IS = { zkontrolovano 18 Jan 2009 },
  UPDATE  = { 2008-12-23 },
  author =      {Kukelova, Zuzana and Bujnak, Martin and Pajdla, Tomas},
  title =       {Automatic Generator of Minimal Problem Solvers},
  year =        {2008},
  pages =       {302-315},
  booktitle =   {Computer Vision - ECCV 2008, 10th European Conference on
                 Computer Vision, Proceedings, Part III},
  editor =      {David A. Forsyth and
                 Philip H. S. Torr and
                 Andrew Zisserman},
  publisher =   {Springer},
  address =     {Berlin, Germany},
  series =      {Lecture Notes in Computer Science},
  volume =      {5304},
  isbn =        {978-3-540-88689-1},
  book_pages =  {820},
  month =       {October},
  day =         {12-18},
  venue =       {Marseille, France},
  annote = {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\"{o}bner basis method for solving systems of polynomial
    equations. Previously, the Gr\"{o}bner 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\"{o}bner 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
  keywords =    {Gr\"{o}bner basis, minimal problems,solver},
  authorship =  {34-33-33},
  project =     {FP6-IST-027787 DIRAC, MRTN-CT-2004-005439 VISIONTRAIN, 
                 MSM6840770038, STINT Dur IG2003-2 062, 
                 MSMT Kontakt 9-06-17},
  psurl       = {[PDF] },
  www         = { Zuzana Kukelova ,  Martin Bujnak ,  Tomas Pajdla },
  prestige     = {important},