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Data Structures for Halfplane Proximity Queries and Incremental Voronoi Diagrams

机译:半平面接近查询和增量Voronoi图的数据结构

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We consider preprocessing a set S of n points in convex position in the plane into a data structure supporting queries of the following form: given a point q and a directed line in the plane, report the point of S that is farthest from (or, alternatively, nearest to) the point q among all points to the left of line . We present two data structures for this problem. The first data structure uses space and preprocessing time, and answers queries in time, for any . The second data structure uses space and polynomial preprocessing time, and answers queries in time. These are the first solutions to the problem with query time and space. The second data structure uses a new representation of nearest- and farthest-point Voronoi diagrams of points in convex position. This representation supports the insertion of new points in clockwise order using only amortized pointer changes, in addition to -time point-location queries, even though every such update may make combinatorial changes to the Voronoi diagram. This data structure is the first demonstration that deterministically and incrementally constructed Voronoi diagrams can be maintained in o(n) amortized pointer changes per operation while keeping -time point-location queries.
机译:我们考虑将平面中凸位置上的n个点的集合S预处理为支持以下形式的查询的数据结构:给定点q和平面中的有向线,报告最远的S点(或,或者,在行左侧的所有点中最靠近点q的位置。我们为这个问题提供了两种数据结构。第一个数据结构使用空间和预处理时间,并及时回答任何查询。第二种数据结构使用空间和多项式预处理时间,并及时回答查询。这些是查询时间和空间问题的第一个解决方案。第二个数据结构使用凸位置上点的最近和最远Voronoi图的新表示形式。此表示支持除-time点位置查询外,仅使用摊销指针更改按顺时针顺序插入新点,即使每次此类更新都可能对Voronoi图进行组合更改。这种数据结构是第一个演示,它可以确定性和增量构造的Voronoi图可以在每次操作的o(n)摊销指针更改中进行维护,同时保留时间点位置查询。

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