单位磁盘范围搜索和应用

Haitao Wang
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引用次数: 5

摘要

给定平面上一个由$n$点组成的集合$P$,我们考虑计算查询单元磁盘中$P$点的个数的问题(即所有查询磁盘具有相同的半径)。我们证明了平面上单纯形距离搜索的主要技术可以适用于这个问题。例如,通过调整马头\v{s} ek的结果,我们可以构建$O(n)$空间的数据结构,以便每个查询都可以在$O(\sqrt{n})$时间内得到回答。我们的技术改进了其他几个经典问题,如批量范围搜索、单位圆相交对的计数/报告、距离选择、离散二中心等。例如,给定一组$n$单位磁盘和平面上的一组$n$个点,批量范围搜索问题是计算每个磁盘上的点的数量。以前的工作[Katz和Sharir, 1997]在$O(n^{4/3}\log n)$时间内解决了这个问题,而我们的新算法在$O(n^{4/3})$时间内运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unit-Disk Range Searching and Applications
Given a set $P$ of $n$ points in the plane, we consider the problem of computing the number of points of $P$ in a query unit disk (i.e., all query disks have the same radius). We show that the main techniques for simplex range searching in the plane can be adapted to this problem. For example, by adapting Matou\v{s}ek's results, we can build a data structure of $O(n)$ space so that each query can be answered in $O(\sqrt{n})$ time. Our techniques lead to improvements for several other classical problems, such as batched range searching, counting/reporting intersecting pairs of unit circles, distance selection, discrete 2-center, etc. For example, given a set of $n$ unit disks and a set of $n$ points in the plane, the batched range searching problem is to compute for each disk the number of points in it. Previous work [Katz and Sharir, 1997] solved the problem in $O(n^{4/3}\log n)$ time while our new algorithm runs in $O(n^{4/3})$ time.
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