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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/43BDNEB
Repositorysid.inpe.br/sibgrapi/2020/09.30.04.18
Last Update2020:09.30.04.18.12 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2020/09.30.04.18.12
Metadata Last Update2022:06.14.00.00.14 (UTC) administrator
DOI10.1109/SIBGRAPI51738.2020.00041
Citation KeyChoqueluqueRomanCáma:2020:ViDeLo
TitleViolence Detection and Localization in Surveillance Video
FormatOn-line
Year2020
Access Date2024, May 04
Number of Files1
Size10273 KiB
2. Context
Author1 Choqueluque Roman, David Gabriel
2 Cámara Chávez, Guillermo
Affiliation1 Department of Computer Science, Universidad Católica San Pablo, Arequipa, Perú
2 Department of Computer Science, Federal University of Ouro Preto, Ouro Preto, Brazil
EditorMusse, Soraia Raupp
Cesar Junior, Roberto Marcondes
Pelechano, Nuria
Wang, Zhangyang (Atlas)
e-Mail Addressdavid.choqueluque@ucsp.edu.pe
Conference NameConference on Graphics, Patterns and Images, 33 (SIBGRAPI)
Conference LocationPorto de Galinhas (virtual)
Date7-10 Nov. 2020
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2020-09-30 04:18:12 :: david.choqueluque@ucsp.edu.pe -> administrator ::
2022-06-14 00:00:14 :: administrator -> david.choqueluque@ucsp.edu.pe :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsViolence detection
violence localization
video surveillance
dynamic images
video summarization
saliency detection
AbstractAutomatic 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, Violent Flows, and UCFCrime2Local.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Violence Detection and...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Violence Detection and...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/43BDNEB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/43BDNEB
Languageen
Target File107.pdf
User Groupdavid.choqueluque@ucsp.edu.pe
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/43G4L9S
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2020/10.28.20.46 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume
7. Description control
e-Mail (login)david.choqueluque@ucsp.edu.pe
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