Abstract
This paper presents a general constructive algorithm to recover external camera parameters from a set of pairwise partial camera calibrations embedded in the structure named Camera Dependency Graph (CDG) [1] that encompasses both the feasibility and the reliability of each calibration. An edge in CDG and its weight account for the existence and for the quality of the essential matrix between the two views connected by it, respectively. Any triplet of cameras sharing visible points forms a triangle in a CDG, which permits to compute the relative scale between any two of its edges. The algorithm first selects from CDG the set of feasible paths being the shortest ones in terms of reliability that also are connected by a sequence of triangles. The global external parameters of the arrangement of cameras are computed in a process in two steps that aggregates partial calibrations, represented by triangles, along the paths connecting pairs of views taking into account the relative scales between triangles until recovering the parameters between the extremes of each path. Finally, the scales of the whole set of paths are referred to one canonical value corresponding to the edge in the CDG working as the global scale. Initial experimental results on simulated data demonstrate the usefulness and accuracy of such scheme that can be applied either alone or as the initial approximation for other calibration methods.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Verges-Llahi, J., Molodovan, D., Wada, T.: A new reliability measure for essential matrices suitable in multiple view calibration. In: Proceedings of the Int’l Conference on Vision, Image Analysis and Applications VISAPP 2008 (2008)
Hartley, R., Zisserman, A.: Multiple view geometry in computer vision, 2nd edn. Cambridge University Press, Cambridge (2003)
Longuet-Higgins, H.C.: A computer algorithm for reconstructing a scene from two projections. Nature 293, 133–135 (1981)
Triggs, B., McLauchlan, P., Hartley, R., Fitzgibbon, A.: Bundle adjustment –a modern synthesis. In: ICCV 1999: Proc. of the Int’l Workshop on Vision Algorithms, pp. 298–372 (1999)
Martinec, D., Pajdla, T.: 3d reconstruction by gluing pair-wise euclidean reconstructions. In: 3DPVT (2006)
Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. IJCV 9(2), 134–154 (1992)
Sturm, P., Triggs, B.: A factorization based algorithm for multi-image projective structure and motion. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1065, pp. 709–720. Springer, Heidelberg (1996)
Schaffalitzky, F., Zisserman, A.: Multi-view Matching for Unordered Image Sets, or How Do I Organize My Holiday Snaps? In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 414–431. Springer, Heidelberg (2002)
Martinec, D., Pajdla, T.: 3d reconstruction by fitting low-rank matrices with missing data. In: CVPR, San Diego, USA, vol. I, pp. 198–205 (2005)
Fitzgibbon, A.W., Zisserman, A.: Automatic camera recovery for closed or open image sequences. In: ECCV, vol. I, pp. 311–326 (1998)
Luong, Q.T., Faugeras, O.: The fundamental matrix: theory, algorithms, and stability analysis. Int. J. Comput. Vision, 3–17 (1996)
Csurka, G., Zeller, C., Zhang, Z., Faugeras, O.: Characterizing the uncertainty of the fundamental matrix. Computer Vision and Image Understanding (1997)
Kanatani, K.: Optimal fundamental matrix computation: Algorithm and reliability analysis. In: Proc. 6th Symp. Sensing via Image Inf. (2000)
Kanatani, K.: Statistical optimization for geometric computation: Theory and Practice. North-Holland, Amsterdam (1996)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vergés-Llahí, J., Wada, T. (2008). A General Algorithm to Recover External Camera Parameters from Pairwise Camera Calibrations. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_29
Download citation
DOI: https://doi.org/10.1007/978-3-540-69812-8_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69811-1
Online ISBN: 978-3-540-69812-8
eBook Packages: Computer ScienceComputer Science (R0)