Close
Metadata

Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPAW/3PJD3L2
Repositorysid.inpe.br/sibgrapi/2017/09.06.13.12
Last Update2017:09.06.13.12.02 diandraakemi@gmail.com
Metadatasid.inpe.br/sibgrapi/2017/09.06.13.12.02
Metadata Last Update2020:02.20.22.06.47 administrator
Citation KeyKuboBellFlynSilv:2017:CoFeEx
TitleFacial Expression Recognition: Comparison of Feature Extraction Methods
FormatOn-line
Year2017
DateOct. 17-20, 2017
Access Date2021, Jan. 19
Number of Files1
Size1338 KiB
Context area
Author1 Kubo, Diandra Akemi Alves
2 Bellon, Olga Regina Pereira
3 Flynn, Patrick
4 Silva, Luciano
Affiliation1 Universidade Federal do Paraná
2 Universidade Federal do Paraná
3 University of Notre Dame
4 Universidade Federal do Paraná
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 Addressdiandraakemi@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeUndergraduate Work
History2017-09-06 13:12:02 :: diandraakemi@gmail.com -> administrator ::
2020-02-20 22:06:47 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsfacial expression, feature extraction.
AbstractHuman facial expressions are one of the most im-portant communication channels, being used with trust to betterunderstand ones state of mind in a variety of applications, forinstance, emotion recognition. As a result, various algorithms andmethods have been developed for facial expression recognition.On this context, we review the literature and conduct tests ondifferent algorithms regarding facial feature extraction, in orderto evaluate their performance on the BU-3DFE database. Thisdatabase was chosen because it is widely used and all emotionsare annotated for each image. Therefore BU-3DFE is suitable forthe proposed benchmarking. The best result was achieved by acombination of Eigenfaces and SVM as classifier.
source Directory Contentthere are no files
agreement Directory Content
agreement.html 06/09/2017 10:12 1.2 KiB 
Conditions of access and use area
data URLhttp://urlib.net/rep/8JMKD3MGPAW/3PJD3L2
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJD3L2
Languageen
Target File2017_sibgrapi_daakubo.pdf
User Groupdiandraakemi@gmail.com
Visibilityshown
Update Permissionnot transferred
Allied materials area
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PJT9LS
8JMKD3MGPAW/3PKCC58
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
Notes area
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition 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

Close