English

Smallest k-Enclosing Rectangle Revisited

Computational Geometry 2019-03-19 v1

Abstract

Given a set of nn points in the plane, and a parameter kk, we consider the problem of computing the minimum (perimeter or area) axis-aligned rectangle enclosing kk points. We present the first near quadratic time algorithm for this problem, improving over the previous near-O(n5/2)O(n^{5/2})-time algorithm by Kaplan etal [KRS17]. We provide an almost matching conditional lower bound, under the assumption that (min,+)(\min,+)-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 kk, giving near O(nk)O(n k) time. We also present a near linear time (1+ε)(1+\varepsilon)-approximation algorithm to the minimum area of the optimal rectangle containing kk points. In addition, we study related problems including the 33-sided, arbitrarily oriented, weighted, and subset sum versions of the problem.

Keywords

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}
}
R2 v1 2026-06-23T08:09:53.630Z