Performance comparison of ten variations on the interpretation-tree matching algorithm

  • Robert B. Fisher
Recognition II
Part of the Lecture Notes in Computer Science book series (LNCS, volume 800)


The best known algorithm for symbolic model matching in computer vision is the Interpretation Tree search algorithm. This algorithm has a high computational complexity when applied to matching problems with large numbers of features. This paper examines ten variations of this algorithm in a search for improved performance, and concludes that the non-wildcard and hierarchical algorithms have reduced theoretical complexity and run faster than the standard algorithm.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Robert B. Fisher
    • 1
  1. 1.Dept. of Artificial IntelligenceUniversity of EdinburghEdinburghScotland, UK

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