ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 311-316, 2016
https://doi.org/10.5194/isprs-annals-III-3-311-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
06 Jun 2016
INCREMENTAL REFINEMENT OF FAÇADE MODELS WITH ATTRIBUTE GRAMMAR FROM 3D POINT CLOUDS
Y. Dehbi, C. Staat, L. Mandtler, and L. Pl¨umer Institute of Geodesy and Geoinformation, University of Bonn, Meckenheimer Allee 174, Bonn, Germany
Keywords: Weighted Attribute Grammar, Parse Tree, Incremental Parser, Kernel Density Estimation, 3D Building Models, UAV Abstract. Data acquisition using unmanned aerial vehicles (UAVs) has gotten more and more attention over the last years. Especially in the field of building reconstruction the incremental interpretation of such data is a demanding task. In this context formal grammars play an important role for the top-down identification and reconstruction of building objects. Up to now, the available approaches expect offline data in order to parse an a-priori known grammar. For mapping on demand an on the fly reconstruction based on UAV data is required. An incremental interpretation of the data stream is inevitable. This paper presents an incremental parser of grammar rules for an automatic 3D building reconstruction. The parser enables a model refinement based on new observations with respect to a weighted attribute context-free grammar (WACFG). The falsification or rejection of hypotheses is supported as well. The parser can deal with and adapt available parse trees acquired from previous interpretations or predictions. Parse trees derived so far are updated in an iterative way using transformation rules. A diagnostic step searches for mismatches between current and new nodes. Prior knowledge on fac¸ades is incorporated. It is given by probability densities as well as architectural patterns. Since we cannot always assume normal distributions, the derivation of location and shape parameters of building objects is based on a kernel density estimation (KDE). While the level of detail is continuously improved, the geometrical, semantic and topological consistency is ensured.
Conference paper (PDF, 2961 KB)


Citation: Dehbi, Y., Staat, C., Mandtler, L., and Pl¨umer, L.: INCREMENTAL REFINEMENT OF FAÇADE MODELS WITH ATTRIBUTE GRAMMAR FROM 3D POINT CLOUDS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 311-316, https://doi.org/10.5194/isprs-annals-III-3-311-2016, 2016.

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