International Journal of Computer Vision

, Volume 98, Issue 2, pp 217–241 | Cite as

Scale Invariant Feature Transform on the Sphere: Theory and Applications

  • Javier Cruz-Mota
  • Iva Bogdanova
  • Benoît Paquier
  • Michel Bierlaire
  • Jean-Philippe Thiran
Article

Abstract

A SIFT algorithm in spherical coordinates for omnidirectional images is proposed. This algorithm can generate two types of local descriptors, Local Spherical Descriptors and Local Planar Descriptors. With the first ones, point matching between two omnidirectional images can be performed, and with the second ones, the same matching process can be done but between omnidirectional and planar images. Furthermore, a planar to spherical mapping is introduced and an algorithm for its estimation is given. This mapping allows to extract objects from an omnidirectional image given their SIFT descriptors in a planar image. Several experiments, confirming the promising and accurate performance of the system, are conducted.

Keywords

Omnidirectional vision (Spherical) image processing Feature extraction Object detection SIFT Matching 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Javier Cruz-Mota
    • 1
  • Iva Bogdanova
    • 2
    • 3
  • Benoît Paquier
    • 4
  • Michel Bierlaire
    • 1
  • Jean-Philippe Thiran
    • 4
  1. 1.Transport and Mobility Laboratory (TRANSP-OR)École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
  2. 2.Pattern Recognition Laboratory (PARLAB)École Polytechnique Fédérale de Lausanne (EPFL)NeuchâtelSwitzerland
  3. 3.Embedded Systems Lab (ESL)École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
  4. 4.Signal Processing Laboratory 5École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland

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