离散弗雷谢特距离奥秘

Boris Aronov, Tsuri Farhana, Matthew J. Katz, Indu Ramesh
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引用次数: 0

摘要

长度为 $n$ 的两条曲线之间的离散 Fr\'echet 距离不太可能在严格的亚二次方时间内计算出来。因此,我们考虑的是其中一条曲线 $P$ 是事先已知的情况。特别是,我们希望构建接近线性大小的数据结构(距离谕令),以支持在亚线性时间内对 $P$ 进行高效的距离查询。由于有证据表明,对于任意 $\alpha > 0$ 的长度为 $Theta(n^\alpha)$ 的查询曲线来说,这是不可能的,因此我们将重点放在(小)恒定长度的查询曲线上,对于这些曲线,我们能够设计出具有所需界值的距离表达式。我们将工具扩展到处理给定曲线的子曲线,甚至是给定几何树的任意顶点到顶点的子曲线。也就是说,我们构建了一个神谕,可以快速计算短多边形路径(查询)与预处理树中两个查询指定顶点之间路径的距离。此外,我们还定义了一个新的几何图形族--$t$-局部图(严格来说,它包含了具有恒定伸展性的几何跨线图族),对于这个族,也存在类似的神谕:我们可以预处理族中的图$G$,这样,给定一个查询线段和$G$中的一对顶点$u,v$,就可以快速计算出线段与$G$中任意$(u,v)$路径之间的最小离散Fr\'echet距离。如果 $t=1$,答案是精确的;如果 $t>1$,答案是近似的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discrete Fréchet Distance Oracles
It is unlikely that the discrete Fr\'echet distance between two curves of length $n$ can be computed in strictly subquadratic time. We thus consider the setting where one of the curves, $P$, is known in advance. In particular, we wish to construct data structures (distance oracles) of near-linear size that support efficient distance queries with respect to $P$ in sublinear time. Since there is evidence that this is impossible for query curves of length $\Theta(n^\alpha)$, for any $\alpha > 0$, we focus on query curves of (small) constant length, for which we are able to devise distance oracles with the desired bounds. We extend our tools to handle subcurves of the given curve, and even arbitrary vertex-to-vertex subcurves of a given geometric tree. That is, we construct an oracle that can quickly compute the distance between a short polygonal path (the query) and a path in the preprocessed tree between two query-specified vertices. Moreover, we define a new family of geometric graphs, $t$-local graphs (which strictly contains the family of geometric spanners with constant stretch), for which a similar oracle exists: we can preprocess a graph $G$ in the family, so that, given a query segment and a pair $u,v$ of vertices in $G$, one can quickly compute the smallest discrete Fr\'echet distance between the segment and any $(u,v)$-path in $G$. The answer is exact, if $t=1$, and approximate if $t>1$.
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