IS = { zkontrolovano 25 Jan 2011 },
  UPDATE  = { 2009-10-15 },
  author =     {Bujnak, Martin and Kukelova, Zuzana and 
                Pajdla, Tom{\'a}{\v s}},
  title =      {Robust focal length estimation by voting in
                multiview scene reconstruction},
  year =       {2010},
  pages  =     {13--24},
  booktitle =  {{ACCV} 2009: Proceedings of the 9th Asian
                Conference on Computer Vision, Part {I}},
  editor =     {Hongbin Zha, Rin-ichiro Taniguchi, Stephen Maybank},
  publisher =  {Springer},
  series =     {LNSC},
  volume =     {5994},
  address =    {Heidelberg, Germany},
  isbn =       {978-3-642-12306-1},
  book_pages = {390},
  month =      {September},
  day =        {23-27},
  venue =      {Xi'an, China},
  prestige =   {international},
  annote = {We propose a new robust focal length estimation method in
    multi-view structure from motion from unordered data sets,
    e.g. downloaded from the Flickr database, where jpeg-exif headers
    are often incorrect or missing. The method is based on a
    combination of RANSAC with weighted kernel voting and can use any
    algorithm for estimating epipolar geometry and unknown focal
    lengths. We demonstrate by experiments with synthetic and real
    data that the method produces reliable focal length estimates
    which are better than estimates obtained using RANSAC or kernel
    voting alone and which are in most real situations very close to
    the ground truth. An important feature of this method is the
    ability to detect image pairs close to critical configurations or
    the cases when the focal length can't be reliably estimated.},
  keywords =    {focal length, epipolar geometry, 3D reconstruction},
  project =     {FP7-SPACE-218814 PRoVisG, MSM6840770038},
  note        = { CD-ROM },