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Publications [#346294] of Sayan Mukherjee

Papers Published

  1. Turner, K; Mukherjee, S; Boyer, DM, Persistent homology transform for modeling shapes and surfaces, Information and Inference, vol. 3 no. 4 (January, 2014), pp. 310-344 [doi]
    (last updated on 2019/10/29)

    Abstract:
    © The authors 2014. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved. 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.

 

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