Omnidirectional Image Capture on Mobile Devices for Fast Automatic Generation of 2.5d Indoor Maps
Abstract
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 omni-directional 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.
Cite
Text
Pintore et al. "Omnidirectional Image Capture on Mobile Devices for Fast Automatic Generation of 2.5d Indoor Maps." IEEE/CVF Winter Conference on Applications of Computer Vision, 2016. doi:10.1109/WACV.2016.7477631Markdown
[Pintore et al. "Omnidirectional Image Capture on Mobile Devices for Fast Automatic Generation of 2.5d Indoor Maps." IEEE/CVF Winter Conference on Applications of Computer Vision, 2016.](https://mlanthology.org/wacv/2016/pintore2016wacv-omnidirectional/) doi:10.1109/WACV.2016.7477631BibTeX
@inproceedings{pintore2016wacv-omnidirectional,
title = {{Omnidirectional Image Capture on Mobile Devices for Fast Automatic Generation of 2.5d Indoor Maps}},
author = {Pintore, Giovanni and Garro, Valeria and Ganovelli, Fabio and Gobbetti, Enrico and Agus, Marco},
booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
year = {2016},
pages = {1-9},
doi = {10.1109/WACV.2016.7477631},
url = {https://mlanthology.org/wacv/2016/pintore2016wacv-omnidirectional/}
}