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Consider a 2D coordinate space with a set of red and a set of blue points. We define a scenic point as a point that is equidistant to a red point and a blue point. The set of contiguous scenic points form a scenic path. The perpendicular…

Computational Geometry · Computer Science 2023-06-09 Loay Rashid , Lini Thomas , Kamalakar Karlapalem

Consider finitely many points in a geodesic space. If the distance of two points is less than a fixed threshold, then we regard these two points as "near". Connecting near points with edges, we obtain a simple graph on the points, which is…

Combinatorics · Mathematics 2020-09-15 Masamichi Kuroda , Shuhei Tsujie

We discuss the enumeration of planar graphs using bijections with suitably decorated trees, which allow for keeping track of the geodesic distances between faces of the graph. The corresponding generating functions obey non-linear recursion…

Combinatorics · Mathematics 2007-05-23 P. Di Francesco

What is the shortest path between two data points lying in a high-dimensional space? While the answer is trivial in Euclidean geometry, it becomes significantly more complex when the data lies on a curved manifold -- requiring a Riemannian…

Machine Learning · Computer Science 2025-11-04 Louis Béthune , David Vigouroux , Yilun Du , Rufin VanRullen , Thomas Serre , Victor Boutin

We use the $p$-Laplacian with large $p$-values in order to approximate geodesic distances to features on surfaces. This differs from Fayolle and Belyaev's (2018) [1] computational results using the $p$-Laplacian for the distance-to-surface…

Graphics · Computer Science 2025-05-22 Hannah Potgieter , Razvan C. Fetecau , Steven J. Ruuth

In this work we discuss the notion of stationary curves of the length functional, the so-called (weak) geodesics, on a Riemannian manifold. The motivation behind this work is to give a detailed description of many key concepts from…

Differential Geometry · Mathematics 2026-01-12 Tobias Starke

In this paper, we leverage the properties of non-Euclidean Geometry to define the Geodesic distance (GD) on the space of statistical manifolds. The Geodesic distance is a real and intuitive similarity measure that is a good alternative to…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Zakariae Abbad , Ahmed Drissi El Maliani , Said Ouatik El Alaoui , Mohammed El Hassouni

We derive various inequalities involving the intersection number of the curves contained in geodesics and tight geodesics in the curve graph. While there already exist such inequalities on tight geodesics, our method applies in the setting…

Geometric Topology · Mathematics 2016-03-14 Yohsuke Watanabe

The propagation of a light ray in thin layer (film) within geometrical optics is considered. It is assumed that the ray is captured inside the layer due to reflecting walls or total internal reflection (in the case of a dielectric layer).…

Optics · Physics 2018-12-12 Tomasz Radozycki

This paper is a companion paper to [Lipman and Daubechies 2011]. We provide numerical procedures and algorithms for computing the alignment of and distance between two disk type surfaces. We provide a convergence analysis of the discrete…

Numerical Analysis · Mathematics 2014-02-18 Yaron Lipman , Jesus Puente , Ingrid Daubechies

A distance-squared function is one of the most significant functions in the application of singularity theory to differential geometry. Moreover, distance-squared mappings are naturally extended mappings of distance-squared functions,…

Differential Geometry · Mathematics 2018-01-08 Shunsuke Ichiki

Physical geometry studies mutual disposition of geometrical objects and points in space, or space-time, which is described by the distance function $ d$, or by the world function $\sigma =d^{2}/2$. One suggests a new general method of the…

General Mathematics · Mathematics 2007-05-23 Yuri A. Rylov

Many applications of geometry modeling and computer graphics necessite accurate curvature estimations of curves on the plane or on manifolds. In this paper, we define the notion of the discrete geodesic curvature of a geodesic polygon on a…

Numerical Analysis · Mathematics 2020-11-26 Aziz Ikemakhen , Mohamed Bellaihou

Geometry and topology have generated impacts far beyond their pure mathematical primitive, providing a solid foundation for many applicable tools. Typically, real-world data are represented as vectors, forming a linear subspace for a given…

Quantum Physics · Physics 2024-05-01 Nhat A. Nghiem

The minimal geodesic models based on the Eikonal equations are capable of finding suitable solutions in various image segmentation scenarios. Existing geodesic-based segmentation approaches usually exploit image features in conjunction with…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Da Chen , Jean-Marie Mirebeau , Minglei Shu , Xuecheng Tai , Laurent D. Cohen

Graph theoretical problems based on shortest paths are at the core of research due to their theoretical importance and applicability. This paper deals with the geodetic number which is a global measure for simple connected graphs and it…

Data Structures and Algorithms · Computer Science 2020-11-24 Ahmad T. Anaqreh , Boglarka G. -Toth , Tamas Vinko

On a hyperbolic Riemann surface, given two simple closed geodesics that intersect $n$ times, we address the question of a sharp lower bound $L_n$ on the length attained by the longest of the two geodesics. We show the existence of a surface…

Differential Geometry · Mathematics 2007-05-23 Thomas Gauglhofer , Hugo Parlier

Let $P$ be a simple polygon with $n$ vertices. For any two points in $P$, the geodesic distance between them is the length of the shortest path that connects them among all paths contained in $P$. Given a set $S$ of $m$ sites being a subset…

Computational Geometry · Computer Science 2018-09-10 Luis Barba

This note is an invitation to the theory of geometric functions. The foundation techniques and some of the developments in the field are explained with the mindset that the audience is principally young researchers wishing to understand…

Complex Variables · Mathematics 2009-10-21 K. O. Babalola

Real world data often lie on low-dimensional Riemannian manifolds embedded in high-dimensional spaces. This motivates learning degenerate normalizing flows that map between the ambient space and a low-dimensional latent space. However, if…

Machine Learning · Computer Science 2026-04-14 Hanlin Yu , Søren Hauberg , Marcelo Hartmann , Arto Klami , Georgios Arvanitidis