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Object Detection Using a Combination of Multiple 3D Feature Descriptors

  • Lilita Kiforenko
  • Anders Glent Buch
  • Norbert Krüger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9163)

Abstract

This paper presents an approach for object pose estimation using a combination of multiple feature descriptors. We propose to use a combination of three feature descriptors, capturing both surface and edge information. Those descriptors individually perform well for different object classes. We use scenes from an established RGB-D dataset and our own recorded scenes to justify the claim that by combining multiple features, we in general achieve better performance. We present quantitative results for descriptor matching and object detection for both datasets.

Keywords

Object detection Pose estimation Feature combination 

Notes

Acknowledgments

The research leading to these results has received funding from the European Communitys Seventh Framework Programme FP7/2007-2013 (Programme and Theme: ICT-2011.2.1, Cognitive Systems and Robotics) under grant agreement no. 600578, ACAT and by Danish Agency for Science, Technology and Innovation, project CARMEN.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lilita Kiforenko
    • 1
  • Anders Glent Buch
    • 1
  • Norbert Krüger
    • 1
  1. 1.The Mærsk Mc-Kinney Møller InstituteUniversity of Southern DenmarkOdenseDenmark

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