ICA Based Normalization of 3D Objects

نویسندگان

  • Sait Sener
  • Mustafa Unel
چکیده

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.

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تاریخ انتشار 2006