Restructuring aspect graphs into aspect- and cell-equivalence classes for use in computer vision

  • John Stewman
  • Louise Stark
  • Kevin Bowyer
Computer Vision
Part of the Lecture Notes in Computer Science book series (LNCS, volume 314)


A potential disadvantage of using aspect graphs as object models in a computer vision system is their large size. The upper bound on the number of nodes in the aspect graph of an N-face convex object is O(N⋆⋆3). In this paper we introduce the concepts of "aspect-equivalence" and "cell-equivalence" and present a method of using them to restructure a data base of aspect graphs. This process identifies an interconnected set of equivalence classes which we use to form an Equivalence Class Graph (ECG).


Object Recognition Object Model Cell Boundary Longe Edge Robot Vision 
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 1988

Authors and Affiliations

  • John Stewman
    • 1
  • Louise Stark
    • 1
  • Kevin Bowyer
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of South FloridaTampaUSA

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