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On Ray Shooting for Triangles in 3-Space and Related Problems

Authors Esther Ezra , Micha Sharir

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Author Details

Esther Ezra
  • School of Computer Science, Bar Ilan University, Ramat Gan, Israel
Micha Sharir
  • School of Computer Science, Tel Aviv University, Israel

Funding

  • Ezra, Esther: Work partially supported by NSF CAREER under grant CCF:AF-1553354 and by Grant 824/17 from the Israel Science Foundation.
  • Sharir, Micha: Work partially supported by ISF Grant 260/18, by grant 1367/2016 from the German-Israeli Science Foundation (GIF), and by Blavatnik Research Fund in Computer Science at Tel Aviv University.

Acknowledgements

We wish to thank Pankaj Agarwal for the useful interaction concerning certain aspects of the range searching problem.

Cite AsGet BibTex

Esther Ezra and Micha Sharir. On Ray Shooting for Triangles in 3-Space and Related Problems. In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 34:1-34:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.SoCG.2021.34

Abstract

We consider several problems that involve lines in three dimensions, and present improved algorithms for solving them. The problems include (i) ray shooting amid triangles in ℝ³, (ii) reporting intersections between query lines (segments, or rays) and input triangles, as well as approximately counting the number of such intersections, (iii) computing the intersection of two nonconvex polyhedra, (iv) detecting, counting, or reporting intersections in a set of lines in ℝ³, and (v) output-sensitive construction of an arrangement of triangles in three dimensions. Our approach is based on the polynomial partitioning technique. For example, our ray-shooting algorithm processes a set of n triangles in ℝ³ into a data structure for answering ray shooting queries amid the given triangles, which uses O(n^{3/2+ε}) storage and preprocessing, and answers a query in O(n^{1/2+ε}) time, for any ε > 0. This is a significant improvement over known results, obtained more than 25 years ago, in which, with this amount of storage, the query time bound is roughly n^{5/8}. The algorithms for the other problems have similar performance bounds, with similar improvements over previous results. We also derive a nontrivial improved tradeoff between storage and query time. Using it, we obtain algorithms that answer m queries on n objects in max{O(m^{2/3}n^{5/6+{ε}} + n^{1+ε}), O(m^{5/6+ε}n^{2/3} + m^{1+ε})} time, for any ε > 0, again an improvement over the earlier bounds.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Ray shooting
  • Three dimensions
  • Polynomial partitioning
  • Tradeoff

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