Critical points to determine persistence homology |
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Author: | Asirimath, Charmin1; Ratnayake, Jayampathy2; Weeraddana, Chathuranga3; |
Organizations: |
1Center for Machine Vision and Signal Analysis, University of Oulu, Finland 2Department of Mathematics, University of Colombo, Sri Lanka 3Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka
4Centre for Wireless Communications, University of Oulu, Finland
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Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2020060841123 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2020
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Publish Date: | 2020-06-08 |
Description: |
AbstractComputation of simplicial complexes of a large point cloud often relies on extracting a sample, to reduce the associated computational burden. The sampling of the point cloud should minimally mutilate the features of the underlying object to enable effective “feature extraction” that lies at the center of modern data analysis techniques, e.g., machine learning. The study considers sampling critical points of a Morse function associated with a point cloud, to approximate the Vietoris-Rips complex and to compute persistence homology. The effectiveness of the approach is compared with the farthest point sampling (FPS), in the context of two classification problems. The empirical results suggest that sampling critical points of the Morse function can be more effective than FPS when determining the persistence homology for the cases where the critical points play a decisive role. see all
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Series: |
Asilomar Conference on Signals, Systems & Computers |
ISSN: | 1058-6393 |
ISSN-E: | 1058-6393 |
ISSN-L: | 1058-6393 |
ISBN: | 978-1-7281-4300-2 |
ISBN Print: | 978-1-7281-4301-9 |
Pages: | 2121 - 2126 |
DOI: | 10.1109/IEEECONF44664.2019.9048780 |
OADOI: | https://oadoi.org/10.1109/IEEECONF44664.2019.9048780 |
Host publication: |
Conference Record of the Fifty-Third Asilomar Conference on Signals, Systems & Computers, November 3–6, 2019 Pacific Grove, California |
Conference: |
Asilomar Conference on Signals, Systems & Computers |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Copyright information: |
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