Hierarchical hp-Adaptive Signed Distance Fields

Dan Koschier, Crispin Deul, Jan Bender
ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation

In this paper we propose a novel method to construct hierarchical $hp$-adaptive Signed Distance Fields (SDFs). We discretize the signed distance function of an input mesh using piecewise polynomials on an axis-aligned hexahedral grid. Besides spatial refinement based on octree subdivision to refine the cell size (h), we hierarchically increase each cell's polynomial degree (p) in order to construct a very accurate but memory-efficient representation. Presenting a novel criterion to decide whether to apply h- or p-refinement, we demonstrate that our method is able to construct more accurate SDFs at significantly lower memory consumption than previous approaches. Finally, we demonstrate the usage of our representation as collision detector for geometrically highly complex solid objects in the application area of physically-based simulation.

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author = {Dan Koschier and Crispin Deul and Jan Bender},
title = {Hierarchical hp-Adaptive Signed Distance Fields},
booktitle = {Proceedings of the 2016 ACM SIGGRAPH/Eurographics Symposium on Computer
year = {2016},
publisher = {Eurographics Association},
location = {Zurich, Switzerland}

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