@InProceedings{Pajdla-DIRAC-2010,
  IS = { zkontrolovano 14 Jan 2013 },
  UPDATE   = { 2012-05-28 },
  author =      {Pajdla, Tom{\'a}{\v s} and Havlena, Michal and Heller, Jan},
  title =       {Learning from Incongruence},
  c_title =     {U{\v c}en{\'\i} z inkongruence},
  year        = { 2012 },
  pages       = { 119-127 },
  booktitle   = { Detection and Identification of Rare Audiovisual Cues },
  editor      = { Weinshall, Daphna and Anem{\" u}ller, J{\" o}rn and
		 van Gool, Luc },
  publisher =   {Springer-Verlag},
  address =     {Berlin, Germany},
  isbn        = { 978-3-642-24033-1 },
  issn =        {1860-949X},
  series =      {Studies in Computational Intelligence},
  book_pages  = { 192 },
  month =       {September},
  day =         {24},
  venue =       {Barcelona, Spain},
  organization ={Universitat Polit{\`e}cnica de Catalunya -- BarcelonaTech (UPC)},
  annote   = { We present an approach to constructing a model of the
    universe for explaining observations and making decisions based on
    learning new concepts. We use a weak statistical model, e.g. a
    discriminative classifier, to distinguish errors in measurements
    from improper modeling. We use boolean logic to combine outcomes
    of direct detectors of relevant events, e.g. presence of sound
    and presence of human shape in the field of view, into more
    complex models explaining the states in which the universe may
    appear. The process of constructing a new concept is initiated
    when a significant disagreement -- incongruence -- has been
    observed between incoming data and the current model of the
    universe. Then, a new concept, i.e. a new direct detector, is
    trained on incongruent data and combined with existing models to
    remove the incongruence. We demonstrate the concept in an
    experiment with human audio-visual detection. },
  c_annote =    {Uv{\'a}d{\'\i}me p{\v r}{\'\i}stup ke konstrukci
   modelu sv{\v e}ta k vysv{\v e}tlen{\'\i} pozorov{\'a}n{\'\i} a k
   u{\v c}in{\v e}n{\'\i} rozhodnut{\'\i} na z{\'a}klad{\v e} nau{\v
   c}en{\'\i} se nov{\'y}ch koncept{\r u}. Pou{\v z}{\'\i}v{\'a}me
   slab{\'y} statistick{\'y} model, tedy diskriminativn{\'\i}
   klasifik{\'a}tor, k rozli{\v s}en{\'\i} chyby m{\v e}{\v r}en{\'\i}
   od nespr{\'a}vn{\'e}ho modelov{\'a}n{\'\i}. Pou{\v z}{\'\i}v{\'a}me
   boolovskou logiku ke kombinaci v{\'y}stup{\r u} p{\v
   r}{\'\i}m{\'y}ch detektor{\r u} relevantn{\'\i}ch
   ud{\'a}lost{\'\i}, tedy v{\'y}skytu zvuku a tvaru {\v c}lov{\v e}ka
   v zorn{\'e}m poli, v komplexn{\v e}j{\v s}{\'\i} modely vysv{\v
   e}tluj{\'\i}c{\'\i} stavy, ve kter{\'y}ch se sv{\v e}t m{\r u}{\v
   z}e nach{\'a}zet. Proces konstrukce nov{\'e}ho konceptu je
   nastartov{\'a}n, kdy{\v z} dojde k v{\'y}znamn{\'e} neshod{\v e} --
   inkongruenci -- mezi vstupn{\'\i}mi daty a sou{\v c}asn{\'y}m
   modelem sv{\v e}ta. Nov{\'y} koncept, nap{\v r}{\'\i}klad nov{\'y}
   p{\v r}{\'\i}m{\'y} detektor, je pak natr{\'e}nov{\'a}n z
   inkongruentn{\'\i}ch data a kombinov{\'a}n s existuj{\'\i}c{\'\i}m
   modelem za {\'u}{\v c}elem odstran{\v e}n{\'\i}
   inkongruence. Demostrujeme koncept na p{\v r}{\'\i}kladu
   audiovizualn{\'\i} detekce {\v c}lov{\v e}ka.},
  keywords =    {Incongruence, Audio-visual data processing},
  authorship =  {34-33-33},
  project =     {FP6-IST-027787 DIRAC, MSM6840770038},
  volume      = { 384 },
  doi         = { 10.1007/978-3-642-24034-8_10 },
  ut_isi      = { 000302002500011 },
  psurl       = { [10.1007/978-3-642-24034-8_10.pdf] },
}