A Learning Approach to 3D Object Representation for Classification

  • Indriyati Atmosukarto
  • Linda G. Shapiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)

Abstract

In this paper we describe our 3D object signature for 3D object classification. The signature is based on a learning approach that finds salient points on a 3D object and represent these points in a 2D spatial map based on a longitude-latitude transformation. Experimental results show high classification rates on both pose-normalized and rotated objects and include a study on classification accuracy as a function of number of rotations in the training set.

Keywords

3D Object Classification 3D Object Signature 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Indriyati Atmosukarto
    • 1
  • Linda G. Shapiro
    • 1
  1. 1.Department of Computer Science and Engineering,SeattleUniversity of WashingtonUSA

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