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Faster Algorithms for Largest Empty Rectangles and Boxes

Author Timothy M. Chan



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Timothy M. Chan
  • Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA

Acknowledgements

I thank David Zheng for discussions on the 2D problem.

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Timothy M. Chan. Faster Algorithms for Largest Empty Rectangles and Boxes. In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 24:1-24:15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.SoCG.2021.24

Abstract

We revisit a classical problem in computational geometry: finding the largest-volume axis-aligned empty box (inside a given bounding box) amidst n given points in d dimensions. Previously, the best algorithms known have running time O(nlog²n) for d = 2 (by Aggarwal and Suri [SoCG'87]) and near n^d for d ≥ 3. We describe faster algorithms with running time - O(n2^{O(log^*n)}log n) for d = 2, - O(n^{2.5+o(1)}) time for d = 3, and - Õ(n^{(5d+2)/6}) time for any constant d ≥ 4. To obtain the higher-dimensional result, we adapt and extend previous techniques for Klee’s measure problem to optimize certain objective functions over the complement of a union of orthants.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Largest empty rectangle
  • largest empty box
  • Klee’s measure problem

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