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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3C8U3MH
Repositorysid.inpe.br/sibgrapi/2012/07.09.15.07
Last Update2012:07.09.15.07.49 simoneceolin@gmail.com
Metadatasid.inpe.br/sibgrapi/2012/07.09.15.07.49
Metadata Last Update2020:02.19.02.18.27 administrator
Citation KeyCeolinHanc:2012:CoGeDi
TitleComputing gender difference using Fisher-Rao metric from facial surface normals
FormatDVD, On-line.
Year2012
Access Date2021, Jan. 28
Number of Files1
Size199 KiB
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Author1 Ceolin, Simone Regina
2 Hancock, Edwin R.
Affiliation1 Centro Universitário Franciscano
2 University of York
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addresssimoneceolin@gmail.com
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto
DateAug. 22-25, 2012
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2012-09-20 16:45:34 :: simoneceolin@gmail.com -> administrator :: 2012
2020-02-19 02:18:27 :: administrator -> :: 2012
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsFisher-Rao metric, surface normal, shape-from-shading.
AbstractThe aim in this paper is to explore whether the Fisher-Rao metric can be used to characterise the shape changes due to gender difference. We work using a 2.5D representation based on facial surface normals (or facial needle-maps) for gender classification. The needle-map is a shape representation which can be acquired from 2D intensity images using shape-from-shading (SFS). Using the von-Mises Fisher distribution, we compute the elements of the Fisher information matrix, and use this to compute geodesic distance between fields of surface normals to construct a shape-space. We embed the fields of facial surface normals into a low dimensional pattern space using a number of alternative methods including multidimensional scaling, heat kernel embedding and commute time embedding. We present results on clustering the embedded faces using the Max Planck and EAR database.
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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3C8U3MH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C8U3MH
Languageen
Target Filepaper_sibgrapi_2012.pdf
User Groupsimoneceolin@gmail.com
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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