Publications by year Most documents on this website are protected by copyright.
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has the right to do so. Note that the definitive versions of all EG papers (Eurographics,...) can be downloaded from http://www.eg.org/EG/DL. ACM papers (Siggraph, ...) can be downloaded from http://www.acm.org/dl/. “Numerical Methods for Digital Geometry Processing” Bruno Lévy Israel Korea BiNational Conference  Invited talk, 2005 Abstract: Digital Geometry Processing recently appeared (in the middle of the 90's) as a promising avenue to solve the geometric modeling problems encountered when manipulating surfaces represented by discrete elements (i.e. meshes). Since a mesh may be considered to be a sampling of a surface  in other words a signal  the DGP (digital signal processing) formalism was a natural theoretic background for this discipline (see e.g. Taubin 95). In this discipline, discrete fairing Kobbelt 97 and mesh parameterization Floater 98 have been two active research topics these last few years. In parallel with the evolution of this discipline, acquisition techniques have made huge advances, and todays meshes acquired from real objects by rangelaser scanners are larger and larger (30 million triangles is now common). This causes difficulties when trying to apply DGP tools to these meshes. The kernel of a DGP algorithm is a numerical method, used either to solve a linear system, or to minimize a multivariate function. The GaussSeidel iteration and gradient descent methods used at the early ages of DGP do not scaleup when applied to huge meshes. In this presentation, our goal is to give a survey of classic and more recent numerical methods, to show how they can be applied to DGP problems, from a theoretic point of view down to implementation. We will focus on two different classes of DGP problems (mesh fairing and mesh parameterization), show solutions for linear problems, quadratic problems, and general nonlinear problems, with and without constraint. In particular, we give a general formulation of quadratic problems with reduced degrees of freedom that can be used as a general framework to solve a wide class of DGP problems. Our method is implemented in the OpenNL library, freely available on the web. The presentation will be illustrated with live demos of the methods. BibTex reference @INPROCEEDINGS{levy:NMD:2005,
AUTHOR = "Bruno Lévy",
TITLE = "Numerical Methods for Digital Geometry Processing",
BOOKTITLE = "Israel Korea BiNational Conference",
NOTE = "Invited talk",
YEAR = "2005",
}
Supplemental material, links, hindsight ...
 See our book
Polygon Mesh Processing (Botsch, Kobbelt, Pauly, Alliez and
Levy), "Numerics" chapter (Poisson and Laplace, data structure for
sparse matrices, iterative solvers, direct solvers ...)
 An implementation is available in our OpenNL
numerical library (if you need something you can include in your own
application),
 ... and also in
Graphite (if you need a GUI).

