IS = { zkontrolovano 05 Dec 2003 },
  UPDATE  = { 2003-04-24 },
  author =   {Wierschin, Torsten},
  title =   {Surface Patch Modeling and Perfect Simulation in Markov
                  Random Fields},
  institution =   {Center for Machine Perception, K13133 FEE Czech Technical University},
  address =   {Prague, Czech Republic},
  year =   {2003},
  month =   {April},
  type =   {Research Report},
  number =   {{CTU--CMP--2003--09}},
  issn =   {1213-2365},
  pages =        {17},
  authorship =   {100},
  psurl =   {[Wierschin-TR-2003-09.pdf]},
  project =   {MIRACLE ICA1-CT-2000-70002, MSM 212300013, 
                  GACR 102/01/1371},
  annote =   {The paper discusses various issues related to the
                  application of Gibbs models in image analysis tasks. The
                  topics include stereo modeling for partial surface
                  reconstruction, relations to cost function design in
                  Bayesian imaging and computation of functions defined in
                  terms of the proposed models by means of Markov Chain Monte
                  Carlo Simulation. In particular we study a recently
                  introduced technique called Coupling from the Past to obtain
                  samples perfectly distributed according to the target
                  distribution of the chain under concern, which in our case
                  is the Gibbs Sampler. The paper surveys known results and
                  presents some new connections in the field.},
  keywords =   {computer vision},