Four Soviets Walk the Dog: Improved Bounds for Computing the Frechet Distance

作者：Buchin Kevin^*; Buchin Maike; Meulemans Wouter; Mulzer Wolfgang

来源：Discrete & Computational Geometry, 2017, 58(1): 180-216.

DOI：10.1007/s00454-017-9878-7

• Frechet distance
• Word RAM
• Pointer machine
• Algebraic decision tree
• Four Russian trick

Given two polygonal curves in the plane, there are many ways to define a notion of similarity between them. One popular measure is the Frechet distance. Since it was proposed by Alt and Godau in 1992, many variants and extensions have been studied. Nonetheless, even more than 20 years later, the original O (n(2) log n) algorithm by Alt and Godau for computing the Frechet distance remains the state of the art (here, n denotes the number of edges on each curve). This has led Helmut Alt to conjecture that the associated decision problem is 3SUM-hard. In recent work, Agarwal et al. show how to break the quadratic barrier for the discrete version of the Frechet distance, where one considers sequences of points instead of polygonal curves. Building on their work, we give a randomized algorithm to compute the Frechet distance between two polygonal curves in time O (n(2) root log log n)(3/2)) on a pointer machine and in time O(n(2)(log log n)(2)) on a word RAM. Furthermore, we show that there exists an algebraic decision tree for the decision problem of depth O(n(2-epsilon)), for some epsilon > 0. We believe that this reveals an intriguing new aspect of this well- studied problem. Finally, we show how to obtain the first subquadratic algorithm for computing the weak Frechet distance on a word RAM.

• 出版日期2017-7