English

Critical Points to Determine Persistence Homology

Computer Vision and Pattern Recognition 2018-05-17 v1 Artificial Intelligence Computational Geometry

Abstract

Computation of the simplicial complexes of a large point cloud often relies on extracting a sample, to reduce the associated computational burden. The study considers sampling critical points of a Morse function associated to a point cloud, to approximate the Vietoris-Rips complex or the witness complex and compute persistence homology. The effectiveness of the novel approach is compared with the farthest point sampling, in a context of classifying human face images into ethnics groups using persistence homology.

Keywords

Cite

@article{arxiv.1805.06148,
  title  = {Critical Points to Determine Persistence Homology},
  author = {Charmin Asirimath and Jayampathy Ratnayake and Chathuranga Weeraddana},
  journal= {arXiv preprint arXiv:1805.06148},
  year   = {2018}
}

Comments

11 pages, 4 figures

R2 v1 2026-06-23T01:57:02.873Z