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Reference TypeConference Proceedings
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3EDKF62
Repositorysid.inpe.br/sibgrapi/2013/07.05.13.57
Last Update2013:07.05.13.57.34 teofilobd@lia.ufc.br
Metadatasid.inpe.br/sibgrapi/2013/07.05.13.57.34
Metadata Last Update2020:02.19.03.09.22 administrator
Citation KeyDutraCavaVidaMuss:2013:MuFiMo
TitleA multipotential field model for crowds with scalable behaviors
FormatOn-line.
Year2013
DateAug. 5-8, 2013
Access Date2020, Dec. 04
Number of Files1
Size1186 KiB
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Author1 Dutra, Teófilo Bezerra
2 Cavalcante-Neto, Joaquim Bento
3 Vidal, Creto Augusto
4 Musse, Soraia Raupp
Affiliation1 Universidade Federal do Ceará
2 Universidade Federal do Ceará
3 Universidade Federal do Ceará
4 Pontifícia Universidade Católica do Rio Grande do Sul
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
e-Mail Addressteofilobd@lia.ufc.br
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2013-07-05 13:57:34 :: teofilobd@lia.ufc.br -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
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Is the master or a copy?is the master
Document Stagecompleted
Transferable1
Content TypeExternal Contribution
Tertiary TypeFull Paper
KeywordsPotential fields, reciprocal velocity obstacles, scalable behaviors, crowd simulation.
AbstractComputer simulation of realistic crowd behavior has been the focus of active research for more than two decades now. In crowd simulation, there is usually a trade-off between performance and realistic crowd behavior. In this paper, we propose a model, based on potential fields, that enables the introduction of many behaviors in crowd simulations, while keeping good performance. The model uses multiple groups to guide agents to various different goals in the environment, and combines potential fields and reciprocal velocity obstacles (RVO) approaches, where the first sets the preferred velocities of the agents according to their current goals, whereas the second makes the agents avoid collisions. We used three scenarios to demonstrate the capabilities of our model for simulating crowds in which the agents present greater variety of behaviors in real-time without using a complex architecture.
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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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