Analysis on a Local Approach to 3D Object Recognition

  • Elisabetta Delponte
  • Elise Arnaud
  • Francesca Odone
  • Alessandro Verri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


We present a method for 3D object modeling and recognition which is robust to scale and illumination changes, and to viewpoint variations. The object model is derived from the local features extracted and tracked on an image sequence of the object. The recognition phase is based on an SVM classifier. We analyse in depth all the crucial steps of the method, and report very promising results on a dataset of 11 objects, that show how the method is also tolerant to occlusions and moderate scene clutter.


Object Recognition Local Approach Unscented Kalman Filter Sift Descriptor Main Orientation 
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

  • Elisabetta Delponte
    • 1
  • Elise Arnaud
    • 1
  • Francesca Odone
    • 1
  • Alessandro Verri
    • 1
  1. 1.DISI – Università degli Studi di GenovaItaly

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