Abstract
This paper presents an approach for camera auto-calibration from uncalibrated video sequences taken by a hand-held camera. The novelty of this approach lies in that the line parallelism is transformed to the constraints on the absolute quadric during camera autocalibration. This makes some critical cases solvable and the reconstruction more Euclidean. The approach is implemented and validated using simulated data and real image data. The experimental results show the effectiveness of the approach.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Faugeras O, Luong Q T, Maybank S. Camera Selfcalibration: Theory and experiments.Computer Vision — ECCV’92, Lecture Notes in Computer Science 588, 1992, pp.321–334.
Heyden A, Åström K. Flexible calibration: Minimal cases for auto-calibration. InProc. International Conference on Computer Vision, Kerkyra, Greece, 1999, pp.350–355.
M Pollefeys, R Koch, L Van Gool. Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters.International Journal of Computer Vision, Kluwer Academic Publishers. 1999, 32(1): 7–25.
Pollefeys M, Gool L V. Self-calibration from the absolute conic on the plane at infinity. InProc. International Conference on Computer Analysis of Images and Patterns, Kiel, Germany, 1997, pp.175–182.
Heyden A, Åström K. Euclidean reconstruction from constant intrinsic parameters. InProc. the 13th International Conference on Pattern Recognition, IEEE Computer Soc. Press, 1996, pp.339–343.
Triggs B. the absolute quadric. InProc. IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Soc. Press, 1997, pp.609–614.
M Pollefeys, R Koch, L Van Gool. Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters. InProc. International Conference on Computer Vision, 1998, pp.90–95.
Sturm P. Critical motion sequences for monocular selfcalibration and uncalibrated Euclidean reconstruction. InProc. 1997 Conference on Computer Vision and Pattern Recognition, IEEE Computer Soc. Press 1997, pp.1100–1105.
Kahl F. Critical motions and ambiguous euclidean reconstruction in auto-calibration. InProc. International Conference on Computer Vision, 1999, 1: 469–475.
Heyden A, Åström K. Euclidean reconstruction from image sequences with varying and unknown focal length and principle point. InProc. IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Soc. Press. 1997, pp.438–443.
Faugeras O. What can be seen in three dimensions with an uncalibrated stereo rig.Computer Vision — ECCV’92, Lecture Notes in Computer Science 588, 1992, pp.563–578.
Hartley R. Projective reconstruction from uncalihrated views. InApplications of Invariance in Computer Vision, Lecture Notes in Computer Science 825, 1994, pp.237–256.
Pollefeys M. Self-Calibration and Metric 3D Reconstruction from Uncalibrated Image Sequences [Dissertation]. Katholieke Universiteit Leuven, Karkinaal Mercierlaan 94–3001 Heverlee, Belgium, May 1999.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work is supported by the National Natural Science Foundation of China under Grant No.69972039 and Hong Kong RGC under Grant No. GULIK4402/99E.
Rights and permissions
About this article
Cite this article
Liu, Y., Wu, C. & Hung-Tat, T. Integrating scene parallelism in camera auto-calibration. J. Comput. Sci. & Technol. 18, 839–847 (2003). https://doi.org/10.1007/BF02945474
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02945474