Violence Detection and Localization in Surveillance Video

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Automatic violence detection in video surveillance is crucial for social and personal security. Due to the massive video data produced by surveillance cameras installed in different environments like airports, trains, stadiums, schools, etc., traditional video monitoring by humans operators becomes...

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Detalles Bibliográficos
Autores: Roman D.G.C., Chavez G.C.
Formato: artículo
Fecha de Publicación:2020
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2465
Enlace del recurso:https://hdl.handle.net/20.500.12390/2465
https://doi.org/10.1109/SIBGRAPI51738.2020.00041
Nivel de acceso:acceso abierto
Materia:violence localization
detection
dynamic images
saliency detection
video summarization
video surveillance
http://purl.org/pe-repo/ocde/ford#5.01.01
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/2465
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Violence Detection and Localization in Surveillance Video
title Violence Detection and Localization in Surveillance Video
spellingShingle Violence Detection and Localization in Surveillance Video
Roman D.G.C.
violence localization
detection
dynamic images
saliency detection
video summarization
video surveillance
http://purl.org/pe-repo/ocde/ford#5.01.01
title_short Violence Detection and Localization in Surveillance Video
title_full Violence Detection and Localization in Surveillance Video
title_fullStr Violence Detection and Localization in Surveillance Video
title_full_unstemmed Violence Detection and Localization in Surveillance Video
title_sort Violence Detection and Localization in Surveillance Video
author Roman D.G.C.
author_facet Roman D.G.C.
Chavez G.C.
author_role author
author2 Chavez G.C.
author2_role author
dc.contributor.author.fl_str_mv Roman D.G.C.
Chavez G.C.
dc.subject.none.fl_str_mv violence localization
topic violence localization
detection
dynamic images
saliency detection
video summarization
video surveillance
http://purl.org/pe-repo/ocde/ford#5.01.01
dc.subject.es_PE.fl_str_mv detection
dynamic images
saliency detection
video summarization
video surveillance
dc.subject.ocde.none.fl_str_mv http://purl.org/pe-repo/ocde/ford#5.01.01
description Automatic violence detection in video surveillance is crucial for social and personal security. Due to the massive video data produced by surveillance cameras installed in different environments like airports, trains, stadiums, schools, etc., traditional video monitoring by humans operators becomes inefficient. In this context, develop systems capable of detect automatically violent actions is a challenging task. This study describes a method to detect and localize violent acts in video surveillance using dynamic images, CNN's, and weakly supervised localization methods. Experimental results demonstrate the effectiveness of our approach when applied to three public benchmark datasets: Hockey Fight [1], Violent Flows [2], and UCFCrime2Loca1 [3]. © 2020 IEEE.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/2465
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/SIBGRAPI51738.2020.00041
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85099591859
url https://hdl.handle.net/20.500.12390/2465
https://doi.org/10.1109/SIBGRAPI51738.2020.00041
identifier_str_mv 2-s2.0-85099591859
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Proceedings - 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2020
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp06252600rp00690600Roman D.G.C.Chavez G.C.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2020https://hdl.handle.net/20.500.12390/2465https://doi.org/10.1109/SIBGRAPI51738.2020.000412-s2.0-85099591859Automatic violence detection in video surveillance is crucial for social and personal security. Due to the massive video data produced by surveillance cameras installed in different environments like airports, trains, stadiums, schools, etc., traditional video monitoring by humans operators becomes inefficient. In this context, develop systems capable of detect automatically violent actions is a challenging task. This study describes a method to detect and localize violent acts in video surveillance using dynamic images, CNN's, and weakly supervised localization methods. Experimental results demonstrate the effectiveness of our approach when applied to three public benchmark datasets: Hockey Fight [1], Violent Flows [2], and UCFCrime2Loca1 [3]. © 2020 IEEE.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengInstitute of Electrical and Electronics Engineers Inc.Proceedings - 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2020info:eu-repo/semantics/openAccessviolence localizationdetection-1dynamic images-1saliency detection-1video summarization-1video surveillance-1http://purl.org/pe-repo/ocde/ford#5.01.01-1Violence Detection and Localization in Surveillance Videoinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2465oai:repositorio.concytec.gob.pe:20.500.12390/24652024-05-30 15:45:39.542http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="cdd3c33c-9401-4855-a71f-dd3d1d6d4163"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Violence Detection and Localization in Surveillance Video</Title> <PublishedIn> <Publication> <Title>Proceedings - 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2020</Title> </Publication> </PublishedIn> <PublicationDate>2020</PublicationDate> <DOI>https://doi.org/10.1109/SIBGRAPI51738.2020.00041</DOI> <SCP-Number>2-s2.0-85099591859</SCP-Number> <Authors> <Author> <DisplayName>Roman D.G.C.</DisplayName> <Person id="rp06252" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Chavez G.C.</DisplayName> <Person id="rp00690" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Institute of Electrical and Electronics Engineers Inc.</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>violence localization</Keyword> <Keyword>detection</Keyword> <Keyword>dynamic images</Keyword> <Keyword>saliency detection</Keyword> <Keyword>video summarization</Keyword> <Keyword>video surveillance</Keyword> <Abstract>Automatic violence detection in video surveillance is crucial for social and personal security. Due to the massive video data produced by surveillance cameras installed in different environments like airports, trains, stadiums, schools, etc., traditional video monitoring by humans operators becomes inefficient. In this context, develop systems capable of detect automatically violent actions is a challenging task. This study describes a method to detect and localize violent acts in video surveillance using dynamic images, CNN&apos;s, and weakly supervised localization methods. Experimental results demonstrate the effectiveness of our approach when applied to three public benchmark datasets: Hockey Fight [1], Violent Flows [2], and UCFCrime2Loca1 [3]. © 2020 IEEE.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
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