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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/LFJdm
Repositorysid.inpe.br/sibgrapi@80/2006/07.07.19.03
Last Update2006:07.07.19.03.29 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2006/07.07.19.03.30
Metadata Last Update2022:06.14.00.13.09 (UTC) administrator
DOI10.1109/SIBGRAPI.2006.3
Citation KeyKitaniThomGill:2006:StDiMo
TitleA Statistical Discriminant Model for Face Interpretation and Reconstruction
FormatOn-line
Year2006
Access Date2024, Apr. 29
Number of Files1
Size303 KiB
2. Context
Author1 Kitani, Edson
2 Thomaz, Carlos
3 Gillies, Duncan
Affiliation1 Department of Electrical Engineering, Centro Universitário da FEI, São Paulo, Brazil
2 Department of Electrical Engineering, Centro Universitário da FEI, São Paulo, Brazil
3 Department of Computing, Imperial College, London, UK
EditorOliveira Neto, Manuel Menezes de
Carceroni, Rodrigo Lima
e-Mail Addresscet@fei.edu.br
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)
Conference LocationManaus, AM, Brazil
Date8-11 Oct. 2006
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2006-07-07 19:03:30 :: cethomaz -> banon ::
2006-08-30 21:51:35 :: banon -> cethomaz ::
2008-07-17 14:11:02 :: cethomaz -> administrator ::
2009-08-13 20:38:00 :: administrator -> banon ::
2010-08-28 20:02:22 :: banon -> administrator ::
2022-06-14 00:13:09 :: administrator -> :: 2006
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsStatistical discriminant model
face interpretation and reconstruction
AbstractMultivariate statistical approaches have played an important role of recognising face images and charac-terizing their differences. In this paper, we introduce the idea of using a two-stage separating hyper-plane, here called Statistical Discriminant Model (SDM), to interpret and reconstruct face images. Analogously to the well-known Active Appearance Model proposed by Cootes et. al, SDM requires a previous alignment of all the images to a common template to minimise varia-tions that are not necessarily related to differences between the faces. However, instead of using landmarks or annotations on the images, SDM is based on the idea of using PCA to reduce the dimensionality of the original images and a maximum uncertainty linear classifier (MLDA) to characterise the most discrimi-nant changes between the groups of images. The experimental results based on frontal face images indicate that the SDM approach provides an intuitive interpretation of the differences between groups, reconstructing characteristics that are very subjective in human beings, such as beauty and happiness.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2006 > A Statistical Discriminant...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > A Statistical Discriminant...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/LFJdm
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/LFJdm
Languageen
Target Filethomaz-faces.pdf
User Groupcethomaz
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46RFT7E
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.08.00.20 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository 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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