ACM Transactions on Graphics · 2021 · 27 citations · 49 references
ComputingComputer ScienceMathematicsComputational GeometryComputational PhysicsGeometric ModelingGeometric OptimizationGeometry ProcessingMesh GenerationMesh ProcessingShape OptimizationSurface ModelingAlgorithmic Geometry ProcessingFractional Differential EquationsMathematical VisualizationMesh OptimizationScientific Computing AccelerationSurface GeometrySurface MeshingVolumetric Meshes
Functionals that penalize bending or stretching of a surface play a key role in geometric and scientific computing, but to date have ignored a very basic requirement: in many situations, surfaces must not pass through themselves or each other. This paper develops a numerical framework for optimization of surface geometry while avoiding (self-)collision. The starting point is the tangent-point energy , which effectively pushes apart pairs of points that are close in space but distant along the surface. We develop a discretization of this energy for triangle meshes, and introduce a novel acceleration scheme based on a fractional Sobolev inner product. In contrast to similar schemes developed for curves, we avoid the complexity of building a multiresolution mesh hierarchy by decomposing our preconditioner into two ordinary Poisson equations, plus forward application of a fractional differential operator. We further accelerate this scheme via hierarchical approximation, and describe how to incorporate a variety of constraints (on area, volume, etc. ). Finally, we explore how this machinery might be applied to problems in mathematical visualization, geometric modeling, and geometry processing.
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