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Detecting Symmetry and Symmetric Constellations of Features

  • Gareth Loy
  • Jan-Olof Eklundh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3952)

Abstract

A novel and efficient method is presented for grouping feature points on the basis of their underlying symmetry and characterising the symmetries present in an image. We show how symmetric pairs of features can be efficiently detected, how the symmetry bonding each pair is extracted and evaluated, and how these can be grouped into symmetric constellations that specify the dominant symmetries present in the image. Symmetries over all orientations and radii are considered simultaneously, and the method is able to detect local or global symmetries, locate symmetric figures in complex backgrounds, detect bilateral or rotational symmetry, and detect multiple incidences of symmetry.

Keywords

Feature Point Rotational Symmetry Bilateral Symmetry Symmetric Pair Sift Descriptor 
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 2006

Authors and Affiliations

  • Gareth Loy
    • 1
  • Jan-Olof Eklundh
    • 1
  1. 1.Computational Vision & Active Perception LaboratoryRoyal Institute of Technology (KTH)Sweden

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