activity
20232026
collaborators

7 papers

math.MG2026

On the Duality of Coverings in Hilbert Geometry

Sunil Arya, David M. Mount

We prove polarity duality for covering problems in Hilbert geometry. Let and be convex bodies in where and $\operatorname{i…

cs.CG2026

Visualizing Higher Order Structures, Overlap Regions, and Clustering in the Hilbert Geometry

Hridhaan Banerjee, Soren Brown, June Cagan +9

Higher-order Voronoi diagrams and Delaunay mosaics in polygonal metrics have only recently been studied, yet no tools exist for visualizing them. We introduce a tool that fills thi…

cs.CG2025

Software for the Thompson and Funk Polygonal Geometry

Hridhaan Banerjee, Carmen Isabel Day, Auguste H. Gezalyan +6

Metric spaces defined within convex polygons, such as the Thompson, Funk, reverse Funk, and Hilbert metrics, are subjects of recent exploration and study in computational geometry.…

cs.CG2025

French Onion Soup, Ipelets for Points and Polygons

Klint Faber, Auguste H. Gezalyan, Adam Martinson +6

There are many structures, both classical and modern, involving point-sets and polygons whose deeper understanding can be facilitated through interactive visualizations. The Ipe ex…

cs.CG2024

On The Heine-Borel Property and Minimum Enclosing Balls

Hridhaan Banerjee, Carmen Isabel Day, Megan Hunleth +6

In this paper, we contribute a proof that minimum radius balls over metric spaces with the Heine-Borel property are always LP type. Additionally, we prove that weak metric spaces,…

cs.CG2024

Ipelets for the Convex Polygonal Geometry

Nithin Parepally, Ainesh Chatterjee, Auguste Gezalyan +5

There are many structures, both classical and modern, involving convex polygonal geometries whose deeper understanding would be facilitated through interactive visualizations. The…

cs.CG2023

Delaunay Triangulations in the Hilbert Metric

Auguste Gezalyan, Soo Kim, Carlos Lopez +3

The Hilbert metric is a distance function defined for points lying within the interior of a convex body. It arises in the analysis and processing of convex bodies, machine learning…