Reconstructing Curves from Sparse Samples on Riemannian Manifolds

Fuente: arXiv
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Autori principali: Marin, Diana, Maggioli, Filippo, Melzi, Simone, Ohrhallinger, Stefan, Wimmer, Michael
Natura: Preprint
Pubblicazione: 2024
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author Marin, Diana
Maggioli, Filippo
Melzi, Simone
Ohrhallinger, Stefan
Wimmer, Michael
author_facet Marin, Diana
Maggioli, Filippo
Melzi, Simone
Ohrhallinger, Stefan
Wimmer, Michael
contents Reconstructing 2D curves from sample points has long been a critical challenge in computer graphics, finding essential applications in vector graphics. The design and editing of curves on surfaces has only recently begun to receive attention, primarily relying on human assistance, and where not, limited by very strict sampling conditions. In this work, we formally improve on the state-of-the-art requirements and introduce an innovative algorithm capable of reconstructing closed curves directly on surfaces from a given sparse set of sample points. We extend and adapt a state-of-the-art planar curve reconstruction method to the realm of surfaces while dealing with the challenges arising from working on non-Euclidean domains. We demonstrate the robustness of our method by reconstructing multiple curves on various surface meshes. We explore novel potential applications of our approach, allowing for automated reconstruction of curves on Riemannian manifolds.
format Preprint
id arxiv_https___arxiv_org_abs_2404_09661
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reconstructing Curves from Sparse Samples on Riemannian Manifolds
Marin, Diana
Maggioli, Filippo
Melzi, Simone
Ohrhallinger, Stefan
Wimmer, Michael
Computational Geometry
Graphics
68U05
I.3; I.3.5
Reconstructing 2D curves from sample points has long been a critical challenge in computer graphics, finding essential applications in vector graphics. The design and editing of curves on surfaces has only recently begun to receive attention, primarily relying on human assistance, and where not, limited by very strict sampling conditions. In this work, we formally improve on the state-of-the-art requirements and introduce an innovative algorithm capable of reconstructing closed curves directly on surfaces from a given sparse set of sample points. We extend and adapt a state-of-the-art planar curve reconstruction method to the realm of surfaces while dealing with the challenges arising from working on non-Euclidean domains. We demonstrate the robustness of our method by reconstructing multiple curves on various surface meshes. We explore novel potential applications of our approach, allowing for automated reconstruction of curves on Riemannian manifolds.
title Reconstructing Curves from Sparse Samples on Riemannian Manifolds
topic Computational Geometry
Graphics
68U05
I.3; I.3.5
url https://arxiv.org/abs/2404.09661