Reliable Location with Respect to the Projection of a Smooth Space Curve

Consider a plane curve B defined as the projection of the intersection of two surfaces in R^3 or as the apparent contour of a surface. In general, B has node or cusp singular points and thus is a singular curve. Our main contribution is the computation of a data structure answering point location qu...

Full description

Saved in:
Bibliographic Details
Published inReliable computing Vol. 26; pp. 13 - 55
Main Authors Imbach, Rémi, Moroz, Guillaume, Pouget, Marc
Format Journal Article
LanguageEnglish
Published Springer Verlag 2018
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Consider a plane curve B defined as the projection of the intersection of two surfaces in R^3 or as the apparent contour of a surface. In general, B has node or cusp singular points and thus is a singular curve. Our main contribution is the computation of a data structure answering point location queries with respect to the subdivision of the plane induced by B. This data structure is composed of an approximation of the space curve together with a topological representation of its projection B. Since B is a singular curve, it is challenging to design a method based only on reliable numerical algorithms. In recent work, the authors show how to describe the set of singularities of B as regular solutions of a so-called ball system suitable for a numerical subdivision solver. Here, the space curve is first enclosed in a set of boxes with a certified path-tracker to restrict the domain where the ball system is solved. Boxes around singular points are then computed such that the correct topology of the curve inside these boxes can be deduced from the intersections of the curve with their boundaries. The tracking of the space curve is then used to connect the smooth branches to the singular points. The subdivision of the plane induced by B is encoded as an extended planar combinatorial map allowing point location. We experimented with our method, and we show that our reliable numerical approach can handle classes of examples that symbolic methods cannot.
ISSN:1385-3139
1573-1340