Curve implicitization using moving lines
Computer Aided Geometric Design
Implicitization using moving curves and surfaces
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Implicitizing rational curves by the method of moving algebraic curves
Journal of Symbolic Computation - Special issue: parametric algebraic curves and applications
Journal of Symbolic Computation - Special issue on symbolic computation in algebra, analysis and geometry
Solving Systems of Polynomial Equations
IEEE Computer Graphics and Applications
Simplification of surface parametrizations: a lattice polygon approach
Journal of Symbolic Computation - Special issue: International symposium on symbolic and algebraic computation (ISSAC 2002)
On the problem of proper reparametrization for rational curves and surfaces
Computer Aided Geometric Design
Geometric applications of the Bezout matrix in the Lagrange basis
Proceedings of the 2007 international workshop on Symbolic-numeric computation
Implicitization of bihomogeneous parametrizations of algebraic surfaces via linear syzygies
Proceedings of the 2007 international symposium on Symbolic and algebraic computation
Implicitizing rational hypersurfaces using approximation complexes
Journal of Symbolic Computation
Equations of parametric surfaces with base points via syzygies
Journal of Symbolic Computation
Curve/surface intersection problem by means of matrix representations
Proceedings of the 2009 conference on Symbolic numeric computation
The surface/surface intersection problem by means of matrix based representations
Computer Aided Geometric Design
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In this paper we show that a surface in P^3 parametrized over a 2-dimensional toric variety T can be represented by a matrix of linear syzygies if the base points are finite in number and form locally a complete intersection. This constitutes a direct generalization of the corresponding result over P^2 established in [Buse, L., Jouanolou, J.-P., 2003. J. Algebra 265 (1), 312-357] and [Buse, L., Chardin, M.J., 2005. Symbolic Comput. 40 (4-5), 1150-1168]. Exploiting the sparse structure of the parametrization, we obtain significantly smaller matrices than in the homogeneous case and the method becomes applicable to parametrizations for which it previously failed. We also treat the important case T=P^1xP^1 in detail and give numerous examples.