Optimum-Path Forest
FormatOn-line
Year2017
Access Date2021, Jan. 25
Number of Files1
Size226 KiB
Context area
Author1 Martins, Guilherme Brandão
2 Almeida, Jurandy
3 Papa, João Paulo
Affiliation1 São Paulo State University
2 Federal University of São Paulo
3 São Paulo State University
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addressgui.bmartins3@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeMaster's or Doctoral Work
History2017-09-05 00:08:16 :: gui.bmartins3@gmail.com -> administrator ::
2020-02-20 22:06:47 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsvideo summarization, clustering, optimum-path forest.
AbstractCurrently, a number of improvements related to computational networks and data storage technologies have allowed a considerable amount of digital content to be provided on the Internet, mainly through social networks. In order to exploit this context, video processing and pattern recognition approaches have received a considerable attention in the last years. The main goal of this work is to employ the OptimumPath Forest classifier in both video summarization and video genre classification processes as well as to conduct a viability study of such classifier in the aforementioned contexts. The resultshave shown this classifier can achieve promising performances, being very close in terms of summary quality and consistent recognition rates to some state-of-the-art video summarization and video genre classification approaches, respectively.
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data URLhttp://urlib.net/rep/8JMKD3MGPAW/3PJ69JP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ69JP
Languageen
Target FilePaper_Martins_SIBGRAPI2017_WTD.pdf
User Groupgui.bmartins3@gmail.com
Visibilityshown
Update Permissionnot transferred
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PJT9LS
8JMKD3MGPAW/3PKCC58
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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