Title Approximating lower-star persistence via 2D combinatorial map simplification
Authors Damiand, Guillaume , PALUZO HIDALGO, EDUARDO, Slechta, Ryan , Gonzalez-Diaz, Rocio
External publication Si
Means Pattern Recogn. Lett.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 1
JCR Impact 3.756
SJR Impact 0.669
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078194588&doi=10.1016%2fj.patrec.2020.01.018&partnerID=40&md5=b0522f07d9c66771008f813616d93fe7
Publication date 01/03/2020
ISI 000521971700042
Scopus Id 2-s2.0-85078194588
DOI 10.1016/j.patrec.2020.01.018
Abstract Filtration simplification consists of simplifying a given filtration while simultaneously controlling the perturbation in the associated persistence diagrams. In this paper, we propose a filtration simplification algorithm for orientable 2-dimensional (2D) manifolds with or without boundary (meshes) represented by 2D combinatorial maps. Given a lower-star filtration of the mesh, faces are added into contiguous clusters according to a "height" function and a parameter epsilon. Faces in the same cluster are merged into a single face, resulting in a lower resolution mesh and a simpler filtration. We prove that the parameter epsilon bounds the perturbation in the original persistence diagrams, and we provide experiments demonstrating the computational advantages of the simplification process. (c) 2020 Elsevier B.V. All rights reserved.
Keywords Persistent homology computation; 2D combinatorial map; Mesh simplification
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