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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.identifier.isbn978-1-4799-8131-1pt_BR
dc.contributor.authorunicampPeixoto, Bruno Malveira-
dc.contributor.authorunicampLavi, Bahram-
dc.contributor.authorunicampAvila, Sandra Eliza Fontes de-
dc.contributor.authorunicampDias, Zanoni-
dc.contributor.authorunicampRocha, Anderson de Rezende-
dc.typeArtigopt_BR
dc.titleToward subjective violence detection in videospt_BR
dc.contributor.authorPeixoto, Bruno-
dc.contributor.authorLavi, Bahram-
dc.contributor.authorMartin, João Paulo Pereira-
dc.contributor.authorAvila, Sandra-
dc.contributor.authorDias, Zanoni-
dc.contributor.authorRocha, Anderson-
dc.subjectComputação forensept_BR
dc.subjectVisão por computadorpt_BR
dc.subjectAprendizado de máquinapt_BR
dc.subjectSemânticapt_BR
dc.subject.otherlanguageForensic computingpt_BR
dc.subject.otherlanguageComputer visionpt_BR
dc.subject.otherlanguageMachine learningpt_BR
dc.subject.otherlanguageSemanticspt_BR
dc.description.abstractViolence detection in videos aims to identify whether a violent action occurred within a video stream. Effective tools for intelligent video analysis are highly demanded, specially to determine violence in video streams. Such solution could have applications in detecting inappropriate behaviors in video feeds, aiding law-enforcement in forensic cases, protecting children from accessing inappropriate online content and helping parents making informed decisions about what their kids should watch. Prior art on violence detection, particularly recently proposed deep learning based ones, seeks to identify violence in videos as a whole, without considering breaking down the subject into some of its underlying concepts. In this paper, we explore a different methodology of violence detection, which relies upon two deep neural network (DNNs) frameworks to learn spatial-temporal information on video clips under different scenarios - subjective- and conceptual-based. We leverage deep feature representations for each specific concept, and aggregate them by training a shallow neural network as a binary-classification problem to describe violence as a whole. Finally, we show that using more specific concepts is an intuitive and effective solution, besides being complementary to form a more robust definition of violencept_BR
dc.relation.ispartofIEEE international conference on acoustics, speech and signal processing. proceedingspt_BR
dc.relation.ispartofabbreviationICASSPpt_BR
dc.publisher.cityPiscataway, NJpt_BR
dc.publisher.countryEstados Unidospt_BR
dc.publisherInstitute of Electrical and Electronics Engineerspt_BR
dc.date.issued2019-
dc.date.monthofcirculationApr.pt_BR
dc.language.isoengpt_BR
dc.rightsFechadopt_BR
dc.sourceSCOPUSpt_BR
dc.identifier.issn2379-190Xpt_BR
dc.identifier.eissn1520-6149pt_BR
dc.identifier.doi10.1109/ICASSP.2019.8682833pt_BR
dc.identifier.urlhttps://ieeexplore.ieee.org/document/8682833pt_BR
dc.date.available2020-05-22T17:28:59Z-
dc.date.accessioned2020-05-22T17:28:59Z-
dc.description.provenanceSubmitted by Susilene Barbosa da Silva (susilene@unicamp.br) on 2020-05-22T17:28:59Z No. of bitstreams: 0. Added 1 bitstream(s) on 2020-08-27T19:18:07Z : No. of bitstreams: 1 2-s2.0-85068977309.pdf: 543042 bytes, checksum: ab01e44506ea5208055709155ff6dac6 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-05-22T17:28:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2019en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/342027-
dc.description.conferencenomeICASSP 2019 - 2019 IEEE international conference on acoustics, speech and signal processing (ICASSP)pt_BR
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.departmentDepartamento de Sistemas de Informaçãopt_BR
dc.contributor.departmentDepartamento de Teoria da Computaçãopt_BR
dc.contributor.departmentDepartamento de Sistemas de Informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordSpeech communicationpt_BR
dc.subject.keywordIntelligent videopt_BR
dc.subject.keywordDeep neural networkspt_BR
dc.subject.keywordBinary classification problemspt_BR
dc.identifier.source2-s2.0-85068977309pt_BR
dc.creator.orcidSem informaçãopt_BR
dc.creator.orcid0000-0002-9226-9116pt_BR
dc.creator.orcid0000-0001-9068-938Xpt_BR
dc.creator.orcid0000-0003-3333-6822pt_BR
dc.creator.orcid0000-0002-4236-8212pt_BR
dc.type.formArtigo de eventopt_BR
dc.identifier.articleid18778288pt_BR
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