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<p><b>Abstract</b>—Images taken with wide-angle cameras tend to have severe distortions which pull points towards the optical center. This paper proposes a simple method for recovering the distortion parameters without the use of any calibration objects. Since distortions cause straight lines in the scene to appear as curves in the image, our algorithm seeks to find the distortion parameters that map the image curves to straight lines. The user selects a small set of points along the image curves. Recovery of the distortion parameters is formulated as the minimization of an objective function which is designed to explicitly account for noise in the selected image points. Experimental results are presented for synthetic data as well as real images. We also present the idea of a polycamera which is defined as a tightly packed camera cluster. Possible configurations are proposed to capture very large fields of view. Such camera clusters tend to have a nonsingle viewpoint. We therefore provide analysis of what we call the minimum working distance for such clusters. Finally, we present results for a polycamera consisting of four wide-angle sensors having a minimum working distance of about <tmath>$4$</tmath>m. On undistorting the acquired images using our proposed technique, we create real-time high resolution panoramas.</p>
Camera calibration, wide-angle lens, radial distortion, decentering distortion, camera clusters, polycamera, nonsingle viewpoint, minimum working distance, real-time panoramic sensor.
Rahul Swaminathan, Shree K. Nayar, "Nonmetric Calibration of Wide-Angle Lenses and Polycameras", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 22, no. , pp. 1172-1178, October 2000, doi:10.1109/34.879797
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