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Camera Calibration from Silhouettes Under Incomplete Circular Motion with a Constant Interval Angle

  • Po-Hao Huang
  • Shang-Hong Lai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

In this paper, we propose an algorithm for camera calibration from silhouettes under circular motion with an unknown constant interval angle. Unlike previous silhouette-based methods based on surface of revolution, the proposed algorithm can be applied to sparse and incomplete image sequences. Under the assumption of circular motion with a constant interval angle, epipoles of successive image pairs remain constant and can be determined from silhouettes. A pair of epipoles formed by a certain interval angle can provide a constraint on the angle and focal length. With more pairs of epipoles recovered, the focal length can be determined from the one that most satisfies the constraints and determine the interval angle concurrently. The rest of camera parameters can be recovered from image invariants. Finally, the estimated parameters are optimized by minimizing the epipolar tangency constraints. Experimental results on both synthetic and real images are shown to demonstrate its performance.

Keywords

Circular Motion Camera Calibration Shape Reconstruction 

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References

  1. 1.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)zbMATHGoogle Scholar
  2. 2.
    Fitzgibbon, A.W., Cross, G., Zisserman, A.: Automatic 3D Model Construction for Turn-Table Sequences. In: Proceedings of SMILE Workshop on 3D Structure from Multiple Images of Large-Scale Environments, pp. 155–170 (1998)Google Scholar
  3. 3.
    Jiang, G., Tsui, H.T., Quan, L., Zisserman, A.: Single Axis Geometry by Fitting Conics. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1343–1348 (2002)CrossRefGoogle Scholar
  4. 4.
    Jiang, G., Quan, L., Tsui, H.T.: Circular Motion Geometry Using Minimal Data. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 721–731 (2004)CrossRefGoogle Scholar
  5. 5.
    Cao, X., Xiao, J., Foroosh, H., Shah, M.: Self-calibration from Turn-table Sequences in Presence of Zoom and Focus. Computer Vision and Image Understanding 102, 227–237 (2006)CrossRefGoogle Scholar
  6. 6.
    Mendonca, P.R.S., Cipolla, R.: Estimation of Epipolar Geometry from Apparent Contours: Affine and Circular Motion Cases. In: Proceedings of Computer Vision and Pattern Recognition, pp. 9–14 (1999)Google Scholar
  7. 7.
    Mendonca, P.R.S., Wong, K.-Y.K., Cipolla, R.: Epipolar Geometry from Profiles under Circular Motion. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 604–616 (2001)CrossRefGoogle Scholar
  8. 8.
    Zhang, H., Zhang, G., Wong, K.-Y.K.: Auto-Calibration and Motion Recovery from Silhouettes for Turntable Sequences. In: Proceedings of British Machine Vision Conference, pp. 79–88 (2005)Google Scholar
  9. 9.
    Zhang, G., Zhang, H., Wong, K.-Y.K.: 1D Camera Geometry and Its Application to Circular Motion Estimation. In: Proceedings of British Machine Vision Conference, pp. 67–76 (2006)Google Scholar
  10. 10.
    Matusik, W., Buehler, C., Raskar, R., Gortler, S.J., McMillan, L.: Image-Based Visual Hulls. In: Proceedings of SIGGRAPH, pp. 369–374 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Po-Hao Huang
    • 1
  • Shang-Hong Lai
    • 1
  1. 1.Department of Computer Science, National Tsing Hua University, HsinchuTaiwan

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