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Laplace-Beltrami Eigenfunctions Towards an Algorithm That "Understands" Geometry
Open accessAbstract
One of the challenges in geometry processing is to automatically reconstruct a higher-level representation from raw geometric data. For instance, computing a parameterization of an object helps attaching information to it and converting between various representations. More generally, this family of problems may be thought of in terms of constructing structured function bases attached to surfaces. In this paper, we study a specific type of hierarchical function bases, defined by the eigenfunctions of the Laplace-Beltrami operator. When applied to a sphere, this function basis corresponds to the classical spherical harmonics. On more general objects, this defines a function basis well adapted to the geometry and the topology of the object. Based on physical analogies (vibration modes), we first give an intuitive view before explaining the underlying theory. We then explain in practice how to compute an approximation of the eigenfunctions of a differential operator, and show possible applications in geometry processing
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Cites
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
Cited by
Geodesic Convolutional Neural Networks on Riemannian Manifolds
Masci, J., Boscaini, D., Bronstein, M. M., & Vandergheynst, P. (2015) · 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) · doi:10.1109/iccvw.2015.112 · Cited by 721
Spectral Geometry Processing with Manifold Harmonics
Vallet, B., & Lévy, B. (2008) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2008.01122.x · Cited by 386
Bronstein, A. M., Bronstein, M. M., Kimmel, R., Mahmoudi, M., & Sapiro, G. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0301-6 · Cited by 267
Three-Class Differential Diagnosis among Alzheimer Disease, Frontotemporal Dementia, and Controls
Raamana, P. R., Rosen, H., Miller, B., Weiner, M. W., Wang, L., & Beg, M. F. (2014) · Frontiers in Neurology · doi:10.3389/fneur.2014.00071 · Cited by 55
Metadata
- Authors
- Levy, B.
- Venue
- IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06)
- Publisher
- IEEE
- Published
- 2006-07-10
- Pages
- 13-13
- OpenAlex
- W1984159596
- Cited by
- 422
- References
- 1
- FWCI
- 26.74
- Type
- conference paper
- Language
- en
- Open access
- green
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- Levy, B. (2006). Laplace-Beltrami Eigenfunctions Towards an Algorithm That "Understands" Geometry. IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06). https://doi.org/10.1109/smi.2006.21
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