Persistent homology transform for modeling shapes and surfaces

Journal Article (Journal Article)

We introduce a statistic, the persistent homology transform (PHT), to model surfaces in R3 and shapes in R2. This statistic is a collection of persistence diagrams-multiscale topological summaries used extensively in topological data analysis. We use the PHT to represent shapes and execute operations such as computing distances between shapes or classifying shapes. We provide a constructive proof that the map from the space of simplicial complexes in R3 into the space spanned by this statistic is injective. This implies that we can use it to determine a metric on the space of piecewise linear shapes. Stability results justify that we can approximate this metric using finitely many persistence diagrams. We illustrate the utility of this statistic on simulated and real data.

Full Text

Duke Authors

Cited Authors

  • Turner, K; Mukherjee, S; Boyer, DM

Published Date

  • December 1, 2014

Published In

Volume / Issue

  • 3 / 4

Start / End Page

  • 310 - 344

Electronic International Standard Serial Number (EISSN)

  • 2049-8772

Digital Object Identifier (DOI)

  • 10.1093/imaiai/iau011

Citation Source

  • Scopus