Detecting symmetry and symmetric constellations of features

  • Authors:
  • Gareth Loy;Jan-Olof Eklundh

  • Affiliations:
  • Computational Vision & Active Perception Laboratory, Royal Institute of Technology (KTH), Sweden;Computational Vision & Active Perception Laboratory, Royal Institute of Technology (KTH), Sweden

  • Venue:
  • ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
  • Year:
  • 2006

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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.