Abstract
Camera calibration is a fundamental task in photogrammetry and computer vision. In view of the requirements in live camera characteristics, we present a novel calibration approach to obtain all the camera optimal parameters and the distortion rectification by using only a single image. The existing automatic calibration approaches inspired by the vanishing point theory or the homography matrix are not capable of entirely deal with the internal, external and the len distortion parameters simultaneously. Compared to the previous works, our approach solves the problem by applying the linear features extracted from the image and thus improves the accuracy and efficiency. Results of experiments in different scenes demonstrate the comparable performance to the traditional methods.
This work is partially supported by the Special Funds for the Frontier and Key Technology Innovation of Guangdong Province (Grant No. 2017B050506008), the Key R&D Program of Guangdong Province (Grant No. 2019B090915001), and the Program of Foshan Innovation Team of Science and Technology (Grant No. 2015IT100072).
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References
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
Corke, P.: Robotics, Vision and Control: Fundamental Algorithms in MATLAB® Second, Completely Revised, vol. 118. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-54413-7
Hu, L., Zhang, J., Zhang, S., Li, X.: A method of estimating the camera distortion parameters from a single image. J. Comput.-Aided Des. Comput. Graph. (2015)
Hartley, R., Kang, S.B.: Parameter-free radial distortion correction with center of distortion estimation. IEEE Trans. Pattern Anal. Mach. Intell. 29(8), 1309–1321 (2007)
Bukhari, F., Dailey, M.N.: Automatic radial distortion estimation from a single image. J. Math. Imaging Vis. 45(1), 31–45 (2013)
Wang, A., Qiu, T., Shao, L.: A simple method of radial distortion correction with centre of distortion estimation. J. Math. Imaging Vis. 35(3), 165–172 (2009)
Wu, F., Wei, H., Wang, X.: Correction of image radial distortion based on division model. Opt. Eng. 56(1), 013108 (2017)
Lucas, L., Loscos, C., Remion, Y.: Camera Calibration: Geometric and Colorimetric Correction. Wiley, Hoboken (2013)
Liu, D., Liu, X., Wang, M.: Camera self-calibration with lens distortion from a single image. Photogram. Eng. Remote Sens. 82(5), 325–334 (2016)
Santana-Cedrés, D., Gomez, L., Alemán-Flores, M., Salgado, A., Esclarín, J., Mazorra, L., Alvarez, L.: An iterative optimization algorithm for lens distortion correction using two-parameter models. Image Process. On Line 6, 326–364 (2016)
Boby, R.A., Saha, S.K.: Single image based camera calibration and pose estimation of the end-effector of a robot. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 2435–2440 (2016)
Espuny, F.: A new linear method for camera self-calibration with planar motion. J. Math. Imaging Vis. 27(1), 81–88 (2007)
Lee, J.: Camera calibration from a single image based on coupled line cameras and rectangle constraint. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR 2012), pp. 758–762 (2012)
Grammatikopoulos, L., Karras, G., Petsa, E.: An automatic approach for camera calibration from vanishing points. ISPRS J. Photogram. Remote Sens. 62(1), 64–76 (2007)
Li, B., Peng, K., Ying, X., Zha, H.: Simultaneous vanishing point detection and camera calibration from single images. In: Bebis, G., et al. (eds.) ISVC 2010. LNCS, vol. 6454, pp. 151–160. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17274-8_15
Broszio, H.: Automatic Line-Based Estimation of Radial Lens Distortion. IOS Press, Amsterdam (2005)
Devernay, F., Faugeras, O.D.: Automatic calibration and removal of distortion from scenes of structured environments. Invest. Trial Image Process. 2567, 62–72 (1995)
Xianyu, X.J.S.: Camera calibration with single image based on two orthogonalone-dimensional objects. Acta Optica Sinica 32(1), 145–151 (2012)
Thormählen, T., Broszio, H.: Automatic line-based estimation of radial lens distortion. Integr. Comput.-Aided Eng. 12(2), 177–190 (2005)
Alemán-Flores, M., Alvarez, L., Gomez, L., Santana-Cedrés, D.: Automatic lens distortion correction using one-parameter division models. Image Process. On Line 4, 327–343 (2014)
Santana-Cedrés, D., et al.: Invertibility and estimation of two-parameter polynomial and division lens distortion models. SIAM J. Imaging Sci. 8(3), 1574–1606 (2015)
Alvarez, L., Gomez, L., Sendra, J.R.: Algebraic lens distortion model estimation. Image Process. On Line 1, 1–10 (2010)
Alvarez, L., Gómez, L., Sendra, J.R.: An algebraic approach to lens distortion by line rectification. J. Math. Imaging Vision 35(1), 36–50 (2009)
Engelbrecht, A.P.: Computational Intelligence: An Introduction. Wiley, Hoboken (2007)
Bukhari, F., Dailey, M.N.: Robust radial distortion from a single image. In: International Symposium on Visual Computing (2010)
Geiger, A., Moosmann, F., Car, O., Schuster, B.: Automatic camera and range sensor calibration using a single shot. In: Proceedings IEEE International Conference on Robotics and Automation, pp. 3936–3943 (2012)
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Yu, S., Hong, J., Zhang, T., Yang, Z., Guan, Y. (2020). A Self-correction Based Algorithm for Single-Shot Camera Calibration. In: Chan, C.S., et al. Intelligent Robotics and Applications. ICIRA 2020. Lecture Notes in Computer Science(), vol 12595. Springer, Cham. https://doi.org/10.1007/978-3-030-66645-3_37
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