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Main Authors: Bednarczuk, Ewa, Bieńkowski, Rafał, Kłopotek, Robert, Kryński, Jan, Leśsniewski, Krzysztof, Rutkowski, Krzysztof, Szelachowska, Małgorzata
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2601.07621
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author Bednarczuk, Ewa
Bieńkowski, Rafał
Kłopotek, Robert
Kryński, Jan
Leśsniewski, Krzysztof
Rutkowski, Krzysztof
Szelachowska, Małgorzata
author_facet Bednarczuk, Ewa
Bieńkowski, Rafał
Kłopotek, Robert
Kryński, Jan
Leśsniewski, Krzysztof
Rutkowski, Krzysztof
Szelachowska, Małgorzata
contents We address the problem of comparing and aligning spatial point configurations in $\mathbb{R}^3$ arising from structured geometric patterns. Each pattern is decomposed into arms along which we define a normalized finite-difference operator measuring local variations of the height component with respect to the planar geometry of the pattern. This quantity provides a parametrization-independent local descriptor that complements global similarity measures. In particular, it integrates naturally with Wasserstein-type distances for comparing point distributions and with Procrustes analysis for rigid alignment of geometric structures.
format Preprint
id arxiv_https___arxiv_org_abs_2601_07621
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Searching point patterns in point clouds describing local topography
Bednarczuk, Ewa
Bieńkowski, Rafał
Kłopotek, Robert
Kryński, Jan
Leśsniewski, Krzysztof
Rutkowski, Krzysztof
Szelachowska, Małgorzata
Computational Geometry
Optimization and Control
We address the problem of comparing and aligning spatial point configurations in $\mathbb{R}^3$ arising from structured geometric patterns. Each pattern is decomposed into arms along which we define a normalized finite-difference operator measuring local variations of the height component with respect to the planar geometry of the pattern. This quantity provides a parametrization-independent local descriptor that complements global similarity measures. In particular, it integrates naturally with Wasserstein-type distances for comparing point distributions and with Procrustes analysis for rigid alignment of geometric structures.
title Searching point patterns in point clouds describing local topography
topic Computational Geometry
Optimization and Control
url https://arxiv.org/abs/2601.07621