Finding clusters and planes from 3D line segments with application to 3D motion determination

  • Zhengyou Zhang
  • Olivier D. Faugeras
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)


We address in this paper how to find clusters based on proximity and planar facets based on coplanarity from 3D line segments obtained from stereo. The proposed methods are efficient and have been tested with many real stereo data. These procedures are indispensable in many applications including scene interpretation, object modeling and object recognition. We show their application to 3D motion determination. We have developed an algorithm based on the hypothesize-and-verify paradigm to register two consecutive 3D frames and estimate their transformation/motion. By grouping 3D line segments in each frame into clusters and planes, we can reduce effectively the complexity of the hypothesis generation phase.


Mobile Robot Extended Kalman Filter Plane Parameter Planar Facet Rigidity Constraint 
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 1992

Authors and Affiliations

  • Zhengyou Zhang
    • 1
  • Olivier D. Faugeras
    • 1
  1. 1.INRIA Sophia-AntipolisValbonne CedexFrance

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