Title :
Laplace-Beltrami Eigenfunctions Towards an Algorithm That "Understands" Geometry
Author_Institution :
INRIA-ALICE, Villers-Les-Nancy
Abstract :
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
Keywords :
computational geometry; eigenvalues and eigenfunctions; graph theory; image reconstruction; image representation; mathematical operators; Laplace-Beltrami eigenfunction; differential operator; geometry processing; hierarchical function base; higher-level representation; image reconstruction; object parameterization; spherical harmonics; Calculus; Computational geometry; Eigenvalues and eigenfunctions; Finite element methods; Joining processes; Laplace equations; Mesh generation; Shape; Surface reconstruction; Topology;
Conference_Titel :
Shape Modeling and Applications, 2006. SMI 2006. IEEE International Conference on
Conference_Location :
Matsushima
Print_ISBN :
0-7695-2591-1
DOI :
10.1109/SMI.2006.21