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Fast Random Sample Matching of 3d Fragments

  • Simon Winkelbach
  • Markus Rilk
  • Christoph Schönfelder
  • Friedrich M. Wahl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3175)

Abstract

This paper proposes an efficient pairwise surface matching approach for the automatic assembly of 3d fragments or industrial components. The method rapidly scans through the space of all possible solutions by a special kind of random sample consensus (RANSAC) scheme. By using surface normals and optionally simple features like surface curvatures, we can highly constrain the initial 6 degrees of freedom search space of all relative transformations between two fragments. The suggested approach is robust, very time and memory efficient, easy to implement and applicable to all kinds of surface data where surface normals are available (e.g. range images, polygonal object representations, point clouds with neighbor connectivity, etc.).

Keywords

Range Image Iterative Close Point Point Pair Iterative Close Point Matching Quality 
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

  • Simon Winkelbach
    • 1
  • Markus Rilk
    • 1
  • Christoph Schönfelder
    • 1
  • Friedrich M. Wahl
    • 1
  1. 1.Institute for Robotics and Process ControlTechnical University of BraunschweigBraunschweigGermany

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