ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume II-4/W1
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W1, 1–6, 2013
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W1, 1–6, 2013

  26 Nov 2013

26 Nov 2013

Combined Grammar for the Modeling of Building Interiors

S. Becker1, M. Peter1, D. Fritsch1, D. Philipp2, P. Baier2, and C. Dibak2 S. Becker et al.
  • 1Institute for Photogrammetry, University of Stuttgart, Stuttgart, Germany
  • 2Institute of Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany

Keywords: Building, Modeling, Abstraction, Prediction, Automation

Abstract. As spatial grammars have proven successful and efficient to deliver LOD3 models, the next challenge is their extension to indoor applications, leading to LOD4 models. Therefore, a combined indoor grammar for the automatic generation of indoor models from erroneous and incomplete observation data is presented. In building interiors where inaccurate observation data is available, the grammar can be used to make the reconstruction process robust, and verify the reconstructed geometries. In unobserved building interiors, the grammar can generate hypotheses about possible indoor geometries matching the style of the rest of the building. The grammar combines concepts from L-systems and split grammars. It is designed in such way that it can be derived from observation data fully automatically. Thus, manual predefinitions of the grammar rules usually required to tune the grammar to a specific building style, become obsolete. The potential benefit of using our grammar as support for indoor modeling is evaluated based on an example where the grammar has been applied to automatically generate an indoor model from erroneous and incomplete traces gathered by foot-mounted MEMS/IMU positioning systems.