Orthogonalized Fourier Polynomials for Signal Approximation and Transfer
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Date
2021
Authors
Maggioli, Filippo
Melzi, Simone
Ovsjanikov, Maks
Bronstein, Michael M.
Rodolà, Emanuele
Melzi, Simone
Ovsjanikov, Maks
Bronstein, Michael M.
Rodolà, Emanuele
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
We propose a novel approach for the approximation and transfer of signals across 3D shapes. The proposed solution is based on taking pointwise polynomials of the Fourier-like Laplacian eigenbasis, which provides a compact and expressive representation for general signals defined on the surface. Key to our approach is the construction of a new orthonormal basis upon the set of these linearly dependent polynomials. We analyze the properties of this representation, and further provide a complete analysis of the involved parameters. Our technique results in accurate approximation and transfer of various families of signals between near-isometric and non-isometric shapes, even under poor initialization. Our experiments, showcased on a selection of downstream tasks such as filtering and detail transfer, show that our method is more robust to discretization artifacts, deformation and noise as compared to alternative approaches.
Description
@article{10.1111:cgf.142645,
journal = {Computer Graphics Forum},
title = {{Orthogonalized Fourier Polynomials for Signal Approximation and Transfer}},
author = {Maggioli, Filippo and Melzi, Simone and Ovsjanikov, Maks and Bronstein, Michael M. and Rodolà, Emanuele},
year = {2021},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.142645}
}