Abstract
Global calibration has direct influence on measurement accuracy of multi-camera system. The present calibration methods are hard to be applied in field calibration for the usage of complicated structures with accurate geometric or simple parts requiring overlap** view field of the system. Aiming at these problems, a new method is proposed in this paper by using two fixed plane targets with invariable pose. Objective functions are established according to constantness of the distance between original points and the axis angles of the plane targets, and nonlinear optimization is improved by means of Rodrigues transform. An apparatus is manufactured for real calibration experiments, and results verify the effectively and reliability of the method.
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References
Muhlich, M., Aach, T.: High accuracy feature detection for camera calibration: a multi-steerable approach. In: Proceeding of the 29th DAGM Conference on Pattern Recognition, pp. 284–293. Springer-Verlag, Berlin, Heidelberg (2007)
de Franca, J.A., Stemmer, M.R.: A new robust algorithmic for multi-camera calibration with a 1D object under general motions without prior knowledge of any camera intrinsic parameter. Pattern Recogn. 45, 3636–3647 (2012)
Olsen, B.D., Hoover, A.: Calibrating camera network using domino grid. Pattern Recogn. 34, 1105–1117 (2001)
Shi, Y.Q., Sun, C.K., Wang, B. G., Wang, P., Duan, H.X.: A global calibration method of multi-vision sensors in the measurement of engine cylinder joint surface holes. In: International Conference on Materials Mechatronics and Automation, pp. 1182–1188. Melbourne, Australia (2011)
Wang, Y., Yuan, F., Jiang, H., Hu, Y.H.: Novel camera calibration based on cooperative target in attitude measurement. Optik 127, 10457–10466 (2016)
Krüger, L., Wöhler, C.: Accurate chequerboard corner localisation for camera calibration. Pattern Recogn. Lett. 32, 1428–1435 (2011)
Bouguet, J.T.: Camera calibration toolbox for matlab. MRL–Intel Corp. (2004)
Lu, H., Li, Y., Chen, M., Kim, H., Serikawa, S.: Brain intelligence: go beyond artificial intelligence. Mob. Netw. Appl. 1–10 (2017)
Lu, H., Li, Y., Mu, S., Wang, D., Kim, H., Serikawa, S.: Motor anomaly detection for unmanned aerial vehicles using reinforcement learning. IEEE Int. Things J. (2017) 10.1109/JIOT.2017.2737479
Serikawa, S., Lu, H.: Underwater image dehazing using joint trilateral filter. Comput. Electr. Eng. 40(1), 41–50 (2014)
Acknowledgements
This work is partially supported by the Hunan Provincial Natural Science Foundation(No: 2015JJ5009), and the National Nature Science Foundation of China(No: 51405154, No: 51275169).
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Yang, T., Zhao, Q., Zhou, Q., Huang, D. (2018). Global Calibration of Multi-camera Measurement System from Non-overlap** Views. In: Lu, H., Xu, X. (eds) Artificial Intelligence and Robotics. Studies in Computational Intelligence, vol 752. Springer, Cham. https://doi.org/10.1007/978-3-319-69877-9_20
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DOI: https://doi.org/10.1007/978-3-319-69877-9_20
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