Volume XLI-B3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 71-74, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 71-74, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  09 Jun 2016

09 Jun 2016

3D Building Reconstruction Using Dense Photogrammetric Point Cloud

S. Malihi1,2, M. J. Valadan Zoej1, M. Hahn2, M. Mokhtarzade1, and H. Arefi3 S. Malihi et al.
  • 1Faculty of Geodesy and Geomatics Engineering, Khaje Nasir Toosi University of Technology, Tehran, Iran
  • 2University of Applied Sciences, Stuttgart, Germany
  • 3School of Surveying and Geospatial Engineering, University of Tehran, Tehran, Iran

Keywords: Building reconstruction, UAV, Point Cloud, Data-driven, Occlusion

Abstract. Three dimensional models of urban areas play an important role in city planning, disaster management, city navigation and other applications. Reconstruction of 3D building models is still a challenging issue in 3D city modelling. Point clouds generated from multi view images of UAV is a novel source of spatial data, which is used in this research for building reconstruction. The process starts with the segmentation of point clouds of roofs and walls into planar groups. By generating related surfaces and using geometrical constraints plus considering symmetry, a 3d model of building is reconstructed. In a refinement step, dormers are extracted, and their models are reconstructed. The details of the 3d reconstructed model are in LoD3 level, with respect to modelling eaves, fractions of roof and dormers.