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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PJ4GM5
Repositorysid.inpe.br/sibgrapi/2017/09.04.14.38
Last Update2017:09.04.14.38.55 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.04.14.38.55
Metadata Last Update2022:05.18.22.18.23 (UTC) administrator
Citation KeyPaixãoPereKoma:2017:ReExFa
TitleReconhecimento de expressões faciais aplicada à análise de vídeos com reações espontâneas usando SVM com resposta probabilística
FormatOn-line
Year2017
Access Date2024, Oct. 15
Number of Files1
Size1113 KiB
2. Context
Author1 Paixão, Wdnei Ribeiro da
2 Pereira, Flávio Garcia
3 Komati, Karin Satie
Affiliation1 Instituto Federal do Espirito Santo - Campus Serra
2 Instituto Federal do Espirito Santo - Campus Serra
3 Instituto Federal do Espirito Santo - Campus Serra
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addresswdneipaixao@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2017-09-04 14:38:55 :: wdneipaixao@gmail.com -> administrator ::
2022-05-18 22:18:23 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsreconhecimento de expressões faciais
reações espontâneas
análise de vídeos
machine learning
HoG
SVM
AbstractThis work defines an initial proposal of a system for automated facial emotion classification applied to video that contains recordings of spontaneous reactions of spectators. The proposed approach uses a variation of the classifier Support Vector Machines (SVM) with outputs in a posteriori probability value and the Histogram of Oriented Gradients (HoG) as a feature descriptor. For the training, the Radboud Face Database (RaFD) was used. The results presented show the viability of the use in the mass media to assess the mood of the audience in quantitative terms of probability with respect to time.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Reconhecimento de expressões...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PJ4GM5
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ4GM5
Languagept
Target File7_wip.pdf
User Groupwdneipaixao@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 50
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi 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 versiontype volume


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