在 4 LoC 中快速遛青蛙

Nis Meinert
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引用次数: 0

摘要

给定两条多边形曲线,有许多方法可以定义它们之间的相似性概念。其中一种流行的度量方法是弗雷谢特距离,它有许多理想的特性,但计算起来却出了名的昂贵,特别是对于非三维度量。1994 年,Eiter 和 Mannila 引入了离散的 Fr\'echet 距离,它更容易实现,并以二次运行时间开销近似连续的 Fr\'echet 距离。我们展示了仅有四行代码的算法实现,并展示了我们的算法在现代 CPU 和 GPGPU 上快速运行的基准测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Walking Your Frog Fast in 4 LoC
Given two polygonal curves, there are many ways to define a notion of similarity between them. One popular measure is the Fr\'echet distance which has many desirable properties but is notoriously expensive to calculate, especially for non-trivial metrics. In 1994, Eiter and Mannila introduced the discrete Fr\'echet distance which is much easier to implement and approximates the continuous Fr\'echet distance with a quadratic runtime overhead. However, this algorithm relies on recursions and is not well suited for modern hardware. To that end, we introduce the Fast Fr\'echet Distance algorithm, a recursion-free algorithm that calculates the discrete Fr\'echet distance with a linear memory overhead and that can utilize modern hardware more effectively. We showcase an implementation with only four lines of code and present benchmarks of our algorithm running fast on modern CPUs and GPGPUs.
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