Repulsive Surfaces
Christopher Yu1, Caleb Brakensiek, Henrik Schumacher2, Keenan Crane1
1Carnegie Mellon University, 2RWTH Aachen
ACM SIGGRAPH ASIA 2021
1Carnegie Mellon University, 2RWTH Aachen
ACM SIGGRAPH ASIA 2021
Abstract:
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.
Paper: Download here (88.5 MB)
Video: Download here (43.6 MB)
Code: Github
Paper: Download here (88.5 MB)
Video: Download here (43.6 MB)
Code: Github