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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/UNsdi
Repositorysid.inpe.br/sibgrapi@80/2008/07.18.22.27
Last Update2008:07.18.22.27.43 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2008/07.18.22.27.44
Metadata Last Update2022:09.13.03.49.21 (UTC) administrator
DOI10.1109/SIBGRAPI.2008.40
Citation KeyMena-ChalcoMacêVelhCesa:2008:PC3DFa
TitlePCA-based 3D Face Photography
FormatPrinted, On-line.
Year2008
Access Date2024, Apr. 27
Number of Files1
Size836 KiB
2. Context
Author1 Mena-Chalco, Jesús P.
2 Macêdo, Ives
3 Velho, Luiz Carlos Pacheco Rodrigues
4 Cesar-Jr, Roberto M.
Affiliation1 IME - Universidade de Sao Paulo
2 Instituto Nacional de Matemática Pura e Aplicada
3 Instituto Nacional de Matemática Pura e Aplicada
4 IME - Universidade de Sao Paulo
EditorJung, Cláudio Rosito
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 21 (SIBGRAPI)
Conference LocationCampo Grande, MS, Brazil
Date12-15 Oct. 2008
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-18 22:27:44 :: jmena@vision.ime.usp.br -> administrator ::
2009-08-13 20:38:59 :: administrator -> jmena@vision.ime.usp.br ::
2010-08-28 20:03:23 :: jmena@vision.ime.usp.br -> administrator ::
2022-09-13 03:49:21 :: administrator -> :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywords3D photography
principal component analysis
computer vision
AbstractThis paper presents a 3D face photography system based on a small set of training facial range images. The training set is composed by 2D texture and 3D range images (i.e. geometry) of a single subject with different facial expressions. The basic idea behind the method is to create texture and geometry spaces based on the training set and transformations to go from one space to the other. The main goal of the proposed approach is to obtain a geometry representation of a given face provided as a texture image, which undergoes a series of transformations through the texture and geometry spaces. Facial feature points are obtained by an active shape model (ASM) extracted from the 2D gray-level images. PCA then is used to represent the face dataset, thus defining an orthonormal basis of texture and range data. An input face is given by a gray-level face image to which the ASM is matched. The extracted ASM is fed to the PCA basis representation and a 3D version of the 2D input image is built. The experimental results on static images and video sequences using seven samples as training dataset show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency of our approach.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2008 > PCA-based 3D Face...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > PCA-based 3D Face...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/UNsdi
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/UNsdi
Languageen
Target FileMenaChalco-3DFacePhotography.pdf
User Groupjmena@vision.ime.usp.br
administrator
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SG4TH
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.04.55 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress 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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