Reconstruction of Sewer Shaft Profiles from Fisheye-Lens Camera Images

  • Sandro Esquivel
  • Reinhard Koch
  • Heino Rehse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5748)

Abstract

In this paper we propose a robust image and sensor based approach for automatic 3d model acquisition of sewer shafts from survey videos captured by a downward-looking fisheye-lens camera while lowering it into the shaft. Our approach is based on Structure from Motion adjusted to the constrained motion and scene, and involves shape recognition in order to obtain the geometry of the scene appropriately. The approach has been implemented and applied successfully to the practical stage as part of a commercial software.

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References

  1. 1.
    Cooper, D., Pridmore, T.P., Taylor, N.: Towards the Recovery of Extrinsic Camera Parameters from Video Records of Sewer Surveys. Machine Vision and Applications 11, 53–63 (1998)CrossRefGoogle Scholar
  2. 2.
    Kannala, J.: Measuring the Shape of Sewer Pipes from Video. Master thesis, Helsinki University of Technology, Helsinki (2004)Google Scholar
  3. 3.
    Kannala, J., Brandt, S.S., Heikkilä, J.: Measuring and Modelling Sewer Pipes from Video. Machine Vision and Applications 19(2), 73–83 (2008)CrossRefGoogle Scholar
  4. 4.
    Zhang, Z.: Flexible Camera Calibration by Viewing a Plane from Unknown Orientations. In: Proc. ICCV, pp. 666–673 (1999)Google Scholar
  5. 5.
    Scaramuzza, D., Martinelli, A., Siegwart, R.: A Flexible Technique for Accurate Omnidirection Camera Calibration and Structure from Motion. In: Proc. ICVS, p. 45 (2006)Google Scholar
  6. 6.
    Chang, P., Hebert, M.: Omni-Directional Structure from Motion. In: Proc. IEEE Workshop on Omnidirectional Vision, p. 127 (2000)Google Scholar
  7. 7.
    Bartczak, B., Köser, K., Woelk, F., Koch, R.: Extraction of 3D Freeform Surfaces as Visual Landmarks for Real-Time Tracking. Journal of Real-Time Image Processing 2(2–3), 81–101 (2007)CrossRefGoogle Scholar
  8. 8.
    Tomasi, C., Kanade, T.: Detection and Tracking of Point Features. Carnegie Mellon University Technical Report CMU-CS-91-132, 04/1991Google Scholar
  9. 9.
    Pratt, V.: Direct Least Squares Fitting of Algebraic Surfaces. Computer Graphics 21(4), 145–152 (1987)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Fitzgibbon, A., Pilu, M., Fisher, R.: Direct Least Squares Fitting of Ellipses. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(5), 476–480 (1999)CrossRefGoogle Scholar
  11. 11.
    Chauduri, D., Samal, A.: A Simple Method for Fitting of Boundary Rectangles to Closed Regions. Pattern Recognition 40(7), 1981–1989 (2007)CrossRefMATHGoogle Scholar
  12. 12.
    Dierckx, P.: Curve and Surface Fitting with Splines. Oxford University Press, Oxford (1993)MATHGoogle Scholar
  13. 13.
    Burger, B., Fiedler, M., Gellrich, J., Reuter, H.-P.: Schachtinspektion in neuer Qualität. Bauwirtschaftliche Information UmweltBau Nr. 1, 02/2009Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sandro Esquivel
    • 1
  • Reinhard Koch
    • 1
  • Heino Rehse
    • 2
  1. 1.Christian-Albrechts-UniversityKielGermany
  2. 2.IBAK Helmut Hunger GmbH & Co. KGKielGermany

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