Identity statement area
Reference TypeConference Proceedings
Last Update2018: administrator
Metadata Last Update2020: administrator
Citation KeyHurtadoGattRapoCoel:2018:AdPaMe
TitleAdaptive patches for mesh denoising
DateOct. 29 - Nov. 1, 2018
Access Date2020, Dec. 02
Number of Files1
Size11981 KiB
Context area
Author1 Hurtado, Jan
2 Gattass, Marcelo
3 Raposo, Alberto
4 Coelho, Jéferson
Affiliation1 Pontifícia Universidade Católica do Rio de Janeiro
2 Pontifícia Universidade Católica do Rio de Janeiro
3 Pontifícia Universidade Católica do Rio de Janeiro
4 Pontifícia Universidade Católica do Rio de Janeiro
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2018-08-28 13:14:30 :: -> administrator :: 2018
2018-09-03 20:37:56 :: administrator -> :: 2018
2018-09-08 12:17:30 :: -> administrator :: 2018
2020-02-19 03:10:44 :: administrator -> :: 2018
Content and structure area
Is the master or a copy?is the master
Document Stagecompleted
Document Stagenot transferred
Content TypeExternal Contribution
Tertiary TypeFull Paper
Keywordsadaptive patches, mesh denoising.
AbstractThe generation of triangular meshes typically introduces undesired noise which comes from different sources. Mesh denoising is a geometry processing task to remove this kind of distortion. To preserve the geometric fidelity of the desired mesh, a mesh denoising algorithm must maintain the object details while removing artificial high-frequencies from the surface. In this work, we propose a two-step algorithm which uses adaptive patches and bilateral filtering to denoise the normal vector field, and then update vertex positions fitting the faces to the denoised normals. The computation of the adaptive patches is our main contribution. We formulate this computation as local quadratic optimization problems that can be controlled by a set of parameters to obtain the desired behavior. We compared our proposal with several algorithms proposed in the literature using synthetic and real data. Our algorithm yields better results in general and is based on a formal mathematical formulation.
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adaptive-patches-SIBGRAPI2018.pdf 27/08/2018 14:16 11.7 MiB
AdaptivePatchesForMeshDenoising-SIBGRAPI2018.pdf 28/08/2018 10:14 11.7 MiB
agreement Directory Content
agreement.html 27/08/2018 14:16 1.2 KiB 
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Target FilePID5560825.pdf
Allied materials area
Next Higher Units8JMKD3MGPAW/3RPADUS
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