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Proceedings Paper

Target recognition based on a computational vision model
Author(s): Theodore J. Doll; Katharine L. Schlag; Shane W. McWhorter; David E. Schmieder
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Paper Abstract

A simulation of human pattern recognition is outlined which classifies objects based on outputs of a computational vision model, called the Georgia Tech Vision (GTV) model. It is shown that the simulation is able to identify high- level features of military targets, and that identification of high-level features can be used as a tool for recognizing targets. The results suggest that the computational vision model will simplify the task of simulating target recognition by providing a 'front-end' that simulates the basic features that human observes use to recognize targets.

Paper Details

Date Published: 17 June 1996
PDF: 7 pages
Proc. SPIE 2742, Targets and Backgrounds: Characterization and Representation II, (17 June 1996); doi: 10.1117/12.243026
Show Author Affiliations
Theodore J. Doll, Georgia Institute of Technology (United States)
Katharine L. Schlag, Georgia Institute of Technology (United States)
Shane W. McWhorter, Georgia Institute of Technology (United States)
David E. Schmieder, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 2742:
Targets and Backgrounds: Characterization and Representation II
Wendell R. Watkins; Dieter Clement, Editor(s)

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