@MastersThesis{Uricar-TR-2011-05,
  IS = { zkontrolovano 01 Apr 2012 },
  UPDATE  = { 2011-08-01 },
 author =        {U{\v r}i{\v c}{\' a}{\v r}, Michal},
 supervisor =    {Franc, Vojt{\v e}ch},
 title =         {Detector of Facial Landmarks},
 school =        {Center for Machine Perception,
                  K13133 FEE Czech Technical University},
 address =       {Prague, Czech Republic},
 year =          {2011},
 month =         {June},
 day =           {7},
 type =          {{MSc Thesis CTU--CMP--2011--05}},
 issn =          {1213-2365},
 pages =         {69},
 authorship =    {100},
 psurl =         {[Uricar-TR-2011-05.pdf]},
 project =       {FP7-ICT-247525 HUMAVIPS, PERG04-GA-2008-239455 SEMISOL},
 annote =        {In this thesis we develop 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 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 changed for detection of a
   different set of landmarks. We evaluate performance of the proposed
   landmark detector on a challenging ``Labeled Face in the Wild''
   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 as well as the algorithm for supervised
   learning of its parameters from data. },
 keywords =      {Facial Landmark Detection, Support Vector Machines,
                 Structured Output Classification, Deformable Part Models},
}