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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3ME7NF2
Repositorysid.inpe.br/sibgrapi/2016/09.13.14.06
Last Update2016:09.13.14.06.23 (UTC) julio.batista@ufpr.br
Metadata Repositorysid.inpe.br/sibgrapi/2016/09.13.14.06.23
Metadata Last Update2022:05.18.22.21.10 (UTC) administrator
Citation KeyBatistaBellSilv:2016:LaSmIn
TitleLandmark-free smile intensity estimation
FormatOn-line
Year2016
Access Date2024, Apr. 28
Number of Files1
Size747 KiB
2. Context
Author1 Batista, Júlio César
2 Bellon, Olga Regina Pereira
3 Silva, Luciano
Affiliation1 Universidade Federal do Paraná
2 Universidade Federal do Paraná
3 Universidade Federal do Paraná
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressjulio.batista@ufpr.br
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeFace Processing Application Paper
History (UTC)2016-09-13 14:06:23 :: julio.batista@ufpr.br -> administrator ::
2022-05-18 22:21:10 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordssmile intensity estimation
facial expression analysis
feature extraction
machine learning
AbstractFacial expression analysis is an important field of research, mostly because of the rich information faces can provide. The majority of works published in the literature have focused on facial expression recognition and so far estimating facial expression intensities have not gathered same attention. The analysis of these intensities could improve face processing applications on distinct areas, such as computer assisted health care, human-computer interaction and biometrics. Because the smile is the most common expression, studying its intensity is a first step towards estimating other expressions intensities. Most related works are based on facial landmarks, sometimes combined with appearance features around these points, to estimate smile intensities. Relying on landmarks can lead to wrong estimations due to errors in the registration step. In this work we investigate a landmark-free approach for smile intensity estimation using appearance features from a grid division of the face. We tested our approach on two different databases, one with spontaneous expressions (BP4D) and the other with posed expressions (BU-3DFE); results are compared to state-of-the-art works in the field. Our method shows competitive results even using only appearance features on spontaneous facial expression intensities, but we found that there is still need for further investigation on posed expressions.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > Landmark-free smile intensity...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3ME7NF2
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3ME7NF2
Languageen
Target FileLandmark_free_smile_intensity_estimation.pdf
User Groupjulio.batista@ufpr.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 6
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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