UPDATE  = { 2009-01-27 },
  author =       {Varga, Ctibor},
  supervisor =   {Svoboda, Tom{\'a}{\v s} and Zimmermann, Karel },
  language =     {czech},
  title =        {Detekce objekt{\accent23 u} n{\'a}hodn{\v e}
                  inicializovan{\'y}m sledov{\'a}n{\'\i}m},
  e_title =      {Linear predictors for object detection},
  school =       {Center for Machine Perception, K13133 FEE Czech
                  Technical University},
  address =      {Prague, Czech Republic},
  year =         {2008},
  month =        {June},
  day =          {19},
  type =         {{MSc Thesis CTU--CMP--2008--10}},
  issn =         {1213-2365},
  pages =        {64},
  psurl =        {[Varga-TR-2008-10.pdf]},
  project =      {1ET101210407},
  annote = {Detection and tracking objects is one of the main topics
    in computer vision. In many systems the fast camera data
    processing is desired. In this diploma thesis a fast algorithm for
    tracking rigid parts of known objects by sequences of learned
    linear predictors was implemented. We propose to use the same
    algorithm also for object detection The principal drawback of
    tracking by linear predictors in fast motion (failure by reason of
    limited range of learned predictor) is supressed by redetection in
    neighbourhood of the last know object position. Algorithm is also
    used for human face detection. The ability of algorithm for
    tracking and detection (achieved framerate and effectivity of
    detection and redetection) is verified by experiments on real
  keywords =     {Computer Vision, Object Tracking, Linear Predictors,
                  Machine Learning},