@MastersThesis{Konecny-TR-2008-03,
  UPDATE  = { 2009-01-27 },
   author =      {Kone{\v c}n{\'y}, Jan},
   supervisor =  {Svoboda, Tom{\'a}{\v s} and Zimmermann, Karel},
   language =    {czech},
   title =       {Adaptivn{\'\i} modelov{\'a}n{\'\i} a sledov{\'a}n{\'\i}
                   objekt{\accent23u} ve videosekvenc{\'\i}ch},
   e_title =     {Adaptive Object Modeling and Tracking in Videosequences},
   school =      {Center for Machine Perception, K13133 FEE Czech Technical
                   University},
   address =     {Prague, Czech Republic},
   year =        {2008},
   month =       {February},
   day =         {12},
   type =        {{MSc Thesis CTU--CMP--2008--03}},
   issn =        {1213-2365},
   pages =       {47},
   psurl =   {[Konecny-TR-2008-03.pdf]},
   project =     {1ET101210407 },
   annote = {We propose tracking method which is based on Linear
     Predictor (LLiP) suitable for objects with variable
     appearance. Linear Predictor is a learned linear mapping between
     observed intensities and motion. Since object appearance may
     change (e.g. due to non-rigid deformation) we propose Parametric
     Linear Predictor (PLLiP), which is adjusted by the
     appearance. PLLiP tracking algorithm first aligns the object with
     current image data and then estimates actual appearance
     parameters that adjust PLLiP for the next image. We
     experimentally show that PLLiP has lower motion estimation error
     than LLiP which does not use extended information of actual
     object appearance. },
   keywords =    {learning, tracking, modeling},
   comment =     {ftp://pub/cmp/articles/zimmerk/konecny_msc2008.pdf},
}