Tytuł artykułu
Autorzy
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
An important task for stereo vision is camera calibration, whose goal is to obtain the intrinsic and extrinsic parameters of each camera. This paper proposes a new accurate calibration method with multilevel process of camera parameters. In or- der to improve the calibration accuracy, a sub-pixel corner detection method is presented. We start with several views of a planar calibration to obtain some intrinsic camera parameters and to build an accurate model with lens distortion on a planar calibration target. Flexibly making use of geometry imaging theory, our algorithm obtains all the parameters through logical organization of solving order, accordingly avoids obtaining possible local optimized problem when solving the non-linear equation, gets over the relativity influence of every unknown parameters of traditional calibration way, and makes the error distributed among the constraint relation of parameters. Experiments with real images are carried out to verify the image correction effect and numerical robustness of our results. Compared with classical calibration techniques, that use expensive equipment and complicated mathematical computation, the proposed technique, which was verified by experiment, achieves high accuracy and reliable parameters.
Wydawca
Czasopismo
Rocznik
Tom
Strony
454--461
Opis fizyczny
Bibliogr. 12 poz.
Twórcy
autor
- College of Computer Science, Shaanxi Normal University, 710062 Xi'an, China, longford@xjtu.edu.cn
Bibliografia
- [1] Y. Yan, Q. Zhu, Z. Lin, and Q. Chen, “Camera calibration in binocular stereo vision of moving robot”, The 6th World Congress on Intelligent Control and Automation 2, 9257-9261 (2006).
- [2] F. G. King, G. V. Puskorius, and F. Yuan, “Vision guided robots for automated assembly”, Proc. IEEE Int. Conf. Robotics and Automation 3, 1611-1616 (1988).
- [3] H. D. Garner, “Development of a real-time vision based absolute orientation sensor”, PhD Dissertation, Georgia Institute of Technology, 2001.
- [4] L. Jong-Soo and J. Yu-Ho, “CCD camera calibrations and projection error analysis”, Proc. 2000 IEEE Int. Conf. Science and Technology, Korea-Russia 2, 50-55 (2000).
- [5] R. Y. Tsai, “A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses”, IEEE J. Robotics and Automation 3, 323-344 (1987).
- [6] J. Heikkilä, “Geometric camera calibration using circular control points”, IEEE T. Pattern Anal. 22, 1066-1077 (2000).
- [7] Z. Zhao, Y. Liu, and Z. Zhang, “Camera calibration with three noncollinear points under special motions”, IEEE T. Image Process. 17, 2393-2402 (2008).
- [8] Z.Y. Zhang, “A flexible new technique for camera calibration”, IEEE T. Pattern Anal. 22, 1330-1334 (2000).
- [9] R. I. Hartley, “Self-calibration from multiple views with a rotating camera”, Proc. 1994 IEEE Int. Conf. Computer Vision and Pattern Recognition, 471-478 (1994).
- [10] H. Yu and Y. Wang, “An improved self-calibration method for active stereo camera”, The 6th World Congress on Intelligent Control and Automation 1, 5186-5190 (2006).
- [11] S. Zheng, H. Hu, Q. Wang, and H. Xiao, “One method of self-calibration in spite of varying internal camera parameters”, WRI World Congress on Software Engineering 1, 230-233 (2009).
- [12] R. G. Wilson and S. A. Shafer, “What is the centre of the image”, IEEE J. Opt. Soc. Am. 11, 2946-2955 (1994).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAW-0007-0007