Reconstruction of Façade Structures Using a Formal Grammar and RjMCMC

  • Nora Ripperda
  • Claus Brenner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


Today’s processes to extract man-made objects from measurement data are quite traditional. Often, they are still point based, with the exception of a few systems which allow to automatically fit simple primitives to measurement data. At the same time, demands on the data are steadily growing. The need to be able to automatically transform object representations, for example, in order to generalize their geometry, enforces a structurally rich object description. Likewise, the trend towards more and more detailed representations requires to exploit structurally repetitive and symmetric patterns present in man-made objects, in order to make extraction cost-effective. In this paper, we address the extraction of building façades in terms of a structural description. As has been described previously by other authors, we use a formal grammar to derive a structural façade description in the form of a derivation tree. We use a process based on reversible jump Markov Chain Monte Carlo (rjMCMC) to guide the application of derivation steps during the construction of the tree.


Point Cloud Markov Chain Monte Carlo Method Derivation Tree Derivation Rule Reversible Jump 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nora Ripperda
    • 1
  • Claus Brenner
    • 1
  1. 1.Institute of Cartography and GeoinformaticsUniversity of HannoverGermany

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