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Calibrating Distributed Camera Networks Using Belief Propagation

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 060696 (2006) Cite this article

Abstract

We discuss how to obtain the accurate and globally consistent self-calibration of a distributed camera network, in which camera nodes with no centralized processor may be spread over a wide geographical area. We present a distributed calibration algorithm based on belief propagation, in which each camera node communicates only with its neighbors that image a sufficient number of scene points. The natural geometry of the system and the formulation of the estimation problem give rise to statistical dependencies that can be efficiently leveraged in a probabilistic framework. The camera calibration problem poses several challenges to information fusion, including overdetermined parameterizations and nonaligned coordinate systems. We suggest practical approaches to overcome these difficulties, and demonstrate the accurate and consistent performance of the algorithm using a simulated 30-node camera network with varying levels of noise in the correspondences used for calibration, as well as an experiment with 15 real images.

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Authors and Affiliations

  1. Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

    Dhanya Devarajan & Richard J. Radke

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  1. Dhanya Devarajan
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  2. Richard J. Radke
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Correspondence to Dhanya Devarajan.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Devarajan, D., Radke, R.J. Calibrating Distributed Camera Networks Using Belief Propagation. EURASIP J. Adv. Signal Process. 2007, 060696 (2006). https://doi.org/10.1155/2007/60696

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