Pose Estimation from Uncertain Omnidirectional Image Data Using Line-Plane Correspondences

  • Christian Gebken
  • Antti Tolvanen
  • Gerald Sommer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


Omnidirectional vision is highly beneficial for robot navigation. We present a novel perspective pose estimation for omnidirectional vision involving a parabolic central catadioptric sensor using line-plane correspondences. We incorporate an appropriate and approved stochastic method to deal with uncertainties in the data.


Image Point Rigid Body Motion Geometric Algebra Parabolic Mirror Good Linear Unbiased Estimator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Christian Gebken
    • 1
  • Antti Tolvanen
    • 1
  • Gerald Sommer
    • 1
  1. 1.Institut für Informatik, CAU KielKielGermany

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