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dc.contributor.authorZhu, Zaiping
dc.contributor.authorIglesias Prieto, Andrés 
dc.contributor.authorZhou, Liqi
dc.contributor.authorYou, Lihua
dc.contributor.authorZhang, Jianjun
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2022-03-21T19:00:34Z
dc.date.available2022-03-21T19:00:34Z
dc.date.issued2022
dc.identifier.issn2227-7390
dc.identifier.otherTIN2017-89275-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/24266
dc.description.abstractPartial differential equation (PDE) based surfaces own a lot of advantages, compared to other types of 3D representation. For instance, fewer variables are required to represent the same 3D shape; the position, tangent, and even curvature continuity between PDE surface patches can be naturally maintained when certain conditions are satisfied, and the physics-based nature is also kept. Although some works applied implicit PDEs to 3D surface reconstruction from images, there is little work on exploiting the explicit solutions of PDE to this topic, which is more efficient and accurate. In this paper, we propose a new method to apply the explicit solutions of a fourth-order partial differential equation to surface reconstruction from multi-view images. The method includes two stages: point clouds data are extracted from multi-view images in the first stage, which is followed by PDE-based surface reconstruction from the obtained point clouds data. Our computational experiments show that the reconstructed PDE surfaces exhibit good quality and can recover the ground truth with high accuracy. A comparison between various solutions with different complexity to the fourth-order PDE is also made to demonstrate the power and flexibility of our proposed explicit PDE for surface reconstruction from images.es_ES
dc.description.sponsorshipThis research is supported by the PDE-GIR project, which has received funding from the European Union Horizon 2020 research and innovation programme under the Marie SkodowskaCurie grant agreement No 778035. Andres Iglesias also the project TIN2017-89275-R funded by MCIN/AEI/10.13039/501100011033/FEDER “Una manera de hacer Europa”.es_ES
dc.format.extent17 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution 4.0 International. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceMathematics, 2022, 10(4), 542es_ES
dc.subject.otherShape reconstructiones_ES
dc.subject.otherExplicit fourth-order partial differential equationes_ES
dc.subject.otherPoint clouds reconstruction from multi-view imageses_ES
dc.subject.otherPoint cloud parameterizationes_ES
dc.titlePDE-Based 3D surface reconstruction from multi-view 2d imageses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.3390/math10040542es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/778035/EU/PDE-based geometric modelling, image processing, and shape reconstruction/PDE-GIR/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89275-R/ES/SWARM INTELLIGENCE PARA MODELADO Y RECONSTRUCCION DE FORMAS EN GRAFICOS POR COMPUTADOR, IMAGENES MEDICAS Y ROBOTICA/es_ES
dc.identifier.DOI10.3390/math10040542
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 International. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.