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Kinetic Medians and kd-Trees

机译:运动中位数和kd树

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We propose algorithms for maintaining two variants of kd-trees of a set of moving points in the plane. A pseudo kd-tree allows the number of points stored in the two children to differ by a constant factor. An overlapping kd-tree allows the bounding boxes of two children to overlap. We show that both of them support range search operations in O(n~(1/2+ε)) time, where ε only depends on the approximation precision. As the points move, we use event-based kinetic data structures to update the tree when necessary. Both trees undergo only a quadratic number of events, which is optimal, and the update cost for each event is only poly-logarithmic. To maintain the pseudo kd-tree, we develop algorithms for computing an approximate median level of a line arrangement, which itself is of great interest. We show that the computation of the approximate median level of a set of lines or line segments can be done in an online fashion smoothly, i.e., there are no expensive updates for any events. For practical consideration, we study the case in which there axe speed-limit restrictions or smooth trajectory requirements. The maintenance of the pseudo kd-tree, as a consequence of the approximate median algorithm, can also adapt to those restrictions.
机译:我们提出了用于维护平面中一组移动点的kd树的两个变体的算法。伪kd树允许两个子节点中存储的点数相差一个常数。重叠的kd树允许两个孩子的边界框重叠。我们证明它们都支持O(n〜(1/2 +ε))时间范围内的搜索操作,其中ε仅取决于近似精度。随着点的移动,我们在必要时使用基于事件的动力学数据结构来更新树。两棵树仅经历二次事件,这是最佳事件,每个事件的更新成本仅为对数。为了维护伪kd树,我们开发了用于计算行排列的近似中值水平的算法,这本身引起了人们的极大兴趣。我们表明,可以以在线方式平稳地完成一组线或线段的近似中值水平的计算,即没有任何事件的昂贵更新。出于实际考虑,我们研究存在轴速限制或平滑轨迹要求的情况。作为近似中值算法的结果,伪kd树的维护也可以适应这些限制。

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