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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3EDLD6H
Repositorysid.inpe.br/sibgrapi/2013/07.05.19.01
Last Update2013:07.05.19.01.14 iralmeida@inf.ufrgs.br
Metadatasid.inpe.br/sibgrapi/2013/07.05.19.01.14
Metadata Last Update2020:02.19.03.09.22 administrator
Citation KeyAlmeidaJung:2013:ChDeHu
TitleChange detection in human crowds
FormatOn-line.
Year2013
Access Date2021, Jan. 27
Number of Files1
Size10550 KiB
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Author1 Almeida, Igor Rodrigues de
2 Jung, Claudio Rosito
Affiliation1 Federal University of Rio Grande do Sul
2 Federal University of Rio Grande do Sul
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
e-Mail Addressiralmeida@inf.ufrgs.br
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
DateAug. 5-8, 2013
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2013-07-05 19:01:14 :: iralmeida@inf.ufrgs.br -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsCrowd analysis, Unusual event detection, Video surveillance.
AbstractThis paper presents a method to detect unusual behavior in human crowds based on histograms of velocities in world coordinates. A combination of background removal and optical flow is used to extract the global motion at each image frame, discarding small motion vectors due artifacts such as noise, non-stationary background pixels and compression issues. Using a calibrated camera, the global motion can be estimated, and it is used to build a 2D histogram containing information of speed and direction for all frames. Each frame is compared with a set of previous frames by using a histogram comparison metric, resulting in a similarity vector. This vector is then used to determine changes in the crowd behavior, also allowing a classification based on the nature of the change in time: short or long-term changes. The method was tested on publicly available datasets involving crowded scenarios.
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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3EDLD6H
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3EDLD6H
Languageen
Target FilePID2848451.pdf
User Groupiralmeida@inf.ufrgs.br
Visibilityshown
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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