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/Author (Junzhi Guan, Francis Deboeverie, Maarten Slembrouck, Dirk van Haerenborgh, Dimitri van Cauwelaert, Peter Veelaert, Wilfried Philips)
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/Keywords ("Camera network; extrinsic calibration; sphere-based calibration; orthogonal procrustes")
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/Subject ( 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. )
/Title (Extrinsic Calibration of Camera Networks Using a Sphere)
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Junzhi Guan, Francis Deboeverie, Maarten Slembrouck, Dirk van Haerenborgh, Dimitri van Cauwelaert, Peter Veelaert, Wilfried Philips
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.
Extrinsic Calibration of Camera Networks Using a Sphere
Camera network; extrinsic calibration; sphere-based calibration; orthogonal procrustes
2015-08-04T13:52:36+08:00
LaTeX with hyperref package
2015-08-04T13:53:24+08:00
2015-08-04T13:53:24+08:00
"Camera network; extrinsic calibration; sphere-based calibration; orthogonal procrustes"
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