
Proceedings Paper
Automatic loop closure detection using multiple cameras for 3D indoor localizationFormat | Member Price | Non-Member Price |
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Paper Abstract
Automated 3D modeling of building interiors is useful in applications such as virtual reality and environment
mapping. We have developed a human operated backpack data acquisition system equipped with a variety of
sensors such as cameras, laser scanners, and orientation measurement sensors to generate 3D models of building
interiors, including uneven surfaces and stairwells. An important intermediate step in any 3D modeling system,
including ours, is accurate 6 degrees of freedom localization over time. In this paper, we propose two approaches
to improve localization accuracy over our previously proposed methods. First, we develop an adaptive localization
algorithm which takes advantage of the environment's floor planarity whenever possible. Secondly, we show that
by including all the loop closures resulting from two cameras facing away from each other, it is possible to reduce
localization error in scenarios where parts of the acquisition path is retraced. We experimentally characterize
the performance gains due to both schemes.
Paper Details
Date Published: 10 February 2012
PDF: 12 pages
Proc. SPIE 8296, Computational Imaging X, 82960V (10 February 2012); doi: 10.1117/12.916639
Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)
PDF: 12 pages
Proc. SPIE 8296, Computational Imaging X, 82960V (10 February 2012); doi: 10.1117/12.916639
Show Author Affiliations
John Kua, Univ. of California, Berkeley (United States)
Nicholas Corso, Univ. of California, Berkeley (United States)
Nicholas Corso, Univ. of California, Berkeley (United States)
Avideh Zakhor, Univ. of California, Berkeley (United States)
Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)
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