IS = { zkontrolovano 30 Jan 2008 },
  UPDATE  = { 2008-01-30 },
  author =      {Thurau, Christian},
  title =       {Behavior Histograms for Action 
                 Recognition and Human Detection},
  year =        {2007},
  pages =       {299--312},
  booktitle =   {Human Motion - Understanding, Modeling, 
                 Capture and Animation},
  editor =      {Ahmed Elgammal, Bodo Rosenhahn, Reinhard Klette},
  publisher =   {Springer},
  address =     {Heidelberg, Germany},
  isbn =        {978-3-540-75702-3},
  volume =      {4814},
  series =      {Lecture Notes in Computer Science},
  book_pages =  {327},
  month =       {October},
  day =         {20},
  venue =       {Rio de Janeiro, Brazil},
  annote = {This paper presents an approach for human detection and
    simultaneous behavior recognition from images and image
    sequences. An action representation is derived by applying a
    clustering algorithm to sequences of Histogram of Oriented
    Gradient (HOG) descriptors of human motion images. For novel image
    sequences, we first detect the human by matching extracted
    descriptors with the prototypical action primitives. Given a
    sequence of assigned action primitives, we can build a histogram
    from observed motion. Thus, behavior can be classified by means of
    histogram comparison, interpreting behavior recognition as a
    problem of statistical sequence analysis. Results on publicly
    available benchmark-data show a high accuracy for action
  keywords = {behavior recognition, human detection},
  prestige =    {international},
  project =     {MRTN-CT-2004-005439},