Jet-Based local image descriptors

  • Authors:
  • Anders Boesen Lindbo Larsen;Sune Darkner;Anders Lindbjerg Dahl;Kim Steenstrup Pedersen

  • Affiliations:
  • Department of Computer Science, University of Copenhagen, Denmark;Department of Computer Science, University of Copenhagen, Denmark;Department of Informatics and Mathematical Modelling, Technical University of Denmark, Denmark;Department of Computer Science, University of Copenhagen, Denmark

  • Venue:
  • ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
  • Year:
  • 2012

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Abstract

We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on the recently released DTU Robot dataset. We demonstrate how the use of higher-order image structures enables us to reduce the descriptor dimensionality while still achieving very good performance. The descriptors are tested in a variety of scenarios including large changes in scale, viewing angle and lighting. We show that the proposed jet-based descriptor is superior to state-of-the-art for DoG interest points and show competitive performance for the other tested interest points.