Jörg Schmittwilken and Jens Saatkamp and Wolfgang Förstner and Thomas Kolbe and Lutz Plümer, "A Semantic Model of Stairs in Building Collars", Photogrammetrie, Fernerkundung, Geoinformation PFG., pp. 415-428. 2007.

• Abstract
• BibTeX
• Download

The automated extraction of high resolution 3D building models from imagery and laser scanner data requires strong models for all features which are observable at a large scale. In this paper we give a semantic model of stairs. They play a prominent role in the transition from buildings to the surrounding terrain or infrastructure. We name the transition area between terrain and building collar, and the focus is on stairs in building collars. Simple and complex stairways are represented by UML class diagrams along with constraints reflecting semantic and functional aspects in OCL. A systematic derivation of an attribute grammar consisting of production and semantic rules from UML/OCL is presented. Finally, we show how hypotheses with comprehensive predictions may be derived from observations using mixed integer/real programming driven by grammar rules.

@article{Schmittwiken2007Semantic,
  author = {Schmittwilken, J\"org and Saatkamp, Jens and F\"orstner, Wolfgang and Kolbe, Thomas and Pl\"umer, Lutz},
  title = {A Semantic Model of Stairs in Building Collars},
  journal = {Photogrammetrie, Fernerkundung, Geoinformation PFG},
  year = {2007},
  pages = {415--428}
}

Jens Saatkamp and Jörg Schmittwilken, "Generative Models and Markov Chain Monte Carlo Techniques for Detection and Reconstruction of Stairs from Point Clouds", In Proceedings of the ISPRS Workshop on Updating Geo-spatial Databases with Imagery & The 5th ISPRS Workshop on Dynamic and Multi-dimensional GIS. Jiang, Jie and Zhao, Renliang (Eds.) Urumqi, China, August, 2007. Vol. XXXVI(part 4/W54), pp. 111-119. 2007.

• Abstract
• BibTeX
• Download

The paper describes an approach for the automatical reconstruction of homogeneous straight stairs from point cloud data by using a generative model and Markov Chain Monte Carlo techniques for estimating the parameters. Parameters for a generative model for stairs are presented. The six parameters of this 2D model are determined with a maximum-a-posteriori estimation approach. For all parameters prior probability distributions are chosen. Two types of likelihood functions are introduced. It is shown that four of the parameters under certain conditions can be determined via MCMC. Some results are presented.

@inproceedings{Saatkamp2007Generative,
  author = {Saatkamp, Jens and Schmittwilken, J\"org},
  editor = {Jiang, Jie and Zhao, Renliang},
  title = {Generative Models and Markov Chain Monte Carlo Techniques for Detection and Reconstruction of Stairs from Point Clouds},
  booktitle = {Proceedings of the ISPRS Workshop on Updating Geo-spatial Databases with Imagery \& The 5th ISPRS Workshop on Dynamic and Multi-dimensional GIS},
  year = {2007},
  volume = {XXXVI},
  number = {part 4/W54},
  pages = {111--119}
}