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        <identifier>oai:drops-oai.dagstuhl.de:22184</identifier>
        <datestamp>2024-12-04T06:53:45Z</datestamp>
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          <dc:title>Data Structures for Approximate Fréchet Distance for Realistic Curves</dc:title>
          <dc:creator>van der Hoog, Ivor</dc:creator>
          <dc:creator>Rotenberg, Eva</dc:creator>
          <dc:creator>Wong, Sampson</dc:creator>
          <dc:subject>Fréchet distance</dc:subject>
          <dc:subject>data structures</dc:subject>
          <dc:subject>approximation algorithms</dc:subject>
          <dc:description>The Fréchet distance is a popular distance measure between curves P and Q. Conditional lower bounds prohibit (1+ε)-approximate Fréchet distance computations in strongly subquadratic time, even when preprocessing P using any polynomial amount of time and space. As a consequence, the Fréchet distance has been studied under realistic input assumptions, for example, assuming both curves are c-packed.&#13;
In this paper, we study c-packed curves in Euclidean space ℝ^d and in general geodesic metrics 𝒳. In ℝ^d, we provide a nearly-linear time static algorithm for computing the (1+ε)-approximate continuous Fréchet distance between c-packed curves. Our algorithm has a linear dependence on the dimension d, as opposed to previous algorithms which have an exponential dependence on d.&#13;
In general geodesic metric spaces X, little was previously known. We provide the first data structure, and thereby the first algorithm, under this model. Given a c-packed input curve P with n vertices, we preprocess it in O(n log n) time, so that given a query containing a constant ε and a curve Q with m vertices, we can return a (1+ε)-approximation of the discrete Fréchet distance between P and Q in time polylogarithmic in n and linear in m, 1/ε, and the realism parameter c.&#13;
Finally, we show several extensions to our data structure; to support dynamic extend/truncate updates on P, to answer map matching queries, and to answer Hausdorff distance queries.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Ivor van der Hoog and Eva Rotenberg and Sampson Wong</dc:contributor>
          <dc:date>2024</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 322, 35th International Symposium on Algorithms and Computation (ISAAC 2024)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ISAAC.2024.56</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-221846</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2024.56</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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