Translation Invariant Fr\'echet Distance Queries

TL;DR

This paper presents an efficient preprocessing method for horizontal trajectory segments that enables quick computation of the translation-invariant Fréchet distance between subtrajectories and query segments, advancing the understanding of this problem.

Contribution

It introduces a preprocessing algorithm that allows fast translation-invariant Fréchet distance queries for horizontal segments, a less explored area in trajectory similarity measures.

Findings

Preprocessing time is O(n^2 log^2 n)

Query time is polylogarithmic in n

Supports efficient similarity queries for subtrajectories and horizontal segments

Abstract

The Fr\'echet distance is a popular similarity measure between curves. For some applications, it is desirable to match the curves under translation before computing the Fr\'echet distance between them. This variant is called the Translation Invariant Fr\'echet distance, and algorithms to compute it are well studied. The query version, finding an optimal placement in the plane for a query segment where the Fr\'echet distance becomes minimized, is much less well understood. We study Translation Invariant Fr\'echet distance queries in a restricted setting of horizontal query segments. More specifically, we preprocess a trajectory in $\mathcal O(n^2 \log^2 n) $ time and $\mathcal O(n^{3/2})$ space, such that for any subtrajectory and any horizontal query segment we can compute their Translation Invariant Fr\'echet distance in $\mathcal O(\text{polylog } n)$ time. We hope this will be a step towards answering Translation Invariant Fr\'echet queries between arbitrary trajectories.