Volume XLII-4/W10 | Copyright
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W10, 47-54, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W10-47-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Sep 2018

12 Sep 2018

AUTOMATIC 3D RECONSTRUCTION OF BUILDINGS ROOF TOPS IN DENSELY URBANIZED AREAS

M. Gkeli and C. Ioannidis M. Gkeli and C. Ioannidis
  • Laboratory of Photogrammetry, School of Rural and Surveying Engineering, National Technical University of Athens, Greece

Keywords: 3D reconstruction, RANSAC, plane fitting, moments of inertia, Automation, Building

Abstract. 3D reconstruction of the urban environment constitutes a well-studied problem in the field of photogrammetry and computer vision, attracting the growing interest of the scientific community, for many years. Although the current state of the art present very impressive results, there is still room for improvements. The production of reliable and accurate 3D reconstructions is useful for a wide range of applications, such as urban planning, GIS, tax assessment, cadastre, insurance, 3D city modelling, etc. In this paper, a methodology for the automatic 3D reconstruction of buildings roof tops in densely urbanized areas, utilizing dense point clouds data, is proposed. It consists of three (3) main phases, each of which comprises a set of processing steps. In the first phase, the point cloud is simplified and smoothed. Outliers and non-roof elements are detected and removed utilizing shape, position and area criteria. In the second phase, the geometry buildings roof tops is optimized, by detecting and normalizing the edges. In the last phase, the reconstruction of the buildings roof tops is conducted. A progressive process, utilizing a plane fitting algorithm in combination with Screened Poisson Surface Reconstruction is performed. Buildings roof tops surfaces are produced and optimized. A software tool is developed and utilized for the implementation of the proposed methodology. The produced results are assessed and a comparison with another open-source software is conducted. The proposed methodology seems to be effective providing satisfactory results, as it can manage properly the really noisy point clouds of densely urbanized environments.

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