Variational quasi-harmonic maps for computing diffeomorphisms

Yu Wang, Minghao Guo, J. Solomon
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Abstract

Computation of injective (or inversion-free) maps is a key task in geometry processing, physical simulation, and shape optimization. Despite being a longstanding problem, it remains challenging due to its highly nonconvex and combinatoric nature. We propose computation of variational quasi-harmonic maps to obtain smooth inversion-free maps. Our work is built on a key observation about inversion-free maps: A planar map is a diffeomorphism if and only if it is quasi-harmonic and satisfies a special Cauchy boundary condition. We hence equate the inversion-free mapping problem to an optimal control problem derived from our theoretical result, in which we search in the space of parameters that define an elliptic PDE. We show that this problem can be solved by minimizing within a family of functionals. Similarly, our discretized functionals admit exactly injective maps as the minimizers, empirically producing inversion-free discrete maps of triangle meshes. We design efficient numerical procedures for our problem that prioritize robust convergence paths. Experiments show that on challenging examples our methods can achieve up to orders of magnitude improvement over state-of-the-art, in terms of speed or quality. Moreover, we demonstrate how to optimize a generic energy in our framework while restricting to quasi-harmonic maps.
计算微分同态的变分拟调和映射
内射(或无反转)映射的计算是几何处理、物理模拟和形状优化的关键任务。尽管这是一个长期存在的问题,但由于其高度非凸性和组合性,它仍然具有挑战性。我们提出了计算变分拟调和映射来获得光滑的无反转映射。我们的工作建立在一个关于无反转映射的关键观察上:一个平面映射是一个微分同态当且仅当它是拟调和的并且满足一个特殊的柯西边界条件。因此,我们将无反转映射问题等同于由我们的理论结果导出的最优控制问题,其中我们在定义椭圆PDE的参数空间中搜索。我们证明这个问题可以通过在泛函族内最小化来解决。同样地,我们的离散函数承认精确的内射映射作为最小值,经验地产生三角形网格的无反演离散映射。我们为我们的问题设计了有效的数值程序,优先考虑鲁棒收敛路径。实验表明,在具有挑战性的例子中,我们的方法可以在速度或质量方面实现比最先进的数量级的改进。此外,我们还演示了如何在我们的框架中优化一般能量,同时限制于拟调和映射。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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