Isometry Invariant Shape Recognition of Projectively Perturbed Point Clouds by the Mergegram Extending 0D Persistence



Elkin, Yury and Kurlin, Vitaliy ORCID: 0000-0001-5328-5351
(2021) Isometry Invariant Shape Recognition of Projectively Perturbed Point Clouds by the Mergegram Extending 0D Persistence. MATHEMATICS, 9 (17). p. 2121.

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Abstract

Rigid shapes should be naturally compared up to rigid motion or isometry, which preserves all inter-point distances. The same rigid shape can be often represented by noisy point clouds of different sizes. Hence the isometry shape recognition problem requires methods that are independent of a cloud size. This paper studies stable-under-noise isometry invariants for the recognition problem stated in the harder form when given clouds can be related by affine or projective transformations. The first contribution is the stability proof for the invariant mergegram, which completely determines a single-linkage dendrogram in general position. The second contribution is the experimental demonstration that the mergegram outperforms other invariants in recognizing isometry classes of point clouds extracted from perturbed shapes in images.

Item Type: Article
Additional Information: arXiv admin note: substantial text overlap with arXiv:2007.11278
Uncontrolled Keywords: shape recognition, Topological Data Analysis, machine learning, computer vision
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 30 Sep 2021 15:59
Last Modified: 14 Mar 2024 17:32
DOI: 10.3390/math9172121
Open Access URL: https://doi.org/10.3390/math9172121
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3138846