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HOT: Hodge-Optimized Triangulations (pdf)
To Appear in ACM Transactions on Graphics (SIGGRAPH), 2011.
We introduce Hodge-optimized triangulations (HOT), a family of well-shaped primal-dual pairs of complexes designed for fast and accurate computations in computer graphics. Previous work most commonly employs barycentric or circumcentric duals; while barycentric duals guarantee that the dual of each simplex lies within the simplex, circumcentric duals are often preferred due to the induced orthogonality between primal and dual complexes. We instead promote the use of weighted duals ("power diagrams"). They allow greater flexibility in the location of dual vertices while keeping primal-dual orthogonality, thus providing a valuable extension to the usual choices of dual by only adding one additional scalar per primal vertex. Furthermore, we introduce a family of functionals on pairs of complexes that we derive from bounds on the errors induced by diagonal Hodge stars, commonly used in discrete computations. The minimizers of these functionals, called HOT meshes, are shown to be generalizations of Centroidal Voronoi Tesselations and Optimal Delaunay Triangulations, and to provide increased accuracy and flexibility for a variety of computational purposes.
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Discrete Lie Advection of Differential Forms (pdf)
Foundations of Computational Mathematics, Volume 11, Number 2, 131-149, 2011.
In this paper, we present a numerical technique for performing Lie advection of arbitrary differential forms. Leveraging advances in high-resolution finite volume methods for scalar hyperbolic conservation laws, we first discretize the interior product (also called contraction) through integrals over Eulerian approximations of extrusions. This, along with Cartan's homotopy formula and a discrete exterior derivative, can then be used to derive a discrete Lie derivative. The usefulness of this operator is demonstrated through the numerical advection of scalar fields and 1-forms on regular grids.
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Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets (pdf)
Symposium on Geometry Processing, 2010.
We propose a modular framework for robust 3D reconstruction from unorganized, unoriented, noisy, and outlierridden geometric data. We gain robustness and scalability over previous methods through an unsigned distance approximation to the input data followed by a global stochastic signing of the function. An isosurface reconstruction is finally deduced via a sparse linear solve. We show with experiments on large, raw, geometric datasets that this approach is scalable while robust to noise, outliers, and holes. The modularity of our approach facilitates customization of the pipeline components to exploit specific idiosyncracies of datasets, while the simplicity of each component leads to a straightforward implementation.
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Energy-Preserving Integrators for Fluid Animation (pdf)
ACM Transactions on Graphics (SIGGRAPH), 2009.
Numerical viscosity has long been a problem in fluid animation. Existing
methods suffer from intrinsic artificial dissipation and often apply complicated
computational mechanisms to combat such effects. Consequently, dissipative
behavior cannot be controlled or modeled explicitly in a manner independent of
time step size, complicating the use of coarse previews and adaptive-time
stepping methods. This paper proposes simple, unconditionally stable, fully
Eulerian integration schemes with no numerical viscosity that are capable of
maintaining the liveliness of fluid motion without recourse to corrective
devices. Pressure and fluxes are solved efficiently and simultaneously in a
time-reversible manner on simplicial grids, and the energy is preserved exactly
over long time scales in the case of inviscid fluids. These integrators can be
viewed as an extension of the classical energy-preserving Harlow-Welch /
Crank-Nicolson scheme to simplicial grids.
Video (divx) YouTube
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Numerical Coarsening of Inhomogeneous Elastic Materials (pdf)
Lily Kharevych, Patrick Mullen, Houman Owhadi
and Mathieu Desbrun.
ACM Transactions on Graphics (SIGGRAPH), 2009.
We propose an approach for efficiently simulating elastic objects made of
non-homogeneous, non-isotropic materials. Based on recent developments in
homogenization theory, a methodology is introduced to approximate a deformable
object made of arbitrary fine structures of various linear elastic materials
with a dynamically similar coarse model. This numerical coarsening of the
material properties allows for simulation of fine, heterogeneous structures on
very coarse grids while capturing the proper dynamics of the original dynamical
system, thus saving orders of magnitude in computational time. Examples
including inhomogeneous and/or anisotropic materials can be realistically
simulated in realtime using a numerically-coarsened model made of a few mesh
elements.
Video (divx)
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Spectral Conformal Parameterization (pdf)
Patrick Mullen, Yiying Tong, Pierre Alliez
and Mathieu Desbrun.
Symposium on Geometry Processing, 2008.
We present a spectral approach to automatically and efficiently obtain
discrete free-boundary conformal parameterizations of triangle mesh patches,
without the common artifacts due to positional constraints on vertices and
without undue bias introduced by sampling irregularity. High-quality
parameterizations are computed through a constrained minimization of a discrete
weighted conformal energy by finding the largest eigenvalue/eigenvector of a
generalized eigenvalue problem involving sparse, symmetric matrices. We
demonstrate that this novel and robust approach improves on previous linear
techniques both quantitatively and qualitatively.
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A Variational Approach to Eulerian Geometry Processing (pdf)
Patrick Mullen, Alexander McKenzie, Yiying
Tong and Mathieu Desbrun.
ACM Transactions on Graphics (SIGGRAPH), 2007.
We present a purely Eulerian framework for geometry processing of surfaces
and foliations. Contrary to current Eulerian methods used in graphics, we use
conservative methods and a variational interpretation, offering a unified
framework for routine surface operations such as smoothing, offsetting, and
animation. Computations are performed on a fixed volumetric grid without
recourse to Lagrangian techniques such as triangle meshes, particles, or path
tracing. At the core of our approach is the use of the Coarea Formula to express
area integrals over isosurfaces as volume integrals. This enables the
simultaneous processing of multiple isosurfaces, while a single interface can be
treated as the special case of a dense foliation. We show that our method is a
powerful alternative to conventional geometric representations in delicate cases
such as the handling of high-genus surfaces, weighted offsetting, foliation
smoothing of medical datasets, and incompressible fluid animation.
Supplemental Video (divx)
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Data-Dependent Fairing of Subdivision Surfaces (pdf)
Ilja Friedel, Patrick Mullen and Peter Schröder.
Solid Modeling, 2003.
In this paper we present a new algorithm for solving the data dependent fairing problem for subdivision surfaces, using Catmull-Clark surfaces as an example. Earlier approaches to subdivision surface fairing encountered problems with singularities in the parametrization of the surface. We address these issues through the use of the characteristic map parametrization, leading to well defined membrane and bending energies even at irregular vertices. Combining this approach with ideas from data-dependent energy operators we are able to express the associated nonlinear stiffness matrices for Catmull-Clark surfaces as linear combinations of precomputed energy matrices. This machinery also provides exact, inexpensive gradients and Hessians of the new energy operators. With these the nonlinear minimization problem can be solved in a stable and efficient way using Steihaug's Newton/CG trust-region method. We compare properties of linear and nonlinear methods through a number of examples and report on the performance of the algorithm.
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