
Proceedings Paper
Investigating the validity of the networked imaging sensor modelFormat | Member Price | Non-Member Price |
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Paper Abstract
The Networked Imaging Sensor (NIS) model takes as input target acquisition probability as a function of time for
individuals or individual imaging sensors, and outputs target acquisition probability for a collection of imaging
sensors and individuals. System target acquisition takes place the moment the first sensor or individual acquires
the target. The derivation of the NIS model implies it is applicable to multiple moving sensors and targets. The
principal assumption of the NIS model is independence of events that give rise to input target acquisition
probabilities. For investigating the validity of the NIS model, we consider a collection of single images where
neither the sensor nor target is moving. This paper investigates the ability of the NIS model to predict system
target acquisition performance when multiple observers view first and second Gen thermal imagery, field-of-view
imagery that has either zero or one stationary target in a laboratory environment when observers have a maximum
of 12, 17 or unlimited seconds to acquire the target. Modeled and measured target acquisition performance are
in good agreement.
Paper Details
Date Published: 15 May 2015
PDF: 52 pages
Proc. SPIE 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI, 94520R (15 May 2015); doi: 10.1117/12.2178418
Published in SPIE Proceedings Vol. 9452:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI
Gerald C. Holst; Keith A. Krapels, Editor(s)
PDF: 52 pages
Proc. SPIE 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI, 94520R (15 May 2015); doi: 10.1117/12.2178418
Show Author Affiliations
Melvin Friedman, U.S. Army Night Vision and Electronic Sensors Directorate (United States)
Published in SPIE Proceedings Vol. 9452:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI
Gerald C. Holst; Keith A. Krapels, Editor(s)
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