{"title":"A Coreset for Approximate Furthest-Neighbor Queries in a Simple Polygon","authors":"Mark de Berg, Leonidas Theocharous","doi":"arxiv-2403.04513","DOIUrl":null,"url":null,"abstract":"Let $\\mathcal{P}$ be a simple polygon with $m$ vertices and let $P$ be a set\nof $n$ points inside $\\mathcal{P}$. We prove that there exists, for any\n$\\varepsilon>0$, a set $\\mathcal{C} \\subset P$ of size $O(1/\\varepsilon^2)$\nsuch that the following holds: for any query point $q$ inside the polygon\n$\\mathcal{P}$, the geodesic distance from $q$ to its furthest neighbor in\n$\\mathcal{C}$ is at least $1-\\varepsilon$ times the geodesic distance to its\nfurther neighbor in $P$. Thus the set $\\mathcal{C}$ can be used for answering\n$\\varepsilon$-approximate furthest-neighbor queries with a data structure whose\nstorage requirement is independent of the size of $P$. The coreset can be\nconstructed in $O\\left(\\frac{1}{\\varepsilon} \\left( n\\log(1/\\varepsilon) +\n(n+m)\\log(n+m)\\right) \\right)$ time.","PeriodicalId":501570,"journal":{"name":"arXiv - CS - Computational Geometry","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computational Geometry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.04513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Let $\mathcal{P}$ be a simple polygon with $m$ vertices and let $P$ be a set
of $n$ points inside $\mathcal{P}$. We prove that there exists, for any
$\varepsilon>0$, a set $\mathcal{C} \subset P$ of size $O(1/\varepsilon^2)$
such that the following holds: for any query point $q$ inside the polygon
$\mathcal{P}$, the geodesic distance from $q$ to its furthest neighbor in
$\mathcal{C}$ is at least $1-\varepsilon$ times the geodesic distance to its
further neighbor in $P$. Thus the set $\mathcal{C}$ can be used for answering
$\varepsilon$-approximate furthest-neighbor queries with a data structure whose
storage requirement is independent of the size of $P$. The coreset can be
constructed in $O\left(\frac{1}{\varepsilon} \left( n\log(1/\varepsilon) +
(n+m)\log(n+m)\right) \right)$ time.