Abstract
A novel camera calibration algorithm for solving the problems of both circles based and spheres based camera calibration is proposed. By treating the images of both a circle and a sphere as a revolving stick, the introduced algorithm gives the constraint of the imaged absolute conic (IAC) with the help of the projected circle centers. It is also introduced on how to compute the projected circle centers of different calibration objects. Once the projected circle centers are computed, the Euclidean structure then can be determined by the constraint of the IAC. Experiments with simulated and real data are carried out to show the validity of the proposed camera calibration algorithm.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Meng X., Hu Z.: A new easy camera calibration technique based on circular points. Pattern Recognit. 36(5), 1155–1164 (2003)
Wu, Y., Zhu, H., Hu, Z., Wu, F.: Camera calibration from quasi-affine invariance of two parallel circles. In: Proceedings of European Conference on Computer Vision, pp. 190–202 (2004)
Gurdjos, P., Sturm, P., Wu, Y.: Euclidean structure from N ≥ 2 parallel circles: theory and algorithms. In: Proceedings of European Conference on Computer Vision, pp. 238–252 (2006)
Kim J., Gurdjos P., Kweon I.: Geometric and algebraic constraints of projected concentric circles and their applications to camera calibration. IEEE Trans. PAMI 27(4), 637–642 (2005)
Gurdjos, P., Kim, J., Kweon, I.: Euclidean structure from confocal conics: theory and application to camera calibration. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1214–1221 (2006)
Teramoto, H., Xu, G.: Camera calibration by a single image of balls: from conics to the absolute conic. In: Proceedings of Asian Conference on Computer Vision, pp. 499–506 (2002)
Agrawal, M., Davis, L.S.: Camera calibration using spheres: a semi-define programming approach. In: Proceedings of International Conference on Computer Vision, pp. 782–789 (2003)
Ying X., Zha H.: Geometric interpretations of the relation between the image of the absolute conic and sphere images. IEEE Trans. PAMI 28(12), 2031–2036 (2006)
Zhang H., Wong K.K., Zhang G.: Camera calibration with images of spheres. IEEE Trans. PAMI 29(3), 499–503 (2007)
Chen, Q., Wu, H., Wada, T.: Camera calibration with two arbitrary coplanar circles. In: Proceedings European Conference on Computer Vision, pp. 521–532 (2004)
Zhang Z.: Camera calibration with one-dimensional objects. IEEE Trans. PAMI 26(7), 892–899 (2004)
Wu F., Hu Z., Zhu H.: Camera calibration with moving one-dimensional objects. Pattern Recognit. 38(5), 755–765 (2005)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)
Fitzgibbon A.W., pilu M., Fisher R.B.: Direct least squares fitting of ellipses. IEEE Trans. PAMI 21(5), 476–480 (1999)
Zhang Z.: A flexible new technique for camera calibration. IEEE Trans. PAMI 22(11), 1330–1334 (2000)
Zhang Z.: Motion and structure from two perspective views: from essential parameters to Euclidean motion via fundamental matrix. J. Opt. Soc. Am. A 14(11), 2938–2950 (1997)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhao, Z., Liu, Y. Applications of projected circle centers in camera calibration. Machine Vision and Applications 21, 301–307 (2010). https://doi.org/10.1007/s00138-008-0162-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00138-008-0162-y