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相关论文: Locality-sensitive hashing of curves

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We study the Fr\'echet queries problem. It is a data structure problem, where we are given a set $S$ of $n$ polygonal curves and a distance threshold $\rho$. The data structure should support queries with a polygonal curve $q$ for the…

计算几何 · 计算机科学 2024-01-09 Lotte Blank , Anne Driemel

Given a curve $P$ with points in $\mathbb{R}^d$ in a streaming fashion, and parameters $\varepsilon>0$ and $k$, we construct a distance oracle that uses $O(\frac{1}{\varepsilon})^{kd}\log\varepsilon^{-1}$ space, and given a query curve $Q$…

计算几何 · 计算机科学 2020-07-22 Arnold Filtser , Omrit Filtser

The Fr\'echet distance is a popular distance measure for curves. We study the problem of clustering time series under the Fr\'echet distance. In particular, we give $(1+\varepsilon)$-approximation algorithms for variations of the following…

计算几何 · 计算机科学 2015-12-15 Anne Driemel , Amer Krivošija , Christian Sohler

A suitable measure for the similarity of shapes represented by parameterized curves or surfaces is the Fr\'echet distance. Whereas efficient algorithms are known for computing the Fr\'echet distance of polygonal curves, the same problem for…

计算几何 · 计算机科学 2007-05-23 Helmut Alt , Maike Buchin

Computing approximate nearest neighbors in high dimensional spaces is a central problem in large-scale data mining with a wide range of applications in machine learning and data science. A popular and effective technique in computing…

机器学习 · 计算机科学 2019-10-29 Lin Chen , Hossein Esfandiari , Thomas Fu , Vahab S. Mirrokni

The Fr\'echet distance provides a natural and intuitive measure for the popular task of computing the similarity of two (polygonal) curves. While a simple algorithm computes it in near-quadratic time, a strongly subquadratic algorithm…

计算几何 · 计算机科学 2019-01-08 Karl Bringmann , Marvin Künnemann , André Nusser

Locality-sensitive hashing~[Indyk,Motwani'98] is a classical data structure for approximate nearest neighbor search. It allows, after a close to linear time preprocessing of the input dataset, to find an approximately nearest neighbor of…

数据结构与算法 · 计算机科学 2024-06-18 Michael Kapralov , Mikhail Makarov , Christian Sohler

We show an optimal data-dependent hashing scheme for the approximate near neighbor problem. For an $n$-point data set in a $d$-dimensional space our data structure achieves query time $O(d n^{\rho+o(1)})$ and space $O(n^{1+\rho+o(1)} +…

数据结构与算法 · 计算机科学 2015-07-17 Alexandr Andoni , Ilya Razenshteyn

Let $m$ and $n$ be the numbers of vertices of two polygonal curves in $\mathbb{R}^d$ for any fixed $d$ such that $m \leq n$. Since it was known in 1995 how to compute the Fr\'{e}chet distance of these two curves in $O(mn\log (mn))$ time, it…

计算几何 · 计算机科学 2024-10-21 Siu-Wing Cheng , Haoqiang Huang

In 2012 Driemel et al. \cite{DBLP:journals/dcg/DriemelHW12} introduced the concept of $c$-packed curves as a realistic input model. In the case when $c$ is a constant they gave a near linear time $(1+\varepsilon)$-approximation algorithm…

计算几何 · 计算机科学 2020-09-18 Joachim Gudmundsson , Yuan Sha , Sampson Wong

We describe the first strongly subquadratic time algorithm with subexponential approximation ratio for approximately computing the Fr\'echet distance between two polygonal chains. Specifically, let $P$ and $Q$ be two polygonal chains with…

计算几何 · 计算机科学 2021-03-30 Connor Colombe , Kyle Fox

The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a general technique for constructing a data structure to answer approximate near neighbor queries by using a distribution $\mathcal{H}$ over locality-sensitive hash…

数据结构与算法 · 计算机科学 2018-02-19 Tobias Christiani

For many shape analysis problems in computer vision and scientific imaging (e.g., computational anatomy, morphological cytometry), the ability to align two closed curves in the plane is crucial. In this paper, we concentrate on rigidly…

微分几何 · 数学 2025-01-30 Günay Dogan , Javier Bernal , Charles Hagwood

Since its introduction to computational geometry by Alt and Godau in 1992, the Fr\'echet distance has been a mainstay of algorithmic research on curve similarity computations. The focus of the research has been on comparing polygonal…

计算几何 · 计算机科学 2024-01-09 Jacobus Conradi , Anne Driemel , Benedikt Kolbe

We show that a variant of the continuous Frechet distance between polygonal curves can be computed using essentially the same algorithm used to solve the discrete version. The new variant is not necessarily monotone, but this shortcoming…

计算几何 · 计算机科学 2026-01-01 Sariel Har-Peled , Benjamin Raichel , Eliot W. Robson

The fine-grained complexity of computing the Fr\'echet distance has been a topic of much recent work, starting with the quadratic SETH-based conditional lower bound by Bringmann from 2014. Subsequent work established largely the same…

计算几何 · 计算机科学 2024-08-05 Lotte Blank , Anne Driemel

We study approximating the continuous Fr\'echet distance of two curves with complexity $n$ and $m$, under the assumption that only one of the two curves is $c$-packed. Driemel, Har{-}Peled and Wenk DCG'12 studied Fr\'echet distance…

计算几何 · 计算机科学 2025-12-23 Jacobus Conradi , Ivor van der Hoog , Thijs van der Horst , Tim Ophelders

We present efficient data structures for approximate nearest neighbor searching and approximate 2-point shortest path queries in a two-dimensional polygonal domain $P$ with $n$ vertices. Our goal is to store a dynamic set of $m$ point sites…

计算几何 · 计算机科学 2026-03-13 Joost van der Laan , Frank Staals , Lorenzo Theunissen

We study several polygonal curve problems under the Fr\'{e}chet distance via algebraic geometric methods. Let $\mathbb{X}_m^d$ and $\mathbb{X}_k^d$ be the spaces of all polygonal curves of $m$ and $k$ vertices in $\mathbb{R}^d$,…

计算几何 · 计算机科学 2023-10-24 Siu-Wing Cheng , Haoqiang Huang

We study subtrajectory clustering under the Fr\'echet distance. Given one or more trajectories, the task is to split the trajectories into several parts, such that the parts have a good clustering structure. We approach this problem via a…

计算几何 · 计算机科学 2021-12-23 Hugo A. Akitaya , Frederik Brüning , Erin Chambers , Anne Driemel