Efficient Random Sampling for Nonrigid Feature Matching

  • Lixin Fan
  • Timo Pylvänäinen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5875)


This paper aims to match two sets of nonrigid feature points using random sampling methods. By exploiting the principle eigenvector of corres pondence-model-linkage, an adaptive sampling method is devised to efficiently deal with non-rigid matching problems.


Random Model Uniqueness Constraint Adaptive Sampling Graph Match Thin Plate Spline 
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 2009

Authors and Affiliations

  • Lixin Fan
    • 1
  • Timo Pylvänäinen
    • 1
  1. 1.Nokia Research CenterTampereFinland

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