Omnidirectional image capture

Research results of the VASCO project focusing on indoor reconstruction has been selected for a publication and presentation at the IEEE Winter Conference on Applications of Computer Vision ! It will be held March 7-9, 2016 at the Crowne Plaza resort in Lake Placid, NY, USA. Meet us there !

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.

Reference

Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. Giovanni Pintore, Valeria Garro, Fabio Ganovelli, Marco Agus, and Enrico Gobbetti. In Proc. IEEE Winter Conference on Applications of Computer Vision (WACV), February 2016.

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