IS = { zkontrolovano 10 Jan 2012 },
  UPDATE  = { 2011-04-11 },
  author =      {Neumann, Luk{\' a}{\v s} and Matas, Ji{\v r}{\' \i}},
  title =       {Estimating hidden parameters for text localization and recognition},
  year =        {2011},
  pages =       {29--36},
  booktitle =   {CVWW '11: Proceedings of the 16th Computer Vision Winter Workshop},
  editor =      {Wendel, Andreas and Sternig, Sabine and Godec, Martin},
  publisher =   {Graz University of Technology},
  address =     {Inffeldgasse 16/II, Graz, Austria},
  isbn =        {978-3-85125-129-6},
  book_pages =  {165},
  month =       {February},
  day =         {2-4},
  venue =       {Mitterberg, Ennstal, Austria},
 annote = { A new method for text line formation for text localization
    and recognition is proposed. The method exhaustively enumerates
    short sequences of character regions in order to infer values of
    hidden text line parameters (such as text direction) and applies
    the parameters to efficiently limit the search space for longer
    sequences. The exhaustive enumeration of short sequences is
    achieved by finding all character region triplets that fulfill
    constraints of textual content, which keeps the proposed method
    efficient yet still capable to perform a robust estimation of the
    hidden parameters in order to correctly initialize the search. The
    method is applied to character regions which are detected as
    Maximally Stable Extremal Regions (MSERs).  The performance of the
    method is evaluated on the standard ICDAR 2003 dataset, where the
    method outperforms (precision 0.60, recall 0.60) a previously
    published method for text line formation of MSERs.  },
  keywords =    {computer vision, tracking},
  prestige =    {international},
  project =     {MSM6840770038},
  www         = {http://cmp.felk.cvut.cz/~neumalu1/cvww_article.pdf},
  acceptance_ratio = {0.8},