Orthogonalized Fourier Polynomials for Signal Approximation and Transfer
dc.contributor.author | Maggioli, Filippo | en_US |
dc.contributor.author | Melzi, Simone | en_US |
dc.contributor.author | Ovsjanikov, Maks | en_US |
dc.contributor.author | Bronstein, Michael M. | en_US |
dc.contributor.author | RodolĂ , Emanuele | en_US |
dc.contributor.editor | Mitra, Niloy and Viola, Ivan | en_US |
dc.date.accessioned | 2021-04-09T08:01:07Z | |
dc.date.available | 2021-04-09T08:01:07Z | |
dc.date.issued | 2021 | |
dc.description.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. | en_US |
dc.description.number | 2 | |
dc.description.sectionheaders | Shape Analysis | |
dc.description.seriesinformation | Computer Graphics Forum | |
dc.description.volume | 40 | |
dc.identifier.doi | 10.1111/cgf.142645 | |
dc.identifier.issn | 1467-8659 | |
dc.identifier.pages | 435-447 | |
dc.identifier.uri | https://doi.org/10.1111/cgf.142645 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf142645 | |
dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
dc.subject | Computing methodologies | |
dc.subject | Shape analysis | |
dc.subject | Theory of computation | |
dc.subject | Computational geometry | |
dc.subject | Mathematics of computing | |
dc.subject | Functional analysis | |
dc.title | Orthogonalized Fourier Polynomials for Signal Approximation and Transfer | en_US |