Topology-Adaptive Mesh Deformation for Surface Evolution, Morphing, and Multi-View Reconstruction
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Abstract (arXiv)
Triangulated meshes have become ubiquitous discrete-surface representations. In this paper we address the problem of how to maintain the manifold properties of a surface while it undergoes strong deformations that may cause topological changes. We introduce a new self-intersection removal algorithm, TransforMesh, and we propose a mesh evolution framework based on this algorithm. Numerous shape modelling applications use surface evolution in order to improve shape properties, such as appearance or accuracy. Both explicit and implicit representations can be considered for that purpose. However, explicit mesh representations, while allowing for accurate surface modelling, suffer from the inherent difficulty of reliably dealing with self-intersections and topological changes such as merges and splits. As a consequence, a majority of methods rely on implicit representations of surfaces, e.g. level-sets, that naturally overcome these issues. Nevertheless, these methods are based on volumetric discretizations, which introduce an unwanted precision-complexity trade-off. The method that we propose handles topological changes in a robust manner and removes self intersections, thus overcoming the traditional limitations of mesh-based approaches. To illustrate the effectiveness of TransforMesh, we describe two challenging applications, namely surface morphing and 3-D reconstruction.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Dec 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 1.
3 papers.
- 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variabilitycited by 15
- 20213D Shape Registration Using Spectral Graph Embedding and Probabilistic Matchingcited by 1
- 2025Matching Shapes Under Different Topologies: A Topology-Adaptive Deformation Guided Approachcited by 0
- 2025Matching Shapes Under Different Topologies: A Topology-Adaptive Deformation Guided Approach8 Sep 2025
- 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability22 May 2023
- 20213D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching21 Jun 2021