The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

Research Paper #647

Title:Non-Wildcard Matching Beats the Interpretation Tree
Date: 1992
Presented:In the Proceedings 1992 British Machine Vision Conference, Leeds.
Abstract:Probably the best known control algorithm for high-level model matching in computer vision is the Interpretation Tree expansion algorithm, popularized and extended by Grimson and Lozano-Perez. This algorithm has been shown to have a high computational complexity, particularly when being applied to matching problems with large numbers of features. This paper introduces a non-wildcard variation on this algorithm that has an improvement of about 4-10 in performance over the standard Interpretation Tree algorithm.

[Search These Pages] [DAI Home Page] [Comment]