. "Automatic Generator of Minimal Problem Solvers"@cs . "Finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. The state of the art approach for constructing such algorithms is the Gr\u00F6bner basis method for solving systems of polynomial equations. Previously, the Gr\u00F6bner basis solvers were designed ad hoc for concrete problems and they could not be easily applied to new problems. In this paper we propose an automatic procedure for generating Gr\u00F6bner basis solvers which could be used even by non-experts to solve technical problems. The input to our solver generator is a system of polynomial equations with a finite number of solutions. The output of our solver generator is the Matlab or C code which computes solutions to this system for concrete coefficients. Generating solvers automatically opens possibilities t"@en . "Finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. The state of the art approach for constructing such algorithms is the Gr\u00F6bner basis method for solving systems of polynomial equations. Previously, the Gr\u00F6bner basis solvers were designed ad hoc for concrete problems and they could not be easily applied to new problems. In this paper we propose an automatic procedure for generating Gr\u00F6bner basis solvers which could be used even by non-experts to solve technical problems. The input to our solver generator is a system of polynomial equations with a finite number of solutions. The output of our solver generator is the Matlab or C code which computes solutions to this system for concrete coefficients. Generating solvers automatically opens possibilities t" . . "2008-10-12+02:00"^^ . "3"^^ . . "Automatic Generator of Minimal Problem Solvers"@en . "3"^^ . . . . "Buj\u0148\u00E1k, Martin" . . "978-3-540-88689-1" . "Automatic Generator of Minimal Problem Solvers" . . "RIV/68407700:21230/08:03150846" . "Automatic Generator of Minimal Problem Solvers"@cs . "[AA62E9BDA54F]" . "000260659800023" . . "K\u00FAkelov\u00E1, Zuzana" . "21230" . . "RIV/68407700:21230/08:03150846!RIV09-MSM-21230___" . "Automatic Generator of Minimal Problem Solvers"@en . . . "Z(MSM6840770038)" . "Pajdla, Tom\u00E1\u0161" . . . . . "Gr\u00F6bner basis; minimal problems; solver"@en . "357390" . "Berlin" . "Automatic Generator of Minimal Problem Solvers" . "Computer Vision - ECCV 2008, 10th European Conference on Computer Vision, Proceedings, Part III" . "14"^^ . "Finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. The state of the art approach for constructing such algorithms is the Gr\u00F6bner basis method for solving systems of polynomial equations. Previously, the Gr\u00F6bner basis solvers were designed ad hoc for concrete problems and they could not be easily applied to new problems. In this paper we propose an automatic procedure for generating Gr\u00F6bner basis solvers which could be used even by non-experts to solve technical problems. The input to our solver generator is a system of polynomial equations with a finite number of solutions. The output of our solver generator is the Matlab or C code which computes solutions to this system for concrete coefficients. Generating solvers automatically opens possibilities t"@cs . . "Springer-Verlag" . "0302-9743" . . "Marseille" .