The Largest Empty Sphere Problem in 3D Hollowed Point Clouds

Fuente: arXiv
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Main Author: Moriya, Netzer
Format: Preprint
Published: 2024
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author Moriya, Netzer
author_facet Moriya, Netzer
contents We introduce a new approach for the adaptation of the Maximal Internal Envelope method, extended to address the Largest Empty Sphere problem within unstructured 3D point clouds. We explore the identification of the Largest Empty Sphere by computing Convex Hull vertices and employing a Voidness Score based on Minimal Distance Scoring for optimal segment selection. The integration of Delaunay triangulation and Voronoi diagrams facilitates the initial identification of potential Largest Empty Sphere candidates. Our analysis reveals the method's efficacy and efficiency, often locating the Largest Empty Sphere in initial computational stages, suggesting a lower complexity than initially projected.
format Preprint
id arxiv_https___arxiv_org_abs_2401_07593
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Largest Empty Sphere Problem in 3D Hollowed Point Clouds
Moriya, Netzer
Optimization and Control
49Mxx
We introduce a new approach for the adaptation of the Maximal Internal Envelope method, extended to address the Largest Empty Sphere problem within unstructured 3D point clouds. We explore the identification of the Largest Empty Sphere by computing Convex Hull vertices and employing a Voidness Score based on Minimal Distance Scoring for optimal segment selection. The integration of Delaunay triangulation and Voronoi diagrams facilitates the initial identification of potential Largest Empty Sphere candidates. Our analysis reveals the method's efficacy and efficiency, often locating the Largest Empty Sphere in initial computational stages, suggesting a lower complexity than initially projected.
title The Largest Empty Sphere Problem in 3D Hollowed Point Clouds
topic Optimization and Control
49Mxx
url https://arxiv.org/abs/2401.07593