@TechReport{Tylecek-TR-2010-14,
  IS = { zkontrolovano 31 Jan 2011 },
  UPDATE  = { 2010-09-02 },
    author =      {Tyle{\v c}ek, Radim},
    supervisor =  {{\v S}{\'a}ra, Radim},
    title =       {Modelling Structures for Image-Based {3D} Reconstruction -- 
	       {PhD} Thesis Proposal},
    institution = {Center for Machine Perception, K13133 FEE
	       Czech Technical University},
    address =     {Prague, Czech Republic},
    year =        {2010},
    month =       {August},
    day =         {31},
    type =        {Research Report},
    number =      {CTU--CMP--2010--14},
    issn =        {1213-2365},
    pages =       {34},
    figures =     {9},
    authorship =  {100},
    psurl       = {[Tylecek-TR-2010-14.pdf]},
    annote   = { This thesis proposal sets its place in a particular
      area of computer vision that deals with image based
      reconstruction of scenes exhibiting structure, but also aims at
      development of more general methods for stochastic model
      inference. Abstract In the first part the state of the art in
      the chosen area is given and analyzed, starting with
      unconstrained 3D reconstruction methods, followed by discussion
      on reconstruction methods exploiting both scene structure and
      understanding to obtain more accurate models enriched by details
      and semantics. Finally we focus on facade interpretation, which
      is chosen as a representative for a class of structural computer
      vision problems. Abstract Second part presents our recent
      research results, which demonstrate hands-on experience with the
      mentioned topics that allows us to set ground for proposing next
      research interests and thesis objectives within described
      area. The stochastic Markov chain Monte Carlo framework is here
      chosen as the appropriate tool. },
    keywords =   {3D reconstruction, Structural recognition, facades, 
                  Markov Chain Monte Carlo, MCMC},
    project =    {Google Research Award, SGS10/278/OHK3/3T/13},
}