Abstract
A linear approach using three tangent circles is proposed for determining the intrinsic parameters of cameras. A projected circle can be used to compute the image coordinate of the centre of each tangent circle and to find the points in the image corresponding to the tangent points associated with the images of the centres of the projected circles. The vanishing point can be determined along the circle diameter according to the invariance of the cross-ratio. Solving the equations for the tangent lines produced a curve in the image of the tangent point and its corresponding point. The other vanishing point can be obtained from the intersection point of the two tangent lines. With vanishing points in two orthogonal directions, the intrinsic parameters can be linearly determined. The results of our experiments show that this approach is effective and highly precise.
Similar content being viewed by others
References
Fitzgibbon AW, Pilu M, Fisher RB (1999) Direct least-squares fitting of ellipses. IEEE Trans Pattern Anal Mach Intell 26(5):476–480
Harris C, Stephens MJ (1988) A combined corner and edge detector, Proc. of the 4th Alvey Vision Conference. Plessey, United Kingdom, 147–151
Hu Z, Tan Z (2006) Camera calibration with conics fitting and circular points. J Xi'an Jiaotong Univ 40(10):1065–1068
Junejo IN, Foroosh H (2010) GPS coordinates estimation and camera calibration from solar shadows. Comput Vis Image Underst 114(9):991–1003
Kim J, Gurdjos P, Kweon I (2005) Geometric and algebraic constraints of projected concentric circles and their applications to camera calibration. IEEE Trans Pattern Anal Mach Intell 27(4):637–642
Meng X, Hua L, Hu Z (2000) A new easy camera calibration technique based on circular points, Proc. of the BMVC’2000, Bristol, UK, 496–505
Richard H, Andrew Z (2000) Multiple view geometry in computer vision. Cambridge University Press, Cambridge
Semple J, Kneebone G (1952) Algebraic projective geometry. Oxford University Press, London
Wu L, Cao X, Foroosh H (2010) Camera calibration and geo-location estimation from two shadow trajectories. Comput Vis Image Underst 114(8):915–927
Wu Y, Li X, Wu F, Hu Z (2006) Coplanar circle, quasi-affine invariance and calibration. Image Vis Comput 24(4):319–326
Wu Y, Zhu H, Hu Z, Wu F (2004) Camera calibration from the quasi-affine invariance of two parallel circles, Proc. of the ECCV, Beijing, CN, 190–202
Yang C, Sun F, Z Hu (2000) Planar conic based camera calibration, Proc. 15th IEEE Conf. on Pattern Recognition, Barcelona, Spain, 555–558
Zhang Z (1997) Motion and structure from two perspective views: from essential parameters to Euclidean motion via fundamental matrix. J Opt Soc Am 14(11):2938–2950
Zhang Z (2000) A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell 22(11):1330–1334
Zhao Z, Liu Y (2010) Applications of projected center of circles in camera calibration. Mach Vision Appl 21(3):301–307
Zhao Y, Shang X, Ding H (2011) Matching approach based on cross-correlation and affine transformation. International Journal of Digital Content Technology and its Applications(JDCTA) (5):249–256
Acknowledgments
The author wishes to thank the anonymous reviewers for their many valuable suggestions. This research was supported by the Nation Natural Science Foundation of China (No.11361074), the Natural Foundation of Yunnan Province, China (2011FB017), and the Scientific Research Foundation of Yunnan Education Department of China (2013Y167).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, X., Zhao, Y. A linear approach for determining camera intrinsic parameters using tangent circles. Multimed Tools Appl 74, 5709–5723 (2015). https://doi.org/10.1007/s11042-014-1879-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-014-1879-4