Abstract
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.
Originalsprog | Engelsk |
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Titel | Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings |
Redaktører | Rikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen |
Antal sider | 15 |
Forlag | Springer |
Publikationsdato | 2023 |
Sider | 278-292 |
ISBN (Trykt) | 9783031314377 |
DOI | |
Status | Udgivet - 2023 |
Begivenhed | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 - Lapland, Finland Varighed: 18 apr. 2023 → 21 apr. 2023 |
Konference
Konference | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 |
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Land/Område | Finland |
By | Lapland |
Periode | 18/04/2023 → 21/04/2023 |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 13886 LNCS |
ISSN | 0302-9743 |
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.