IS = { zkontrolovano 10 Jan 2012 },
  UPDATE  = { 2011-04-11 },
  author =      {Hurych, David and Zimmermann, Karel and Svoboda, Tom{\' a}{\v s}},
  title =       {Fast Learnable Object Tracking and Detection in High-resolution 
                 Omnidirectional Images},
  year =        {2011},
  pages =       {521-530},
  booktitle =   {Proceedings of VISAPP 2011 International Conference on 
                 Computer Vision Theory and Applications},
  editor =      {Mestetskiy, Leonid and Braz, Jose},
  publisher =   {INSTICC-Institute for Systems and
    Technologies of Information, Control and Communication},
  address =     {Set{\'u}bal, Portugal},
  isbn =        {978-989-8425-47-8},
  book_pages =  {718},
  month =       {March},
  day =         {5-7},
  venue =       {Algarve, Portugal},
  organization ={INSTICC - Institute for Systems and 
    Technologies of Information, Control and Communication},
  annote =      {This paper addresses object detection and tracking in
    high-resolution omnidirectional images. The foreseen application
    is a visual subsystem of a rescue robot equipped with an
    omnidirectional camera, which demands real time efficiency and
    robustness against changing viewpoint. Object detectors typically
    do not guarantee specific frame rate. The detection time may
    vastly depend on a scene complexity and image resolution. The
    adapted tracker can often help to overcome the situation, where
    the appearance of the object is far from the training set. On the
    other hand, once a tracker is lost, it almost never finds the
    object again. We propose a combined solution where a very
    efficient tracker (based on sequential linear predictors)
    incrementally accommodates varying appearance and speeds up the
    whole process. We experimentally show that the performance of the
    combined algorithm, measured by a ratio between false positives
    and false negatives, outperforms both individual algorithms. The
    tracker allows to run the expensive detector only sparsely
    enabling the combined solution to run in real-time on 12 MPx
    images from a high resolution omnidirectional camera (Ladybug3).},
  keywords =    {detection, tracking, incremental, learning,
    predictors, fern, omnidirectional, high-resolution},
  prestige =    {international},
  authorship =  {50-30-20},
  project =     {GACR P103/10/1585, GACR P103/11/P700, FP7-ICT-247870 NIFTi},
  url =         {ftp://cmp.felk.cvut.cz/pub/cmp/articles/hurycd1/visapp2011.pdf},
  psurl       = {[hurych-VISAPP2011.pdf] },