ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 541-548, 2015
https://doi.org/10.5194/isprsannals-II-3-W5-541-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
30 Sep 2015
INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
A. Wichmann1, J. Jung2, G. Sohn2, M. Kada1, and M. Ehlers1 1Institute for Geoinformatics and Remote Sensing (IGF), University of Osnabrück, Barbarastr. 22b, 49076 Osnabrück, Germany
2Department of Earth, Space Science and Engineering, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3
Keywords: Reconstruction, Three-dimensional, Building, Knowledge Base, Regularization, Point Cloud Abstract. Recent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes. In this paper, we present a method to integrate building knowledge into the data-driven approach that uses binary space partitioning (BSP) for modeling the 3D building geometry. A retrospective regularization of polygons that emerge from the BSP tree is not without difficulty because it has to deal with the 2D BSP subdivision itself and the plane definitions of the resulting partition regions to ensure topological correctness. This is aggravated by the use of hyperplanes during the binary subdivision that often splits planar roof regions into several parts that are stored in different subtrees of the BSP tree. We therefore introduce the use of hyperpolylines in the generation of the BSP tree to avoid unnecessary spatial subdivisions, so that the spatial integrity of planar roof regions is better maintained. The hyperpolylines are shown to result from basic building roof knowledge that is extracted based on roof topology graphs. An adjustment of the underlying point segments ensures that the positions of the extracted hyperpolylines result in regularized 2D partitions as well as topologically correct 3D building models. The validity and limitations of the approach are demonstrated on real-world examples.
Conference paper (PDF, 1217 KB)


Citation: Wichmann, A., Jung, J., Sohn, G., Kada, M., and Ehlers, M.: INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 541-548, https://doi.org/10.5194/isprsannals-II-3-W5-541-2015, 2015.

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