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

doi:10.1109/WACV.2016.7477631

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

38 Scopus citations

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.

Original language	English (US)
Title of host publication	2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509006410
DOIs	https://doi.org/10.1109/WACV.2016.7477631
State	Published - May 23 2016
Externally published	Yes
Event	IEEE Winter Conference on Applications of Computer Vision, WACV 2016 - Lake Placid, United States Duration: Mar 7 2016 → Mar 10 2016

Publication series

Name	2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016

Other

Other	IEEE Winter Conference on Applications of Computer Vision, WACV 2016
Country/Territory	United States
City	Lake Placid
Period	03/7/16 → 03/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/WACV.2016.7477631

Cite this

Pintore, G., Garro, V., Ganovelli, F., Gobbetti, E., & Agus, M. (2016). Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. In 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016 Article 7477631 (2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WACV.2016.7477631

Pintore, Giovanni ; Garro, Valeria ; Ganovelli, Fabio et al. / Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016).

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title = "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.",

author = "Giovanni Pintore and Valeria Garro and Fabio Ganovelli and Enrico Gobbetti and Marco Agus",

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doi = "10.1109/WACV.2016.7477631",

language = "English (US)",

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Pintore, G, Garro, V, Ganovelli, F, Gobbetti, E & Agus, M 2016, Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. in 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016., 7477631, 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016, Institute of Electrical and Electronics Engineers Inc., IEEE Winter Conference on Applications of Computer Vision, WACV 2016, Lake Placid, United States, 03/7/16. https://doi.org/10.1109/WACV.2016.7477631

Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. / Pintore, Giovanni; Garro, Valeria; Ganovelli, Fabio et al.
2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7477631 (2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Agus, Marco

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AB - 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.

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Pintore G, Garro V, Ganovelli F, Gobbetti E, Agus M. Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps. In 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7477631. (2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016). doi: 10.1109/WACV.2016.7477631

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

Abstract

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Bibliographical note

ASJC Scopus subject areas

Access to Document

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