IS = { zkontrolovano 12 Jan 2009 },
  UPDATE  = { 2008-05-02 },
  author = {Vl{\v c}ek, Pavol and Svoboda, Tom{\' a}{\v s}},
  title = {Combination of Stochastic and AdaBoost Approach for Object 
           Tracking and Recognition in Video},
  year = {2008},
  pages = {122-123},
  booktitle = {Proceedings of Workshop 2008},
  editor = {Bohuslav {\v R}{\'\i}ha},
  publisher = {Czech Technical University in Prague},
  address = {Prague, Czech Republic},
  isbn = {978-80-01-04016-4},
  book_pages = {693},
  volume = {1},
  month = {February},
  day = {18-22},
  venue = {Prague, Czech Republic},
file        = { :/mnt/home.dokt/vlc/l/bib/pdf/Vlcek-WORKSHOP-2008.pdf:PDF },
annote      = { The digital video processing becomes more and more
   important area of the computer vision. Between the quite developed
   methods for static images processing and video processing there are
   many clear differences, for example the lower overall image quality
   of the video, the higher volume of the video data and the real-time
   processing requirement. In this work we focus on the task of 3D
   tracking of the human head for the application in automated
   indexing of the feature-length movies. One of the most successful
   real-time tracking algorithms is the CONDENSATION algorithm and a
   well known approach to face detection is the Viola-Jones detector,
   based on the AdaBoost learning algorithm. We combine the two
   approaches and design a 3D head tracking algorithm, which is able
   to automatically learn the head appearance and track the full-angle
   head turnaround. },
project     = { CTU0706413, specific research },
keywords    = { object tracking, object recognition, 
   head tracking, video indexing },