Accurate triangulations of deformed, intersecting surfaces

Publisher Website
Google Scholar
Abstract
A quadtree algorithm is developed to triangulate deformed, intersecting parametric surfaces. The biggest problem with adaptive sampling is to guarantee that the triangulation is accurate within a given tolerance. A new method guarantees the accuracy of the triangulation, given a "Lipschitz" condition on the surface definition. The method constructs a hierarchical set of bounding volumes for the surface, useful for ray tracing and solid modeling operations. The task of adaptively sampling a surface is broken into two parts: a subdivision mechanism for recursively subdividing a surface, and a set of subdivision criteria for controlling the subdivision process.An adaptive sampling technique is said to be robust if it accurately represents the surface being sampled. A new type of quadtree, called a restricted quadtree , is more robust than the traditional unrestricted quadtree at adaptive sampling of parametric surfaces. Each sub-region in the quadtree is half the width of the previous region. The restricted quadtree requires that adjacent regions be the same width within a factor of two, while the traditional quadtree makes no restriction on neighbor width. Restricted surface quadtrees are effective at recursively sampling a parametric surface. Quadtree samples are concentrated in regions of high curvature, and along intersection boundaries, using several subdivision criteria. Silhouette subdivision improves the accuracy of the silhouette boundary when a viewing transformation is available at sampling time. The adaptive sampling method is more robust than uniform sampling, and can be more efficient at rendering deformed, intersecting parametric surfaces.

This publication has 14 references indexed in Scilit: