Surface reconstruction from point cloud using a semi-Lagrangian scheme with local interpolator
We propose a level set method to reconstruct unknown surfaces from point clouds, without assuming that the connections between points are known. We consider a variational formulation with a curvature constraint that minimizes the surface area weighted by the distance of the surface from the point cl...
Saved in:
Main Authors | , |
---|---|
Format | Journal Article |
Language | English |
Published |
29.10.2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | We propose a level set method to reconstruct unknown surfaces from point
clouds, without assuming that the connections between points are known. We
consider a variational formulation with a curvature constraint that minimizes
the surface area weighted by the distance of the surface from the point cloud.
More precisely we solve an equivalent advection-diffusion equation that governs
the evolution of an initial surface described implicitly by a level set
function. Among all the possible representations, we aim to compute the signed
distance function at least in the vicinity of the reconstructed surface. The
numerical method for the approximation of the solution is based on a
semi-Lagrangian scheme whose main novelty consists in its coupling with a local
interpolator instead of a global one, with the aim of saving computational
costs. In particular, we resort to a multi-linear interpolator and to a
Weighted Essentially Non-oscillatory one, to improve the accuracy of the
reconstruction. Special attention has been paid to the localization of the
method and to the development of fast algorithms that run in parallel,
resulting in faster reconstruction and thus the opportunity to easily improve
the resolution. A preprocessing of the point cloud data is also proposed to set
the parameters of the method. Numerical tests in two and three dimensions are
presented to evaluate the quality of the approximated solution and the
efficiency of the algorithm in terms of computational time. |
---|---|
DOI: | 10.48550/arxiv.2410.22205 |