Approximate range searching using binary space partitions

  • Authors:
  • Mark de Berg;Micha Streppel

  • Affiliations:
  • Department of Computer Science, TU Eindhoven, Eindhoven, The Netherlands;Department of Computer Science, TU Eindhoven, Eindhoven, The Netherlands

  • Venue:
  • FSTTCS'04 Proceedings of the 24th international conference on Foundations of Software Technology and Theoretical Computer Science
  • Year:
  • 2004

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Abstract

We show how any BSP tree ${\mathcal T}_P$ for the endpoints of a set of n disjoint segments in the plane can be used to obtain a BSP tree of size $O(n.depth({\mathcal T}_P))$ for the segments themselves, such that the range-searching efficiency remains almost the same. We apply this technique to obtain a BSP tree of size O(n log n) such that ε-approximate range searching queries with any constant-complexity convex query range can be answered in O(minε0{1/ε+kε}log n) time, where kε is the number of segments intersecting the ε-extended range. The same result can be obtained for disjoint constant-complexity curves, if we allow the BSP to use splitting curves along the given curves. We also describe how to construct a linear-size BSP tree for low-density scenes consisting of n objects in ${\mathbb R}^{d}$ such that ε-approximate range searching with any constant-complexity convex query range can be done in $O(log n + {\rm min}_{\epsilon 0}{\{1/\epsilon^{(d-1)}+k_{\epsilon}\}})$ time.