mlsanityData to 7 Oct 2026

A Survey of Algorithms for Geodesic Paths and Distances

arXiv 2007.10430 ↗First posted 20 Jul 2020cs.GR cs.CGcited by 11

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Abstract (arXiv)

Numerical computation of shortest paths or geodesics on curved domains, as well as the associated geodesic distance, arises in a broad range of applications across digital geometry processing, scientific computing, computer graphics, and computer vision. Relative to Euclidean distance computation, these tasks are complicated by the influence of curvature on the behavior of shortest paths, as well as the fact that the representation of the domain may itself be approximate. In spite of the difficulty of this problem, recent literature has developed a wide variety of sophisticated methods that enable rapid queries of geodesic information, even on relatively large models. This survey reviews the major categories of approaches to the computation of geodesic paths and distances, highlighting common themes and opportunities for future improvement.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 3; 2026: 4.

11 papers.