一维不确定曲线间Fréchet距离的计算

IF 0.4 4区 计算机科学 Q4 MATHEMATICS
Kevin Buchin , Maarten Löffler , Tim Ophelders , Aleksandr Popov , Jérôme Urhausen , Kevin Verbeek
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引用次数: 1

摘要

我们考虑计算两条曲线之间的Fréchet距离的问题,对于这两条曲线,顶点的确切位置是未知的。每个顶点都可以放置在该顶点的给定不确定性区域中,目标是放置顶点以最小化Fréchet距离。这个问题最近在2D中被证明是NP难的,并且根本不清楚如何计算最优顶点位置。我们提出了这个问题的第一个通用算法框架。我们证明了它导致了一维曲线的多项式时间算法,其中区间是不确定区域。相反,我们证明了在1D中,在放置顶点以最大化Fréchet距离的情况下,该问题是NP困难的。我们还研究了不确定曲线之间的弱Fréchet距离。虽然找到顶点的最佳位置似乎比正则Fréchet距离更困难——事实上,我们可以很容易地证明这个问题在2D中是NP难的——但在1D中顶点的最佳放置可以在多项式时间内计算。最后,我们研究了离散弱Fréchet距离,令人惊讶的是,该问题在1D中已经是NP困难的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computing the Fréchet distance between uncertain curves in one dimension

We consider the problem of computing the Fréchet distance between two curves for which the exact locations of the vertices are unknown. Each vertex may be placed in a given uncertainty region for that vertex, and the objective is to place vertices so as to minimise the Fréchet distance. This problem was recently shown to be NP-hard in 2D, and it is unclear how to compute an optimal vertex placement at all.

We present the first general algorithmic framework for this problem. We prove that it results in a polynomial-time algorithm for curves in 1D with intervals as uncertainty regions. In contrast, we show that the problem is NP-hard in 1D in the case that vertices are placed to maximise the Fréchet distance.

We also study the weak Fréchet distance between uncertain curves. While finding the optimal placement of vertices seems more difficult than the regular Fréchet distance—and indeed we can easily prove that the problem is NP-hard in 2D—the optimal placement of vertices in 1D can be computed in polynomial time. Finally, we investigate the discrete weak Fréchet distance, for which, somewhat surprisingly, the problem is NP-hard already in 1D.

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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
43
审稿时长
>12 weeks
期刊介绍: Computational Geometry is a forum for research in theoretical and applied aspects of computational geometry. The journal publishes fundamental research in all areas of the subject, as well as disseminating information on the applications, techniques, and use of computational geometry. Computational Geometry publishes articles on the design and analysis of geometric algorithms. All aspects of computational geometry are covered, including the numerical, graph theoretical and combinatorial aspects. Also welcomed are computational geometry solutions to fundamental problems arising in computer graphics, pattern recognition, robotics, image processing, CAD-CAM, VLSI design and geographical information systems. Computational Geometry features a special section containing open problems and concise reports on implementations of computational geometry tools.
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