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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PK84H8
Repositorysid.inpe.br/sibgrapi/2017/09.11.13.40
Last Update2017:09.11.13.40.19 (UTC) flaviozavan@gmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.11.13.40.19
Metadata Last Update2022:05.18.22.18.26 (UTC) administrator
Citation KeyZavanSilvBell:2017:NoPoEs
TitleNose pose estimation in the wild and its applications on nose tracking and 3D face alignment
FormatOn-line
Year2017
Access Date2024, May 02
Number of Files1
Size6056 KiB
2. Context
Author1 Zavan, Flávio Henrique de Bittencourt
2 Silva, Luciano
3 Bellon, Olga Regina Pereira
Affiliation1 Universidade Federal do Paraná
2 Universidade Federal do Paraná
3 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 Addressflaviozavan@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 TypeMaster's or Doctoral Work
History (UTC)2017-09-11 13:40:19 :: flaviozavan@gmail.com -> administrator ::
2022-05-18 22:18:26 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsface processing
face analysis
head pose estimation
AbstractAn automatic, landmark free SVM-based method for head pose estimation, solely using the nose region, in constrained and unconstrained scenarios, is presented. Using the nose region has advantages over the whole face; it is less likely to be occluded or deformed by facial expressions, and is proven to be highly discriminant in all poses from profile to frontal. The approach, SVM-NosePose, receives a nose region as and classifies it into a discrete set of poses. Estimation favorably compares against state-of-the-art works on six publicly available datasets. Three applications are derived from the proposed methodology: 1) the original inclusion of a head pose score for face quality estimation for initializing a nose tracker, leading to higher accuracy; 2) 3D face alignment in the wild using only the nose pose, enabling consistent estimates even in challenging scenarios; and 3) multipose action unit detection and intensity estimation for facial images in the wild.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Nose pose estimation...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PK84H8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PK84H8
Languageen
Target Filewtd_sibgrapi_2017_camera_ready.pdf
User Groupflaviozavan@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 5
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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