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A Linear Program for Matching Photogrammetric Point Clouds with CityGML Building Models

In: Operations Research Proceedings 2017

Author

Listed:
  • Steffen Goebbels

    (Niederrhein University of Applied Sciences)

  • Regina Pohle-Fröhlich

    (Niederrhein University of Applied Sciences)

  • Philipp Kant

    (Niederrhein University of Applied Sciences)

Abstract

We match photogrammetric point clouds with 3D city models in order to texture their wall and roof polygons. Point clouds are generated by the Structure from Motion (SfM) algorithm from overlapping pictures and videos that in general do not have precise geo-referencing. Therefore, we have to align the clouds with the models’ coordinate systems. We do this by matching corners of buildings, detected from the 3D point cloud, with vertices of model buildings that are given in CityGML format. Due to incompleteness of our point clouds and the low number of models’ vertices, the standard registration algorithm “Iterative Closest Point” does not yield reliable results. Therefore, we propose a relaxation of a Mixed Integer Linear Program that first finds a set of correspondences between building model vertices and detected corners. Then, in a second step, we use a Linear Program to compute an optimal linear mapping based on these correspondences.

Suggested Citation

  • Steffen Goebbels & Regina Pohle-Fröhlich & Philipp Kant, 2018. "A Linear Program for Matching Photogrammetric Point Clouds with CityGML Building Models," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 129-134, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_18
    DOI: 10.1007/978-3-319-89920-6_18
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