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Multiscale Shape Description with Laplacian Profile and Fourier Transform

  • Evanthia MavridouEmail author
  • James L. Crowley
  • Augustin Lux
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8814)

Abstract

We propose a new local multiscale image descriptor of variable size. The descriptor combines Laplacian of Gaussian values at different scales with a Radial Fourier Transform. This descriptor provides a compact description of the appearance of a local neighborhood in a manner that is robust to changes in scale and orientation. We evaluate this descriptor by measuring repeatability and recall against 1-precision with the Affine Covariant Features benchmark dataset and as well as with a set of textureless images from the MIRFLICKR Retrieval Evaluation dataset. Experiments reveal performance competitive to the state of the art, while providing a more compact representation.

Keywords

Robust image description Scale invariance Local appearance description Compact descriptor Variable vector length 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Evanthia Mavridou
    • 1
    • 2
    Email author
  • James L. Crowley
    • 1
    • 2
  • Augustin Lux
    • 1
    • 2
  1. 1.University of Grenoble Alpes, LIGGrenobleFrance
  2. 2.Inria Grenoble Rhône-Alpes Research Centre, LIGGrenobleFrance

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