Abstract
The paper presents a new calibration method of camera’s principal point and nonlinear parameters, by using the characteristic of radial nonlinear distortion and the curvatures of lines formed by control points from a single planar calibration image. The principal point is estimated by using two curved surfaces fitted by curvatures at all control points, and is the zero curvature crossing point of these two curved surfaces. The radial nonlinear parameters are computed by optimizing the curvature cost function, which adopts a backward nonlinear mapping model. The estimated results of simulated camera and real camera show that our method has higher accuracy and less computational complexity. The method can be used for on-line camera calibration where relative low calibration accuracy can be accepted and low algorithm complexity is needed, or as the initial values of complex calibration optimization algorithm.
This work was supported in part by the Leading Academic Discipline Project of Shanghai Municipal Education Commission (J50104), and the Development Foundation of Shanghai Municipal Commission of Science and Technology (11dz1205902).
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References
Zhang, Z.: Camera Calibration with One-Dimensional Objects. IEEE Trans. PAMI 26, 892–899 (2004)
Zhang, Z.: A Flexible New Technique for Camera Calibration. IEEE Trans. PAMI 22, 1330–1334 (2000)
Sturm, F., Maybank, S.J.: On Plane based Camera Calibration: A General Algorithm, Singularities, Applications. Comput. Vision Pattern Recogn., 432–437 (1999)
Kaset, S., Kitti, T., Takenobu, M.: A Determination Method of Initial Camera Parameters for Coplanar Calibration. Int. J. Control Autom. Syst. 7(5), 777–787 (2009)
Tian, Y., et al.: A Simple Centroid-based Method to Find the Principal Point of an Image Plane for a Pincushion Distortion. Int. J. Adv. Manu. Techn. 23, 110–115 (2004)
Thormählen, T., Broszio, H., Wassermann, I.: Robust Line-Based Calibration of Lens Distortion from a Single View. In: Proceedings of Mirage 2003, INRIA Rocquencourt, France, pp. 105–112 (2003)
Devernay, F., Faugeras, O.: Straight Lines Have to be Straight. Mach. Vision Appl., 14–24 (2001)
Fakhrul, Y., et al.: Establishing the Straightness of a Line for Radial Distortion Correction through Conic Fitting. Int. J. Comput. Sci. Network Security 9, 286–293 (2009)
Carlos, R., Antonio-Jose, S.: Correcting Non-linear Lens Distortion in Cameras without Using a Model. Opt. Laser Techn. 42, 628–639 (2010)
Perš, J., Kovačič, S.: Nonparametric, Model-based Radial Lens Distortion Correction Using Titled Camera Assumption. In: Proceedings of the Computer Vision Winter Workshop 2002, pp. 286–295 (2002)
Ruiz, P.E., Garcia-Mateos, G.: A Note on Principal Point Estimability. In: Proceedings of 16th International Conference on Pattern Recognition 2002, vol. 2, pp. 304–307 (2002)
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Zhu, Q. (2012). Estimating Principal Point and Nonlinear Parameters of Camera from a Planar Calibration Image. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34475-6_3
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DOI: https://doi.org/10.1007/978-3-642-34475-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34474-9
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