English

Approximating Loops in a Shortest Homology Basis from Point Data

Computational Geometry 2009-12-02 v2 Discrete Mathematics

Abstract

Inference of topological and geometric attributes of a hidden manifold from its point data is a fundamental problem arising in many scientific studies and engineering applications. In this paper we present an algorithm to compute a set of loops from a point data that presumably sample a smooth manifold MRdM\subset \mathbb{R}^d. These loops approximate a {\em shortest} basis of the one dimensional homology group H1(M)H_1(M) over coefficients in finite field Z2\mathbb{Z}_2. Previous results addressed the issue of computing the rank of the homology groups from point data, but there is no result on approximating the shortest basis of a manifold from its point sample. In arriving our result, we also present a polynomial time algorithm for computing a shortest basis of H1(K)H_1(K) for any finite {\em simplicial complex} KK whose edges have non-negative weights.

Keywords

Cite

@article{arxiv.0909.5654,
  title  = {Approximating Loops in a Shortest Homology Basis from Point Data},
  author = {Tamal K. Dey and Jian Sun and Yusu Wang},
  journal= {arXiv preprint arXiv:0909.5654},
  year   = {2009}
}
R2 v1 2026-06-21T13:52:33.557Z