Jaywalking your Dog - Computing the Fr\'echet Distance with Shortcuts

TL;DR

This paper introduces a robust variant of the Fréchet distance allowing shortcuts, along with near-linear time algorithms and data structures for efficient approximation and querying, handling noise and outliers in curve similarity measures.

Contribution

The paper presents the first efficient algorithms and data structures for computing and approximating the shortcut Fréchet distance, enhancing robustness against noise and outliers.

Findings

Achieves a (3+ε)-approximation in near-linear time for curves with shortcuts.

Develops data structures for approximate Fréchet distance queries between subcurves and line segments.

Provides a permutation-based method to approximate a curve with a small number of vertices.

Abstract

The similarity of two polygonal curves can be measured using the Fr\'echet distance. We introduce the notion of a more robust Fr\'echet distance, where one is allowed to shortcut between vertices of one of the curves. This is a natural approach for handling noise, in particular batched outliers. We compute a (3+\eps)-approximation to the minimum Fr\'echet distance over all possible such shortcuts, in near linear time, if the curve is c-packed and the number of shortcuts is either small or unbounded. To facilitate the new algorithm we develop several new tools: (A) A data structure for preprocessing a curve (not necessarily c-packed) that supports (1+\eps)-approximate Fr\'echet distance queries between a subcurve (of the original curve) and a line segment. (B) A near linear time algorithm that computes a permutation of the vertices of a curve, such that any prefix of 2k-1 vertices of this permutation, form an optimal approximation (up to a constant factor) to the original curve compared to any polygonal curve with k vertices, for any k > 0. (C) A data structure for preprocessing a curve that supports approximate Fr\'echet distance queries between a subcurve and query polygonal curve. The query time depends quadratically on the complexity of the query curve, and only (roughly) logarithmically on the complexity of the original curve. To our knowledge, these are the first data structures to support these kind of queries efficiently.