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        <identifier>oai:drops-oai.dagstuhl.de:26422</identifier>
        <datestamp>2026-09-05T19:42:57Z</datestamp>
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          <dc:title>Visibility Queries in Simple Polygons</dc:title>
          <dc:creator>Bhore, Sujoy</dc:creator>
          <dc:creator>Liu, Chih-Hung</dc:creator>
          <dc:creator>Naredla, Anurag Murty</dc:creator>
          <dc:creator>Nekrich, Yakov</dc:creator>
          <dc:creator>Oh, Eunjin</dc:creator>
          <dc:creator>van Renssen, André</dc:creator>
          <dc:creator>Staals, Frank</dc:creator>
          <dc:creator>Wang, Haitao</dc:creator>
          <dc:creator>Xue, Jie</dc:creator>
          <dc:subject>simple polygons</dc:subject>
          <dc:subject>visibility polygons</dc:subject>
          <dc:subject>visibility queries</dc:subject>
          <dc:subject>polygon decompositions</dc:subject>
          <dc:description>Given a simple polygon P with n vertices, we consider the problem of constructing a data structure for visibility queries: for any query point q ∈ P, compute the visibility polygon of q in P. To obtain O(log n + k) query time, where k is the size of the visibility polygon of q, the previous best result requires O(n³) space. In this paper, we propose a new data structure that uses O(n^{2+ε}) space, for any ε &gt; 0, while achieving the same query time. If only O(n²) space is available, the best known result provides O(log² n + k) query time. We improve this to O(log n log log n + k) time. When restricted to o(n²) space, the only previously known approach, aside from the O(n)-time algorithm that computes the visibility polygon without preprocessing, is an O(n)-space data structure that supports O(k log n)-time queries. We construct a data structure using O(n log n) space that answers visibility queries in O(n^{1/2+ε} + k) time. In addition, for the special case in which q lies on the boundary of P, we build a data structure of O(n log n) space supporting O(log² n + k) query time; alternatively, we achieve O(log n + k) query time using O(n^{1+ε}) space. To achieve our results, we propose a new method for decomposing simple polygons, which may be of independent interest.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Sujoy Bhore and Chih-Hung Liu and Anurag Murty Naredla and Yakov Nekrich and Eunjin Oh and André van Renssen and Frank Staals and Haitao Wang and Jie Xue</dc:contributor>
          <dc:date>2026</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 374, 53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ICALP.2026.33</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-264222</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2026.33</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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