Efficient Fr\'echet distance queries for segments
Maike Buchin, Ivor van der Hoog, Tim Ophelders, Lena Schlipf, Rodrigo, I. Silveira, Frank Staals

TL;DR
This paper introduces efficient data structures for fast exact Fréchet distance queries between a polygonal curve and query segments of arbitrary orientation, improving space and time complexity over previous methods.
Contribution
It presents novel data structures enabling rapid Fréchet distance computations for arbitrary oriented segments and subcurve queries, with significant improvements in efficiency and generality.
Findings
Achieved $O(n ext{log} n)$ space and $O( ext{log} n)$ query time for horizontal segments.
Extended query capabilities to include subcurve segments with $O(n ext{log}^2 n)$ space and $O( ext{log}^3 n)$ time.
Provided applications for local curve simplification and segment translation minimization.
Abstract
We study the problem of constructing a data structure that can store a two-dimensional polygonal curve , such that for any query segment one can efficiently compute the Fr\'{e}chet distance between and . First we present a data structure of size that can compute the Fr\'{e}chet distance between and a horizontal query segment in time, where is the number of vertices of . In comparison to prior work, this significantly reduces the required space. We extend the type of queries allowed, as we allow a query to be a horizontal segment together with two points (not necessarily vertices), and ask for the Fr\'{e}chet distance between and the curve of in between and . Using storage, such queries take time, simplifying and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
