A Function Space Perspective on Stochastic Shape Evolution

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Modelling randomness in shape data, for example, the evolution of shapes of organisms in biology, requires stochastic models of shapes. This paper presents a new stochastic shape model based on a description of shapes as functions in a Sobolev space. Using an explicit orthonormal basis as a reference frame for the noise, the model is independent of the parameterisation of the mesh. We define the stochastic model, explore its properties, and illustrate examples of stochastic shape evolutions using the resulting numerical framework.

TitelImage Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings
RedaktørerRikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen
Antal sider15
ISBN (Trykt)9783031314377
StatusUdgivet - 2023
Begivenhed23nd Scandinavian Conference on Image Analysis, SCIA 2023 - Lapland, Finland
Varighed: 18 apr. 202321 apr. 2023


Konference23nd Scandinavian Conference on Image Analysis, SCIA 2023
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind13886 LNCS

Bibliografisk note

Funding Information:
The work presented in this article was done at the Center for Computational Evolutionary Morphometry and is partly supported by Novo Nordisk Foundation grant NNF18OC0052000 as well as VILLUM FONDEN research grant 40582 and UCPH Data+ Strategy 2023 funds for interdisciplinary research.

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.


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