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A Faster Convex-Hull Algorithm via Bucketing

机译:一种基于桶的更快的凸包算法

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In the convex-hull problem, in two-dimensional space, the task is to find, for a given sequence S of n points, the smallest convex polygon for which each point of S is either in its interior or on its boundary. In this paper, we propose a variant of the classical bucketing algorithm that (1) solves the convex-hull problem for any multiset of points, (2) uses O(n~(1/2)) words of extra space, (3) runs in O(n) expected time on points drawn independently and uniformly from a rectangle, and (4) requires O(nlgn) time in the worst case. Also, we perform experiments to compare bucketing to other alternatives that are known to work in linear expected time. In our tests, in the integer-coordinate setting, BUCKEYING was a clear winner compared to the considered competitors (plane-sweep, divide & conquer, quickhull, and throw-away).
机译:在凸包问题中,在二维空间中,任务是对于给定的n点序列S,找到最小的凸多边形,S的每个点都在其内部或边界上。在本文中,我们提出了经典存储算法的一种变体,其中(1)解决了任意多点集的凸包问题;(2)使用了多余空间的O(n〜(1/2))个单词;(3 )以O(n)的预期时间在从矩形独立且均匀绘制的点上运行,而(4)在最坏的情况下需要O(nlgn)的时间。此外,我们进行实验以将存储分区与已知可在线性预期时间内工作的其他替代方案进行比较。在我们的测试中,在整数坐标设置下,BUCKEYING与被认为是竞争对手(平面扫描,分而治之,快船体和抛弃式)相比,是明显的赢家。

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