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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PFCA92
Repositorysid.inpe.br/sibgrapi/2017/08.18.22.12
Last Update2017:08.18.22.12.49 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.18.22.12.49
Metadata Last Update2022:06.14.00.08.49 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.34
Citation KeyVaretoSilvCostSchw:2017:FaVeBa
TitleFace Verification based on Relational Disparity Features and Partial Least Squares Models
FormatOn-line
Year2017
Access Date2024, Oct. 15
Number of Files1
Size351 KiB
2. Context
Author1 Vareto, Rafael Henrique
2 Silva, Samira Santos da
3 Costa, Filipe de Oliveira
4 Schwartz, William Robson
Affiliation1 Universidade Federak de Minas Gerais
2 Universidade Federak de Minas Gerais
3 Universidade Federak de Minas Gerais
4 Universidade Federak de Minas Gerais
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 Addressrafaelvareto@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-18 22:12:49 :: rafaelvareto@gmail.com -> administrator ::
2022-06-14 00:08:49 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsFace verification
partial least squares
relational features
AbstractFace verification approaches aim at determining whether two given faces are from the same person. This scenario has several applications, such as information security, forensics, surveillance and smart cards. Several works extract features independently from each face image, i.e., any sort of relation between the two faces is not modeled a priori to either training or classification stages. In this work, we propose an approach that compares a pair of faces by extracting relational features, assuming the hypothesis that modeling the relation between two faces can be useful for increasing the robustness and performance of the face verification task. Then, we employ multiple classification models based on Partial Least Squares to verify whether a given pair of images belongs the same subject (genuine) or belongs to different subjects (impostor). We validate our approach on the Labeled Faces in the Wild (LFW) and on the Public Figures (Pubfig) datasets, using only few images for training. According to the experiments, our approach achieves results up to 0.966 of area under the curve (AUC) for the LFW dataset using its unrestricted, labeled outside data protocol and an average equal error (EER) of 13.65% on PubFig dataset.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Face Verification based...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Face Verification based...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PFCA92
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PFCA92
Languageen
Target FilePID4957039.pdf
User Grouprafaelvareto@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 37
sid.inpe.br/sibgrapi/2022/06.10.21.49 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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 volume


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