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Hypothesis and Verification in 3D Model Matching
Author(s) -
F. P. Sykes,
Stephen Pollard,
J. E. W. Mayhew
Publication year - 1989
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.3.2
Subject(s) - computer science , matching (statistics) , representation (politics) , artificial intelligence , opacity , identification (biology) , quality (philosophy) , data mining , pattern recognition (psychology) , mathematics , statistics , philosophy , physics , botany , optics , epistemology , politics , political science , law , biology
This paper addresses 3-D hypothesis and mixed 3-D and 2-D verification as a means of obtaining high performance closed loop model-matching. Performance includes the following criteria: low computational expence; low failure rate; and good localisation. Hypotheses are based upon congruencies identified between 3-D scene and model descriptions. Verification is provided by quantitative evaluation of the 3-D match and the identification of inconsistency (relient upon properties of opaque objects). Although the results are dependent upon the model representation and the quality of the input (raw images), the ability of a verification system to discriminate between a correct and a wrong match has been demonstrated in a number of experiments. Furthermore, symmetries are identified by the system and exploited to guide the search for correct matches.

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