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Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3A3K6P2
Repositorysid.inpe.br/sibgrapi/2011/07.10.16.48
Last Update2011:07.10.16.48.23 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2011/07.10.16.48.23
Metadata Last Update2022:06.14.00.07.15 (UTC) administrator
DOI10.1109/SIBGRAPI.2011.37
Citation KeyMarroquimPfeiCarvOliv:2011:Te3DMo
TitleTexturing 3D models with low geometric features
FormatDVD, On-line.
Year2011
Access Date2024, Apr. 17
Number of Files1
Size5433 KiB
2. Context
Author1 Marroquim, Ricardo
2 Pfeiffer, Gustavo
3 Carvalho, Felipe Moura de
4 Oliveira, Antonio Alberto Fernades de
Affiliation1 UFRJ
2 UFRJ
3 UFRJ
4 UFRJ
EditorLewiner, Thomas
Torres, Ricardo
e-Mail Addressmarroquim@cos.ufrj.br
Conference NameConference on Graphics, Patterns and Images, 24 (SIBGRAPI)
Conference LocationMaceió, AL, Brazil
Date28-31 Aug. 2011
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2011-07-23 15:36:12 :: marroquim@cos.ufrj.br -> administrator :: 2011
2022-06-14 00:07:15 :: administrator -> :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywords3D virtual replica
high-resolution texture mapping
least-squares minimization
AbstractThis paper presents a texture projection and alignment method specifically tailored for objects with low geometric features. A common way to build virtual replicas is to acquire the geometry with a 3D scanner and model its reflectance properties (i.e. colors) by projecting photos onto the 3D surface. To correctly align each photo it is necessary to retrieve the camera's extrinsic matrix, which is usually achieved by optimization algorithms that match geometric features of the model with their corresponding ones on the photos. However, when dealing with cultural heritage artifacts or mechanical pieces, for example, some models inherently lack significant geometric detail. We propose a method to automatically extract these features from high resolution photos and register them in a sequential manner using a variation of the contour-based approaches. The algorithm requires minimum user intervention as only an initial guess of the camera's direction is required for each photo. In addition, we describe an improved formulation of the optimization method based on a smooth function that avoids typical local minima found in this scenario. The results are illustrated with high-resolution textured models produced by our system.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2011 > Texturing 3D models...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Texturing 3D models...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3A3K6P2
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3A3K6P2
Languageen
Target Filetexture-alignment.pdf
User Groupmarroquim@cos.ufrj.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SKNPE
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.00.56 3
sid.inpe.br/banon/2001/03.30.15.38.24 1
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 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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