@TechReport{Uricar-CAK-2013-47,
  IS = { zkontrolovano 20 Jan 2014 },
  UPDATE  = { 2014-01-20 },
  author =       {U{\v r}i{\v c}{\'a}{\v r}, Michal},
  supervisor =   {Franc, Vojt{\v e}ch and Hlav{\'a}{\v c}, V{\'a}clav},
  title =        {Multi-view Facial Landmark Detector -- {PhD} Thesis
                  Proposal},
  institution =  {Department of Cybernetics, Faculty of Electrical Engineering,
                  Czech Technical University},
  address =      {Prague, Czech Republic},
  year =         {2013},
  month =        {August},
  day =          {},
  type =         {Research Report},
  number =       {K333--47/13, CTU--CMP--2013--21},
  pages =        {56},
  figures =      {3},
  authorship =   {100},
  psurl =        {[Uricar-TR-2013-21.pdf]},
  project =      {1M0567, SGS12/187/OHK3/3T/13, TACR TE01020197},
  annote =       {In this report we outline recent works on the facial
                  landmark detection. We categorize the work of others to
                  three main groups. Namely, the local independent detectors,
                  the global methods and the combined approaches. The emphasis
                  is on the category of detectors using the pictorial
                  structures, also known as deformable part models (DPM). Some
                  papers, which are not dealing with the facial landmark
                  detection directly but which still contain useful ideas are
                  also mentioned. After the literature survey, we give an
                  outline of our contributions to the topic of facial landmark
                  detection. Namely, we summarize our work on the near-frontal
                  detector and the work, which we did for speeding up the
                  learning novel algorithms we proposed to speed up learning
                  of this detector from fully annotated data. Finally, we
                  identify the open issues arising in facial landmark
                  detection based on the DPM. These open issues will serve as
                  a direction for our future work towards the Ph.D. thesis.},
  keywords =     {Facial Landmark Detection, Structured Output Classification,
                  Deformable Part Models, Pictorial Structures, Shape Models},
}