Distributed 3-D Localization of Camera Sensor Networks From 2-D Image Measurements

In this paper we propose distributed algorithms that use 2-D image measurements to estimate the absolute 3-D poses of the nodes in a camera network, with the purpose of enabling higher-level tasks such as tracking and recognition. We assume that pairs of cameras with overlapping fields of view can e...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2014-12, Vol.59 (12), p.3325-3340
Main Authors: Tron, Roberto, Vidal, Rene
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Convergence
Estimates
Manifolds
Mathematical models
Networks
Noise measurement
Position (location)
Three dimensional
Vectors
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Summary:In this paper we propose distributed algorithms that use 2-D image measurements to estimate the absolute 3-D poses of the nodes in a camera network, with the purpose of enabling higher-level tasks such as tracking and recognition. We assume that pairs of cameras with overlapping fields of view can estimate their relative 3-D pose (rotation and translation direction) using standard computer vision techniques. The solution we propose combines these local, noisy estimates into a single consistent localization. We derive our algorithms from optimization problems on the manifold of poses. We provide theoretical results on the convergence of the algorithms (choice of the step-size, initialization) and on the properties of their solutions (sensitivity, uniqueness). We also provide experiments on synthetic and real data. Interestingly, our algorithm for estimating the rotation part of the poses shows some degree of robustness to outliers.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2014.2351912