Interval arithmetic yields efficient dynamic filters for computational geometry ?
We discuss floating-point filters as a means of restricting the precision needed for arithmetic operations while still computing the exact result. We show that interval techniques can be used to speed up the exact evaluation of geometric predicates and describe an efficient implementation of interval arithmetic that is strongly influenced by the rounding modes of the widely used IEEE Standard 754. Using this approach we engineer an efficient floating-point filter for the computation of the sign of a determinant that works for arbitrary dimensions. We validate our approach experimentally, comparing it with other static, dynamic and semi-static filters.
floating-point filter geometric computation robustness