IS = { zkontrolovano 10 Jan 2012 },
  UPDATE  = { 2011-04-11 },
  author =      {Voj{\' \i}{\v r}, Tom{\' a}{\v s} and Matas, Ji{\v r}{\' \i}},
  title =       {Robustifying the Flock of Trackers},
  year =        {2011},
  pages =       {91-97},
  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 =      {The paper presents contributions to the design of the
    Flock of Trackers (FoT). The FoT trackers estimate the pose of the
    tracked object by robustly combining displacement estimates from
    local trackers that cover the object.  The first contribution,
    called the Cell FoT, allows local trackers to drift to points good
    to track. The Cell FoT was compared with the Kalal et al. Grid FoT
    [4] and outperformed it on all sequences but one and for all local
    failure prediction methods.  As a second contribution, we
    introduce two new predictors of local tracker failure - the
    neighbourhood consistency predictor (Nh) and the Markov predictor
    (Mp) and show that the new predictors combined with the NCC
    predictor are more powerful than the Kalal et al. [4] predictor
    based on NCC and FB.  The resulting tracker equipped with the new
    predictors combined with the NCC predictor was compared with
    state-of-the-art tracking algorithms and surpassed them in terms
    of the number of sequences where a given tracking algorithm
    performed best.},
  keywords =    {computer vision, tracking},
  prestige =    {international},
  project =     {GACR P103/10/1585, MSM6840770038},
  www         = {http://cvww2011.icg.tugraz.at/},
  acceptance_ratio = {0.8},