@InProceedings{chum-degen-cvpr05,
  IS = { zkontrolovano 30 Nov 2005 },
  UPDATE  = { 2005-07-18 },
author =      {Chum, Ond{\v r}ej and Werner, Tom{\' a}{\v s} and Matas, Ji{\v r}{\' \i}},
title =       {Two-view Geometry Estimation Unaffected by a Dominant Plane},
booktitle =   {Proc. of Conference on Computer Vision and Pattern Recognition (CVPR)},
address =     {Los Alamitos, USA} ,
year =        {2005},
month =       {June},
day =         {20--25},
isbn        = {0-7695-2372-2},
publisher   = {IEEE Computer Society},
book_pages  = {1219},
pages    =    {772--780},
authorship =  {34-33-33},
psurl    =    {[pdf]},
project  =  {IST-004176, 1ET101210406},
annote = { A RANSAC-based algorithm for robust estimation of epipolar
  geometry from point correspondences in the possible presence of a
  dominant scene plane is presented. The algorithm handles scenes with
  (i) all points in a single plane, (ii) majority of points in a
  single plane and the rest off the plane, (iii) no dominant plane.
  It is not required to know a priori which of the cases (i) -- (iii)
  occurs.  The algorithm exploits a theorem we proved, that if five or
  more of seven correspondences are related by a homography then there
  is an epipolar geometry consistent with the seven-tuple as well as
  with all correspondences related by the homography. This means that
  a seven point sample consisting of two outliers and five inliers
  lying in a dominant plane produces an epipolar geometry which is
  completely wrong and yet consistent with a high number of
  correspondences. The theorem explains why RANSAC often fails to
  estimate epipolar geometry in the presence of a dominant plane.
  Rather surprisingly, the theorem also implies that RANSAC-based
  homography estimation is faster when drawing non-minimal samples of
  seven correspondences than minimal samples of four correspondences. },
keywords =    {RANSAC, wide-baseline stereo, dominant plane},
editor      = {Schmid, Cordelia and Soatto, Stefano and Tomasi, Carlo},
venue       = {San Diego, California, USA  },
volume      = { 1 },
}