Automatic Generator of Minimal Problem Solvers View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2008

AUTHORS

Zuzana Kukelova , Martin Bujnak , Tomas Pajdla

ABSTRACT

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 Gröbner basis method for solving systems of polynomial equations. Previously, the Gröbner 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 Gröbner 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 to solve more complicated problems which could not be handled manually or solving existing problems in a better and more efficient way. We demonstrate that our automatic generator constructs efficient and numerically stable solvers which are comparable or outperform known manually constructed solvers. The automatic generator is available at http://cmp.felk.cvut.cz/minimal More... »

PAGES

302-315

References to SciGraph publications

Book

TITLE

Computer Vision – ECCV 2008

ISBN

978-3-540-88689-1
978-3-540-88690-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-88690-7_23

DOI

http://dx.doi.org/10.1007/978-3-540-88690-7_23

DIMENSIONS

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