The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W4-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W4-2021, 85–90, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-85-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W4-2021, 85–90, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-85-2021

  07 Oct 2021

07 Oct 2021

BUILDING ROOF VECTORIZATION WITH PPGNET

S. Hensel1, S. Goebbels1, and M. Kada2 S. Hensel et al.
  • 1Niederrhein University of Applied Sciences, Institute for Pattern Recognition, Krefeld, Germany
  • 2Technische Universität Berlin, Institute of Geodesy and Geoinformation Science Berlin, Germany

Keywords: Roof Reconstruction, Vectorization, Deep Learning, PPGNet, Orthoimages

Abstract. A challenge in data-based 3D building reconstruction is to find the exact edges of roof facet polygons. Although these edges are visible in orthoimages, convolution-based edge detectors also find many other edges due to shadows and textures. In this feasibility study, we apply machine learning to solve this problem. Recently, neural networks have been introduced that not only detect edges in images, but also assemble the edges into a graph. When applied to roof reconstruction, the vertices of the dual graph represent the roof facets. In this study, we apply the Point-Pair Graph Network (PPGNet) to orthoimages of buildings and evaluate the quality of the detected edge graphs. The initial results are promising, and adjusting the training parameters further improved the results. However, in some cases, additional work, such as post-processing, is required to reliably find all vertices.