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Non-rigid Shape Registration: A Single Linear Least Squares Framework

  • Mohammad Rouhani
  • Angel D. Sappa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7578)

Abstract

This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided.

Keywords

Regularization Term Iterative Close Point Registration Error Thin Plate Spline Control Lattice 
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 2012

Authors and Affiliations

  • Mohammad Rouhani
    • 1
  • Angel D. Sappa
    • 1
  1. 1.Computer Vision CenterEdifici O, Campus UABBellaterra, BarcelonaSpain

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