@inproceedings{a9663b18df01476d92cf765c6600dcca,
title = "Schr{\"o}dinger Operator for Sparse Approximation of 3D Meshes: 15th Eurographics Symposium on Geometry Processing, SGP 2017",
abstract = "We introduce a Schr{\"o}dinger 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.",
author = "Y. Choukroun and G. Pai and R. Kimmel",
note = "Publisher Copyright: {\textcopyright} 2007 Eurographics Association. All rights reserved.; Eurographics Symposium on Geometry Processing, SGP 2017, SGP 2017 ; Conference date: 03-07-2017 Through 05-07-2017",
year = "2017",
doi = "10.2312/sgp.20171205",
language = "English",
series = "Eurographics Symposium on Geometry Processing",
publisher = "Eurographics Association",
pages = "9--10",
booktitle = "SGP17: Eurographics Symposium on Geometry Processing",
}