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.
Original language | English |
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Title of host publication | Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings |
Editors | Rikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen |
Number of pages | 15 |
Publisher | Springer |
Publication date | 2023 |
Pages | 278-292 |
ISBN (Print) | 9783031314377 |
DOIs | |
Publication status | Published - 2023 |
Event | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 - Lapland, Finland Duration: 18 Apr 2023 → 21 Apr 2023 |
Conference
Conference | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 |
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Country/Territory | Finland |
City | Lapland |
Period | 18/04/2023 → 21/04/2023 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13886 LNCS |
ISSN | 0302-9743 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- 3D mesh processing
- diffusions
- shape space