Smallest k-Enclosing Rectangle Revisited
Abstract
Given a set of points in the plane, and a parameter , we consider the problem of computing the minimum (perimeter or area) axis-aligned rectangle enclosing points. We present the first near quadratic time algorithm for this problem, improving over the previous near--time algorithm by Kaplan etal [KRS17]. We provide an almost matching conditional lower bound, under the assumption that -convolution cannot be solved in truly subquadratic time. Furthermore, we present a new reduction (for either perimeter or area) that can make the time bound sensitive to , giving near time. We also present a near linear time -approximation algorithm to the minimum area of the optimal rectangle containing points. In addition, we study related problems including the -sided, arbitrarily oriented, weighted, and subset sum versions of the problem.
Cite
@article{arxiv.1903.06785,
title = {Smallest k-Enclosing Rectangle Revisited},
author = {Timothy M. Chan and Sariel Har-Peled},
journal= {arXiv preprint arXiv:1903.06785},
year = {2019}
}