@Article{Tylecek-CVA-2012,
  IS = { zkontrolovano 11 Jan 2013 },
  UPDATE  = { 2013-01-11 },
  author =	 {Tyle{\v c}ek, Radim and {\v S}{\'a}ra, Radim},
  title =	 {Stochastic Recognition of Regular Structures in Facade
                  Images},
  journal =	 {IPSJ Transactions on Computer Vision and Applications},
  publisher =	 {Information Processing Society of Japan},
  address =	 {Tokyo, Japan},
  ISSN =	 {1882-6695},
  doi =		 {10.2197/ipsjtcva.4.63},
  www =		 {http://www.am.sanken.osaka-u.ac.jp/CVA/},
  year =	 {2012},
  volume =	 {4},
  pages =	 {63-70},
  month =	 {May},
  keywords =	 {Structural recognition, stochastic inference, MCMC, facades,
                  windows},
  annote =	 {We present a method for recognition of structured
    images and demonstrate it on the detection of windows in facade
    images. Given an ability to obtain local low-level data evidence
    on primitive elements of a structure (like window in a facade
    image), we determine their most probable number, attribute values
    (location, size) and neighborhood relation. The embedded structure
    is weakly modeled by pair-wise attribute constraints, which allow
    structure and attributes to mutually support each other. We use a
    very general framework of reversible jump MCMC, which allows
    simple implementation of a specific structure model and plug-in of
    almost arbitrary element classifiers. We have chosen the domain of
    window recognition in facade images to demonstrate that the result
    is an efficient algorithm achieving performance of other strongly
    informed methods for regular structures.},
  project =	 {GACR P103/12/1578},
}