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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3EDLD6H
Repositorysid.inpe.br/sibgrapi/2013/07.05.19.01
Last Update2013:07.05.19.01.14 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2013/07.05.19.01.14
Metadata Last Update2022:06.14.00.07.44 (UTC) administrator
DOI10.1109/SIBGRAPI.2013.18
Citation KeyAlmeidaJung:2013:ChDeHu
TitleChange detection in human crowds
FormatOn-line.
Year2013
Access Date2025, July 06
Number of Files1
Size10550 KiB
2. Context
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
Date5-8 Aug. 2013
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2013-07-05 19:01:14 :: iralmeida@inf.ufrgs.br -> administrator ::
2022-06-14 00:07:44 :: administrator -> :: 2013
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
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.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2013 > Change detection in...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Change detection in...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3EDLD6H
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3EDLD6H
Languageen
Target FilePID2848451.pdf
User Groupiralmeida@inf.ufrgs.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SLB4P
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.04.02 36
sid.inpe.br/sibgrapi/2022/06.10.21.49 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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


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