Boundary Estimation from Point Clouds: Algorithms, Guarantees and Applications

• Main Authors: Calder, J. (Author), Park, S. (Author), Slepčev, D. (Author)
• Format: Article
• Language: English
• Published: Springer 2022
• Subjects: Boundary detection; Boundary estimation; Boundary value problems; Boundary-points; Distance to boundary; Error estimates; Geometrical optics; Meshfree methods; Normal vector; PDE on point cloud; PDE on point clouds; Point-clouds; Sample point
• Online Access: View Fulltext in Publisher

 We investigate identifying the boundary of a domain from sample points in the domain. We introduce new estimators for the normal vector to the boundary, distance of a point to the boundary, and a test for whether a point lies within a boundary strip. The estimators can be efficiently computed and are more accurate than the ones present in the literature. We provide rigorous error estimates for the estimators. Furthermore we use the detected boundary points to solve boundary-value problems for PDE on point clouds. We prove error estimates for the Laplace and eikonal equations on point clouds. Finally we provide a range of numerical experiments illustrating the performance of our boundary estimators, applications to PDE on point clouds, and tests on image data sets. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.