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Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps

Giovanni Pintore, Valeria Garro, Fabio Ganovelli, Enrico Gobbetti, Marco Agus
Proc. IEEE Winter Conference on Applications of Computer Vision (WACV), page 1-9 - february 2016
Download the publication : wacv2016-panorama_indoor.pdf [7.2Mo]  
We introduce a light-weight automatic method to quickly capture and recover 2.5D multi-room indoor environments scaled to real-world metric dimensions. To minimize the user effort required, we capture and analyze a single omnidirectional image per room using widely available mobile devices. Through a simple tracking of the user movements between rooms, we iterate the process to map and reconstruct entire floor plans. In order to infer 3D clues with a minimal processing and without relying on the presence of texture or detail, we define a specialized spatial transform based on catadioptric theory to highlight the room's structure in a virtual projection. From this information, we define a parametric model of each room to formalize our problem as a global optimization solved by Levenberg-Marquardt iterations. The effectiveness of the method is demonstrated on several challenging real-world multi-room indoor scenes.

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BibTex references

@InProceedings{PGGGA16,
  author       = {Pintore, G. and Garro, V. and Ganovelli, F. and Gobbetti, E. and Agus, M.},
  title        = {Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps},
  booktitle    = {Proc. IEEE Winter Conference on Applications of Computer Vision (WACV)},
  pages        = {1-9},
  month        = {february},
  year         = {2016},
  keywords     = {mobile devices, fast maps generation, indoor environments},
  doi          = {10.1109/WACV.2016.7477631},
  url          = {http://publications.crs4.it/pubdocs/2016/PGGGA16},
}

Other publications in the database

» Giovanni Pintore
» Valeria Garro
» Fabio Ganovelli
» Enrico Gobbetti
» Marco Agus