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7 May 2010 Development of an infrared imaging classifier for UGS
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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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bob D'Agostino, Mike McCormack, and Bob Steadman "Development of an infrared imaging classifier for UGS", Proc. SPIE 7693, Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 76930K (7 May 2010); https://doi.org/10.1117/12.851808
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