@InProceedings{Uricar-Franc-Hlavac-VISAPP-2012,
  IS = { zkontrolovano 14 Jan 2013 },
  UPDATE  = { 2012-03-02 },
  author =      {U{\v{r}}i{\v{c}}{\'{a}}{\v{r}}, Michal and 
                 Franc, Vojt{\v{e}}ch and Hlav{\'{a}}{\v{c}}, V{\'{a}}clav },
  title =       {Detector of Facial Landmarks Learned by the Structured Output {SVM}},
  c_title =     {Detektor v{\'{y}}znamn{\'{y}}ch bod\r{u} na lidsk{\'{e}} 
                 tv{\'{a}}{\v{r}}i u{\v{c}}en{\'{y}} pomoc{\'{i}} Structured Output {SVM}},
  year =        {2012},
  pages =       {547-556},
  booktitle =   {VISAPP '12: Proceedings of the 7th International Conference on Computer Vision Theory and Applications},
  editor =      {Csurka, Gabriela and Braz, Jos{\'{e}}},
  publisher =   {SciTePress - Science and Technology Publications},
  address =     {Porto, Portugal},
  volume =      {1},
  isbn =        {978-989-8565-03-7},
  book_pages =  {747},
  month =       {February},
  day =         {24-26},
  venue =       {Rome, Italy},
  annote =      {In this paper we describe a detector of facial
    landmarks based on the Deformable Part Models. We treat the task
    of landmark detection as an instance of the structured output
    classification problem. We propose to learn the parameters of the
    detector from data by the Structured Output Support Vector
    Machines algorithm. In contrast to the previous works, the
    objective function of the learning algorithm is directly related
    to the performance of the resulting detector which is controlled
    by a user-defined loss function. The resulting detector is
    real-time on a standard PC, simple to implement and it can be
    easily modified for detection of a different set of landmarks.  We
    evaluate performance of the proposed landmark detector on a
    challenging ''Labeled Faces in the Wild`` (LFW) database. The
    empirical results demonstrate that the proposed detector is
    consistently more accurate than two public domain implementations
    based on the Active Appearance Models and the Deformable Part
    Models. We provide an open-source implementation of the proposed
    detector and the manual annotation of the facial landmarks for all
    images in the LFW database.},
  c_annote =    {V tomto {\v{c}}l{\'{a}}nku popisujeme detektor
    v{\'{y}}znamn{\'{y}}ch bod\r{u} na lidsk{\'{e}} tv{\'{a}}{\v{r}}i,
    zalo{\v{z}}en{\'{y}} na Deformable Part Models. Tento
    probl{\'{e}}m {\v{r}}e{\v{s}}{\'{i}}me jako instanci structured
    output klasifikace. Navrhujeme u{\v{c}}en{\'{i}} parametr\r{u}
    detektoru z dat pomoc{\'{i}} algoritmu Structured Output Support
    Vector Machines. Narozd{\'{i}}l od p{\v{r}}ede{\v{s}}l{\'{y}}ch
    prac{\'{i}}, je kriteri{\'{a}}ln{\'{i}} funkce
    u{\v{c}}{\'{i}}c{\'{i}}ho algoritmu p{\v{r}}{\'{i}}mo
    souvisl{\'{a}} s v{\'{y}}konem v{\'{y}}sledn{\'{e}}ho detektoru a
    je kontrolov{\'{a}}na u{\v{z}}ivatelem definovanou ztr{\'{a}}tovou
    funkc{\'{i}}. V{\'{y}}sledn{\'{y}} detektor je realtime na
    standardn{\'{i}}m PC, jednodu{\v{s}}e implementovateln{\'{y}} a
    snadno modifikovateln{\'{y}} na jinou sadu v{\'{y}}znamn{\'{y}}ch
    bod\r{u}. V{\'{y}}kon navrhovan{\'{e}}ho detektoru
    m{\v{e}}{\v{r}}{\'{i}}me na obt{\'{i}}{\v{z}}n{\'{e}} ``Labeled
    Faces in the Wild'' (LFW) datab{\'{a}}zi. Empirick{\'{e}}
    v{\'{y}}sledky demonstruj{\'{i}}, {\v{z}}e navrhovan{\'{y}}
    detektor je konzistentn{\v{e}} p{\v{r}}esn{\v{e}}j{\v{s}}{\'{i}}
    ne{\v{z}} dv{\v{e}} ve{\v{r}}ejn{\v{e}} dostupn{\'{e}}
    implementace zalo{\v{z}}en{\'{e}} na Active Appearance Models a
    Deformable Part Models. Poskytujeme open-source implementaci
    navrhovan{\'{e}}ho detektoru a manualn{\'{i}} anotaci bod\r{u} na
    lidsk{\'{e}} tv{\'{a}}{\v{r}}i pro celou LFW datab{\'{a}}zi.  },
  keywords =    {Facial Landmark Detection, Structured Output Classification, 
                 Support Vector Machines, Deformable Part Models},
  prestige =    {important},
  authorship =  {50-40-10},
  project =     {FP7-ICT-247525 HUMAVIPS, PERG04-GA-2008-239455 SEMISOL, 1M0567},
  psurl = {[UricarFrancHlavac-VISAPP2012.pdf]},
  www = {http://www.visapp.visigrapp.org},
  acceptance_ratio = {0.57},
}