Corner Detection in Spherical Images via the Accelerated Segment Test on a Geodesic Grid

  • Hao Guan
  • William A. P. Smith
  • Peng Ren
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8033)


We extend the Accelerated Segment Test (AST) corner detector to operate on spherical images. We represent images using a discrete geodesic grid composed of triangular or hexagonal pixels. This representation has a number of advantages over the more common equirectangular parameterisation and, in the case of hexagonal pixels, leads more naturally to the discrete circular discs used in the AST. We present results on fully spherical imagery and show that our spherical AST outperforms planar AST applied to equirectangular images in terms of repeatability under rotation.


Hexagonal Lattice Triangular Lattice Scale Invariant Feature Transform Corner Detection Spherical Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hao Guan
    • 1
  • William A. P. Smith
    • 1
  • Peng Ren
    • 2
  1. 1.Department of Computer ScienceThe University of YorkUK
  2. 2.College of Information and Control EngineeringChina University of Petroluem (Huadong)China

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