Date of Award

12-1991

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Steven K. Rogers, PhD

Abstract

This research addressed the problem of pose estimation of three- dimensional objects given their two-dimensional IR imagery and corresponding synthetic (computer-generated) IR imagery. Features and techniques were investigated to find those which may be extendable from computer models to real- world IR imagery. GTSIG and SCNGEN were used to create the synthetic imagery. Silhouette and outline shape moments were explored as optimum features for the comparison. Employing back-propagation with momentum as the training paradigm, a two-hidden-layer neural network was able to determine the base-plane orientation of the synthetic imagery to within 7.5 degrees with better than 90% accuracy. (No conclusive results were obtained from comparison with real-world IR imagery. ) Additionally, the use of object hot spots relative to object height-to-width ratio is briefly discussed as an alternative feature/technique.

AFIT Designator

AFIT-ENG-GEO-91D-06

DTIC Accession Number

ADA243699

Comments

The author's Vita page is omitted.

Download

Share

COinS