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Sensors 2015, 15(8), 18985-19005; doi:10.3390/s150818985

Extrinsic Calibration of Camera Networks Using a Sphere

Image Processing and Interpretation, TELIN, Ghent University/iMinds, Sint Pietersnieuwstraat 41, 9000 Gent, Belgium
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Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 8 July 2015 / Revised: 8 July 2015 / Accepted: 30 July 2015 / Published: 4 August 2015
(This article belongs to the Section Sensor Networks)
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Abstract

In this paper, we propose a novel extrinsic calibration method for camera networks using a sphere as the calibration object. First of all, we propose an easy and accurate method to estimate the 3D positions of the sphere center w.r.t. the local camera coordinate system. Then, we propose to use orthogonal procrustes analysis to pairwise estimate the initial camera relative extrinsic parameters based on the aforementioned estimation of 3D positions. Finally, an optimization routine is applied to jointly refine the extrinsic parameters for all cameras. Compared to existing sphere-based 3D position estimators which need to trace and analyse the outline of the sphere projection in the image, the proposed method requires only very simple image processing: estimating the area and the center of mass of the sphere projection. Our results demonstrate that we can get a more accurate estimate of the extrinsic parameters compared to other sphere-based methods. While existing state-of-the-art calibration methods use point like features and epipolar geometry, the proposed method uses the sphere-based 3D position estimate. This results in simpler computations and a more flexible and accurate calibration method. Experimental results show that the proposed approach is accurate, robust, flexible and easy to use. View Full-Text
Keywords: Camera network; extrinsic calibration; sphere-based calibration; orthogonal procrustes Camera network; extrinsic calibration; sphere-based calibration; orthogonal procrustes
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Guan, J.; Deboeverie, F.; Slembrouck, M.; van Haerenborgh, D.; van Cauwelaert, D.; Veelaert, P.; Philips, W. Extrinsic Calibration of Camera Networks Using a Sphere. Sensors 2015, 15, 18985-19005.

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