Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions

We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as potential wall segments, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from those potential wall segments. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and auto- matically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3d scans of indoor environments.

@InProceedings{MMJGP13,
  author       = {Mura, C. and Mattausch, O. and Jaspe Villanueva, A. and Gobbetti, E. and Pajarola, R.},
  title        = {Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions},
  booktitle    = {Proc. 13th International Conference on Computer-Aided Design and Computer Graphics},
  month        = {november},
  year         = {2013},
  keywords     = {geometric reconstruction},
  url          = {https://publications.crs4.it/pubdocs/2013/MMJGP13},
}