Schrödinger Operator for Sparse Approximation of 3D Meshes

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dc.contributor.author Choukroun, Yoni en_US
dc.contributor.author Pai, Gautam en_US
dc.contributor.author Kimmel, Ron en_US
dc.contributor.editor Jakob Andreas Bærentzen and Klaus Hildebrandt en_US
dc.date.accessioned 2017-07-02T17:44:42Z
dc.date.available 2017-07-02T17:44:42Z
dc.date.issued 2017
dc.identifier.isbn 978-3-03868-047-5
dc.identifier.issn 1727-8384
dc.identifier.uri http://dx.doi.org/10.2312/sgp.20171205
dc.identifier.uri https://diglib.eg.org:443/handle/10.2312/sgp20171205
dc.description.abstract We introduce a Schrödinger operator for spectral approximation of meshes representing surfaces in 3D. The operator is obtained by modifying the Laplacian with a potential function which defines the rate of oscillation of the harmonics on different regions of the surface. We design the potential using a vertex ordering scheme which modulates the Fourier basis of a 3D mesh to focus on crucial regions of the shape having high-frequency structures and employ a sparse approximation framework to maximize compression performance. The combination of the spectral geometry of the Hamiltonian in conjunction with a sparse approximation approach outperforms existing spectral compression schemes. en_US
dc.publisher The Eurographics Association en_US
dc.subject I.3.5 [Computer Graphics]
dc.subject Computational Geometry and Object Modeling
dc.subject Curve
dc.subject surface
dc.subject solid
dc.subject and object representations
dc.title Schrödinger Operator for Sparse Approximation of 3D Meshes en_US
dc.description.seriesinformation Symposium on Geometry Processing 2017- Posters
dc.description.sectionheaders Posters
dc.identifier.doi 10.2312/sgp.20171205
dc.identifier.pages 9-10


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