cris.boxmetadata.label.title
SHREC’20 Track: Retrieval of digital surfaces with similar geometric reliefs
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.october 2020
cris.boxmetadata.label.accesslevel
open access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Moscoso Thompson E.
Biasotti S.
Giachetti A.
Tortorici C.
Werghi N.
Obeid A.S.
Berretti S.
Nguyen-Dinh H.P.
Le M.Q.
Nguyen H.D.
Tran M.T.
Gigli L.
Velasco-Forero S.
Marcotegui B.
SIPIRAN MENDOZA, IVAN ANSELMO
Bustos B.
Romanelis I.
Fotis V.
Arvanitis G.
Moustakas K.
Otu E.
Zwiggelaar R.
Hunter D.
Liu Y.
Arteaga Y.
Luxman R.
cris.boxmetadata.label.publisher
Elsevier Ltd
cris.boxmetadata.label.abstract
This paper presents the methods that have participated in the SHREC’20 contest on retrieval of surface patches with similar geometric reliefs and the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local ”geometric pattern” information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches.
cris.boxmetadata.label.citationstartpage
199
cris.boxmetadata.label.citationendpage
218
cris.boxmetadata.label.volume
91
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Ciencias de la computación
cris.boxmetadata.label.subjects
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-85089440088
cris.boxmetadata.label.source
Computers and Graphics (Pergamon)
cris.boxmetadata.label.containerissn
00978493
cris.boxmetadata.label.sponsor
The authors thank the 3DOR 2020 Workshop and Program Chairs for helping us in the organization of our contest despite the current COVID-19 pandemic. We also thank the anonymous reviewers for providing constructive comments on earlier drafts of the manuscript, which helped us to improve and clarify this work. This study was partially supported by the CNR-IMATI projects DIT.AD004.100 and DIT.AD021.080.001. Research for the team from University of Science, Ho Chi Minh city, Vietnam is supported by Vingroup Innovation Foundation (VINIF) in project code VINIF.2019.DA19. The team Y. Arteaga and R. Luxman research is funded by the Horizon 2020 programme of the European Union Grant #813789. The work of Ivan Sipiran has been supported by Proyecto de Mejoramiento y Ampliacin de los Servicios del Sistema Nacional de Ciencia Tecnologȡa e Innovacin Tecnolgica(Banco Mundial, Concytec), Nro. grant 062-2018-FONDECYT-BM-IADT-AV. The work of Benjamin Bustos is funded by the Millennium Institute Foundational Research on Data (IMFD).
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