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Evaluating and Comparing of 3D Shape Descriptors for Object Recognition

  • Alexander Ceron
  • Flavio Prieto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8034)

Abstract

In this work we show the results of a system for object recognition by using depth data. It is based on shape descriptors and PCA reduction. For obtaining the results, we evaluated different combination of three descriptors that are suitable for this work: Spin Images, VFH (Viewpoint Feature Histogram) and NARF (Normal Aligned Radial Feature). In addition, we created a method for extracting the NARF descriptor in order to obtain a global descriptor. The results show that the combination of descriptors can be used for object recognition in a database composed of point clouds obtained with a RGB-D sensor.

Keywords

Point Cloud Object Recognition Shape Descriptor Spin Image Global Descriptor 
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 2013

Authors and Affiliations

  • Alexander Ceron
    • 1
    • 2
  • Flavio Prieto
    • 1
  1. 1.Universidad Nacional de ColombiaBogotáColombia
  2. 2.Universidad Militar Nueva GranadaBogotáColombia

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