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