Connectivity-preserving smooth surface filling with sharp features

Thibault Lescoat, Pooran Memari, Jean Marc Thiery, Maks Ovsjanikov, Tamy Boubekeur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present a method for constructing a surface mesh filling gaps between the boundaries of multiple disconnected input components. Unlike previous works, our method pays special attention to preserving both the connectivity and large-scale geometric features of input parts, while maintaining efficiency and scalability w.r.t. mesh complexity. Starting from an implicit surface reconstruction matching the parts' boundaries, we first introduce a modified dual contouring algorithm which stitches a meshed contour to the input components while preserving their connectivity. We then show how to deform the reconstructed mesh to respect the boundary geometry and preserve sharp feature lines, smoothly blending them when necessary. As a result, our reconstructed surface is smooth and propagates the feature lines of the input. We demonstrate on a wide variety of input shapes that our method is scalable to large input complexity and results in superior mesh quality compared to existing techniques.
Original languageEnglish (US)
Title of host publication27th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2019
PublisherIEEE Computer Society
Pages7-13
Number of pages7
ISBN (Print)9783038680994
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-22
Acknowledged KAUST grant number(s): CRG-2017-3426
Acknowledgements: We thank Lin et al. [LJWH08] and Centin and Signoroni [CS18] for their help with the comparisons. We also thank Marie-Paule Cani for her suggestions of test models. Parts of this work were supported by the ERC Starting Grant StG-2017-758800 (EXPROTEA), KAUST OSR Award CRG-2017-3426 and ANR grant 16-LCV2-0009-01 ALLEGORI.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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