Keyframe Selection for Camera Motion and Structure Estimation from Multiple Views

  • Thorsten Thormählen
  • Hellward Broszio
  • Axel Weissenfeld
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3021)


Estimation of camera motion and structure of rigid objects in the 3D world from multiple camera images by bundle adjustment is often performed by iterative minimization methods due to their low computational effort. These methods need a robust initialization in order to converge to the global minimum. In this paper a new criterion for keyframe selection is presented. While state of the art criteria just avoid degenerated camera motion configurations, the proposed criterion selects the keyframe pairing with the lowest expected estimation error of initial camera motion and object structure. The presented results show, that the convergence probability of bundle adjustment is significantly improved with the new criterion compared to the state of the art approaches.


Feature Point Augmented Reality Camera Motion Camera Parameter Rigid Object 
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 2004

Authors and Affiliations

  • Thorsten Thormählen
    • 1
  • Hellward Broszio
    • 1
  • Axel Weissenfeld
    • 1
  1. 1.Information Technology LaboratoryUniversity of HannoverHannoverGermany

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