Supervised video genre classification using optimum-path forest

Página do item simplificado
dc.contributor.authorMartins, Guilherme B. [UNESP]
dc.contributor.authorAlmeida, Jurandy
dc.contributor.authorPapa, Joao Paulo [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2018-12-11T17:29:23Z
dc.date.available2018-12-11T17:29:23Z
dc.date.issued2015-01-01
dc.description.abstractMultimedia-content classification has been paramount in the last years, mainly because of the massive data accessed daily. Video based retrieval and recommendation systems have attracted a considerable attention, since it is a profitable feature for several online and offline markets. In this work, we deal with the problem of automatic video classification in different genres based on visual information by means of Optimum-Path Forest (OPF), which is a recently developed graph-based pattern recognition technique. The aforementioned classifier is compared against with some state-of-the-art supervised machine learning techniques, such as Support Vector Machines and Bayesian classifier, being its efficiency and effectiveness evaluated in a number of datasets and problems.en
dc.description.affiliationDepartment of Computing São Paulo State University - UNESP
dc.description.affiliationInstitute of Science and Technology Federal University of São Paulo - UNIFESP
dc.description.affiliationUnespDepartment of Computing São Paulo State University - UNESP
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdFAPESP: #2013/20387-7
dc.description.sponsorshipIdFAPESP: #2014/16250-9
dc.description.sponsorshipIdCNPq: #306166/2014-3
dc.description.sponsorshipIdCNPq: #306166/2014-3-6
dc.format.extent735-742
dc.identifierhttp://dx.doi.org/10.1007/978-3-319-25751-8_88
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 9423, p. 735-742.
dc.identifier.doi10.1007/978-3-319-25751-8_88
dc.identifier.issn1611-3349
dc.identifier.issn0302-9743
dc.identifier.scopus2-s2.0-84983554786
dc.identifier.urihttp://hdl.handle.net/11449/178227
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofsjr0,295
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectOptimum-Path Forest
dc.subjectSupervised learning
dc.subjectVideo classification
dc.titleSupervised video genre classification using optimum-path foresten
dc.typeTrabalho apresentado em evento
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

Arquivos

Coleções

Bauru - FC - Faculdade de Ciências