Applications of Gro¨bner bases in non-linear computational geometry
Mathematical aspects of scientific software
Algorithm for implicitizing rational parametric surfaces
Computer Aided Geometric Design
On the Newton Polytope of the Resultant
Journal of Algebraic Combinatorics: An International Journal
Efficient incremental algorithms for the sparse resultant and the mixed volume
Journal of Symbolic Computation
Implicitization of parametric curves and surfaces by using multidimensional Newton formulae
Journal of Symbolic Computation - Special issue: parametric algebraic curves and applications
Splines and geometric modeling
Handbook of discrete and computational geometry
A subdivision-based algorithm for the sparse resultant
Journal of the ACM (JACM)
Residual resultant over the projective plane and the implicitization problem
Proceedings of the 2001 international symposium on Symbolic and algebraic computation
Mathematical Methods for Curves and Surfaces
Real implicitization of curves and geometric extraneous components
Proceedings of the 2007 international workshop on Symbolic-numeric computation
Implicitization of curves and surfaces using predicted support
Proceedings of the 2011 International Workshop on Symbolic-Numeric Computation
Implicitization of curves and (hyper)surfaces using predicted support
Theoretical Computer Science
Hi-index | 0.00 |
We propose the use of various tools from algebraic geometry, with an emphasis on toric (or sparse) elimination theory, in order to predict the support of the implicit equation of a parametric hypersurface. The problem of implicitization lies at the heart of several algorithms in geometric modeling and computer-aided design, two of which (based on interpolation) are immediately improved by our contribution. We believe that other methods of implicitization shall be able to benefit from our work. More specifically, we use information on the support of the toric resultant, and degree bounds, formulated in terms of the mixed volume of Newton polytopes. The computed support of the implicit equation depends on the sparseness of the parametric expressions and is much tighter than the one predicted by degree arguments. Our Maple implementation illustrates many cases in which we obtain the exact support. In addition, it is possible to specify certain coefficients of the implicit equation.