Pose Estimation for Sensors Which Capture Cylindric Panoramas

  • Fay Huang
  • Reinhard Klette
  • Yun-Hao Xie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


We show that there exist linear models for sensor pose estimation for multi-view panoramas defined by a symmetric or leveled pair of cylindric images. We assume that pairs of corresponding points have been detected already in those pairs of panoramas. For the first time a cost function is formulated whose minimization solves the pose estimation problem for these two general cases of multi-view panoramas, specified by unconstrained sensor parameter values but only minor constraints on sensor poses. (Note that due to the non-linearity of the panoramic projection geometry, the modeling of sensor pose estimation typically results into non-linear forms which incur numerical instability.)


Pose estimation panoramic sensor cylindric panorama 


  1. 1.
    Ishiguro, H., Yamamoto, M., Tsuji, S.: Omni-directional stereo. PAMI 14, 257–262 (1992)CrossRefGoogle Scholar
  2. 2.
    Kang, S.B., Szeliski, R.: 3-d scene data recovery using omnidirectional multibaseline stereo. IJCV 25, 167–183 (1997)CrossRefGoogle Scholar
  3. 3.
    Peleg, S., Ben-Ezra, M.: Stereo panorama with a single camera. In: Proc. CVPR 1999, Fort Collins, Colorado, USA, pp. 395–401 (1999)Google Scholar
  4. 4.
    Shum, H.Y., He, L.W.: Rendering with concentric mosaics. In: Proc. SIGGRAPH 1999, Los Angeles, California, USA, pp. 299–306 (1999)Google Scholar
  5. 5.
    Huang, F., Klette, R., Scheibe, K.: Panoramic Imaging: Sensor-Line Cameras and Laser Range-Finders. Wiley, West Sussex (2008)CrossRefGoogle Scholar
  6. 6.
    Huang, F., Wei, S.K., Klette, R.: Geometrical fundamentals of polycentric panoramas. In: Proc. ICCV 2001, Vancouver, Canada, vol. I, pp. 560–565 (2001)Google Scholar
  7. 7.
    Li, Y., Shum, H.Y., Tang, C.K., Szeliski, R.: Stereo reconstruction from multiperspective panoramas. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 45–62 (2004)CrossRefGoogle Scholar
  8. 8.
    Scheibe, K., Suppa, M., Hirschmäller, H., Strackenbrock, B., Huang, F., Liu, R., Hirzinger, G.: Multi-scale 3d-modeling. In: Chang, L.-W., Lie, W.-N. (eds.) PSIVT 2006. LNCS, vol. 4319, pp. 96–107. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Murray, D.: Recovering range using virtual multicamera stereo. CVIU 61, 285–291 (1995)Google Scholar
  10. 10.
    Seitz, S.: The space of all stereo images. In: Proc. ICCV 2001, Vancouver, Canada, pp. 26–33 (2001)Google Scholar
  11. 11.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge Uni. Press, United Kingdom (2000)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Fay Huang
    • 1
  • Reinhard Klette
    • 2
  • Yun-Hao Xie
    • 1
  1. 1.Institute of Computer Science and Information EngineeringNational Ilan UniversityTaiwan, R.O.C.
  2. 2.Department of Computer ScienceThe University of AucklandNew Zealand

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