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Proceedings Paper

Development of an infrared imaging classifier for UGS
Author(s): Bob D'Agostino; Mike McCormack; Bob Steadman
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Paper Abstract

We show design and performance results for an Unattended Ground Sensors (UGS) Automatic Target Recognition (ATR) target classifier using infrared (IR) imagery. Our goal was to develop a basic ATR capability to separate human vs. animal vs. vehicle vs. non-target. Our current UGS video capability accurately detects tracks and transmits targetcentered long wave infrared and visible imagery to a base station. We demonstrate an ATR capability to classify and transmit only targets of interest to the user while excluding others. We describe the ATR development process which includes data collection, building a truthed dataset, feature development, classifier training and performance evaluation.

Paper Details

Date Published: 7 May 2010
PDF: 11 pages
Proc. SPIE 7693, Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 76930K (7 May 2010); doi: 10.1117/12.851808
Show Author Affiliations
Bob D'Agostino, Textron Defense Systems (United States)
Mike McCormack, Textron Defense Systems (United States)
Bob Steadman, Textron Defense Systems (United States)

Published in SPIE Proceedings Vol. 7693:
Unattended Ground, Sea, and Air Sensor Technologies and Applications XII
Edward M. Carapezza, Editor(s)

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