An <inline-formula><tex-math notation="LaTeX">$hp$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq1-2730202.gif"/></alternatives></inline-formula>-Adaptive Discretization Algorithm for Signed Distance Field Generation

In this paper we present an <inline-formula><tex-math notation="LaTeX">$hp$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq2-2730202.gif"/></alternatives></inline-formula>-adaptive algorithm to generate discrete higher-order polynomial Signed Distance Fields (SDFs) on axis-aligned hexahedral grids from manifold polygonal input meshes. Using an orthonormal polynomial basis, we efficiently fit the polynomials to the underlying signed distance function on each cell. The proposed error-driven construction algorithm is globally adaptive and iteratively refines the SDFs using either spatial subdivision (<inline-formula><tex-math notation="LaTeX">$h$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq3-2730202.gif"/></alternatives></inline-formula>-refinement) following an octree scheme or by cell-wise adaption of the polynomial approximation&#x0027;s degree (<inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq4-2730202.gif"/></alternatives></inline-formula>-refinement). We further introduce a novel decision criterion based on an error-estimator in order to decide whether to apply <inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq5-2730202.gif"/></alternatives></inline-formula>- or <inline-formula><tex-math notation="LaTeX">$h$</tex-math><alternatives><inline-graphic xlink:href="koschier-ieq6-2730202.gif"/></alternatives></inline-formula>-refinement. We demonstrate that our method is able to construct more accurate SDFs at significantly lower memory consumption compared to previous approaches. While the cell-wise polynomial approximation will result in highly accurate SDFs, it can not be guaranteed that the piecewise approximation is continuous over cell interfaces. Therefore, we propose an optimization-based post-processing step in order to weakly enforce continuity. Finally, we apply our generated SDFs as collision detector to the physically-based simulation of geometrically highly complex solid objects in order to demonstrate the practical relevance and applicability of our method.