Research of Linear Camera Calibration Based on Planar Pattern
An important step in three-dimensional reconstruction
and computer vision is camera calibration, whose objective is to
estimate the intrinsic and extrinsic parameters of each camera. In this
paper, two linear methods based on the different planes are given. In
both methods, the general plane is used to replace the calibration
object with very good precision. In the first method, after controlling
the camera to undergo five times- translation movements and taking
pictures of the orthogonal planes, a set of linear constraints of the
camera intrinsic parameters is then derived by means of homography
matrix. The second method is to get all camera parameters by taking
only one picture of a given radius circle. experiments on simulated
data and real images,indicate that our method is reasonable and is a
good supplement to camera calibration.
[1] Qiu Mao-Lin, Ma Song-Lin and Li Yi. Overview of camera calibration for
computer vision. ACTA AUTOMATICA SINICA. Vol. 23, No.1, 2000:
43-55
[2] Ma Song de and Zhang Zheng you. Computer vision- calculation theory
and algorithm. Science Press. 1998
[3] Maybank S J, Faugeras O D.A theory of self-calibration of a moving
camera. International Journal of Computer Vision,1992,8(2):123~151
[4] Xu G, Noriko Sugimoto. Algebraic derivation of the Kruppa equaltions
and a new algorithm for self-calibration of cameras. Journal of Optical
Society of America, 1999, 16(10): 2419~2424
[5] Fsugeras O D, Toscani G. The calibration problem for stereo. In: proc
IEEE Conference on Computer Vision and Pattern Recognition.1986.
15-20
[6] A Versatile Camera Calibration Technique for 3D Machine Vision", R. Y.
Tsai, IEEE J. Robotics & Automation, 1987. No. 4.323-344
[7] Wong K W. Mathematical foundation and digital analysis in close-range
photogrammetry. In: Proc. 13th Congress of the Int. Society for
Photogrammetry. 1976,1355-1373
[8] Triggs B. Auto-calibration and the absolute quadric. In: Proceedings of
Computer Vision and Pattern Recognition. 1997: 609-614
[9] Hu Zhan-Yi and Wu Fu-Zhao. A review on some active vision based
camera calibration techniques. Chinese Journal of Computers. Vol. 15,
No. 21 2001: 1150-1156
[10] Hartley R, Zisserman A. Multiple View Geometry in Computer Vision.
Cambridge, UK: Cambridge University Press, 2000
[11] Wu Fu-Zhao and Hu Zhan-Yi. View and multi-plane constraints on
homographies. ACTA AUTOMATICA SINICA Vol. 28, No. 5 690-699
[12] Jun-Sik Kim, In-So Kweon. A new calibration method for robotic
application. In: Proceedings of International Conference on Intelligent
Robotic and Systems. 2001
[1] Qiu Mao-Lin, Ma Song-Lin and Li Yi. Overview of camera calibration for
computer vision. ACTA AUTOMATICA SINICA. Vol. 23, No.1, 2000:
43-55
[2] Ma Song de and Zhang Zheng you. Computer vision- calculation theory
and algorithm. Science Press. 1998
[3] Maybank S J, Faugeras O D.A theory of self-calibration of a moving
camera. International Journal of Computer Vision,1992,8(2):123~151
[4] Xu G, Noriko Sugimoto. Algebraic derivation of the Kruppa equaltions
and a new algorithm for self-calibration of cameras. Journal of Optical
Society of America, 1999, 16(10): 2419~2424
[5] Fsugeras O D, Toscani G. The calibration problem for stereo. In: proc
IEEE Conference on Computer Vision and Pattern Recognition.1986.
15-20
[6] A Versatile Camera Calibration Technique for 3D Machine Vision", R. Y.
Tsai, IEEE J. Robotics & Automation, 1987. No. 4.323-344
[7] Wong K W. Mathematical foundation and digital analysis in close-range
photogrammetry. In: Proc. 13th Congress of the Int. Society for
Photogrammetry. 1976,1355-1373
[8] Triggs B. Auto-calibration and the absolute quadric. In: Proceedings of
Computer Vision and Pattern Recognition. 1997: 609-614
[9] Hu Zhan-Yi and Wu Fu-Zhao. A review on some active vision based
camera calibration techniques. Chinese Journal of Computers. Vol. 15,
No. 21 2001: 1150-1156
[10] Hartley R, Zisserman A. Multiple View Geometry in Computer Vision.
Cambridge, UK: Cambridge University Press, 2000
[11] Wu Fu-Zhao and Hu Zhan-Yi. View and multi-plane constraints on
homographies. ACTA AUTOMATICA SINICA Vol. 28, No. 5 690-699
[12] Jun-Sik Kim, In-So Kweon. A new calibration method for robotic
application. In: Proceedings of International Conference on Intelligent
Robotic and Systems. 2001
@article{"International Journal of Information, Control and Computer Sciences:60553", author = "Jin Sun and Hongbin Gu", title = "Research of Linear Camera Calibration Based on Planar Pattern", abstract = "An important step in three-dimensional reconstruction
and computer vision is camera calibration, whose objective is to
estimate the intrinsic and extrinsic parameters of each camera. In this
paper, two linear methods based on the different planes are given. In
both methods, the general plane is used to replace the calibration
object with very good precision. In the first method, after controlling
the camera to undergo five times- translation movements and taking
pictures of the orthogonal planes, a set of linear constraints of the
camera intrinsic parameters is then derived by means of homography
matrix. The second method is to get all camera parameters by taking
only one picture of a given radius circle. experiments on simulated
data and real images,indicate that our method is reasonable and is a
good supplement to camera calibration.", keywords = "camera calibration, 3D reconstruction, computervision", volume = "3", number = "12", pages = "2874-5", }