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Abstract

In this paper, we present a new 3D object normalization technique based on Independent Component Analysis (ICA). Translation and scale are eliminated by first using standard PCA whitening. ICA and the third order moments are then employed for rotation and reflection normalization. The performance of the proposed approach has been tested with range data subjected to noise and other uncertainties. Our method can be used either as a preprocessing for object modelling, or it can directly be used for 3D recognition.

Keywords

Independent Component Analysis Principle Component Analysis Independent Component Analysis Iterative Close Point Rigid Transformation 
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 2006

Authors and Affiliations

  • Sait Sener
    • 1
  • Mustafa Unel
    • 2
  1. 1.Department of Computer ScienceIstanbul Technical UniversityIstanbulTurkey
  2. 2.Faculty of Engineering and Natural SciencesSabanci UniversityIstanbulTurkey

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