Object Categorization from RGB-D Local Features and Bag of Words

  • Jesus Martínez-Gómez
  • Miguel Cazorla
  • Ismael García-Varea
  • Cristina Romero-González
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 418)

Abstract

Object categorization from robot perceptions has become one of the most well-known problems in robotics. How to select proper representations for these perceptions, specially when using RGB-D images, has received a significant attention in the last years. We present in this paper an object categorization approach from RGB-D images. This approach is based on the BoW representation, and it allows to integrate any type of 3D local feature implemented in the Point Cloud Library. The experimentation performed over the challenging RGB-D Object dataset shows how competitive object categorization systems can be developed using this procedure.

Keywords

Object categorization 3D features Classification Robotics 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jesus Martínez-Gómez
    • 1
    • 2
  • Miguel Cazorla
    • 2
  • Ismael García-Varea
    • 1
  • Cristina Romero-González
    • 1
  1. 1.Computer System DepartmentUniversity of Castilla-La ManchasCiudad RealSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of AlicanteAlicanteSpain

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