Approximating the (Continuous) Fréchet Distance

Authors Connor Colombe, Kyle Fox

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Connor Colombe
  • The University of Texas at Austin, TX, USA
Kyle Fox
  • The University of Texas at Dallas, Richardson, TX, USA


Most of this work was done while the first author was a student at the University of Texas at Dallas. The authors would like to thank Karl Bringmann and Marvin Künnemann for some helpful discussions concerning turning an approximate decision procedure into a proper approximation algorithm.

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Connor Colombe and Kyle Fox. Approximating the (Continuous) Fréchet Distance. In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 26:1-26:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


We describe the first strongly subquadratic time algorithm with subexponential approximation ratio for approximately computing the Fréchet distance between two polygonal chains. Specifically, let P and Q be two polygonal chains with n vertices in d-dimensional Euclidean space, and let α ∈ [√n, n]. Our algorithm deterministically finds an O(α)-approximate Fréchet correspondence in time O((n³ / α²) log n). In particular, we get an O(n)-approximation in near-linear O(n log n) time, a vast improvement over the previously best know result, a linear time 2^O(n)-approximation. As part of our algorithm, we also describe how to turn any approximate decision procedure for the Fréchet distance into an approximate optimization algorithm whose approximation ratio is the same up to arbitrarily small constant factors. The transformation into an approximate optimization algorithm increases the running time of the decision procedure by only an O(log n) factor.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Approximation algorithms analysis
  • Fréchet distance
  • approximation algorithm
  • approximate decision procedure


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