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Depth Map Based Facade Abstraction from Noisy Multi-View Stereo Point Clouds

  • Andreas LeyEmail author
  • Olaf Hellwich
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9796)

Abstract

Multi-View Stereo offers an affordable and flexible method for the acquisition of 3D point clouds. However, these point clouds are prone to errors and missing regions. In addition, an abstraction in the form of a simple mesh capturing the essence of the surface is usually preferred over the raw point cloud measurement. We present a fully automatic pipeline that computes such a mesh from the noisy point cloud of a building facade. We leverage prior work on casting the computation of a 2.5D depth map as a labeling problem and show that this formulation has great potential as an intermediate representation in the context of building facade reconstruction.

Keywords

Point Cloud Input Image Markov Random Field Shape Grammar Smoothness Term 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This paper was supported by a grant (HE 2459/21-1) from the Deutsche Forschungsgemeinschaft (DFG).

Supplementary material

419026_1_En_13_MOESM1_ESM.pdf (1.1 mb)
Supplementary material 1 (pdf 1141 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Computer Vision and Remote Sensing GroupTU BerlinBerlinGermany

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