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Proceedings Paper

Performance modeling of a feature-aided tracker
Author(s): G. Steven Goley; Adam R. Nolan
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Paper Abstract

In order to provide actionable intelligence in a layered sensing paradigm, exploitation algorithms should produce a confidence estimate in addition to the inference variable. This article presents a methodology and results of one such algorithm for feature-aided tracking of vehicles in wide area motion imagery. To perform experiments a synthetic environment was developed, which provided explicit knowledge of ground truth, tracker prediction accuracy, and control of operating conditions. This synthetic environment leveraged physics-based modeling simulations to re-create both traffic flow, reflectance of vehicles, obscuration and shadowing. With the ability to control operating conditions as well as the availability of ground truth, several experiments were conducted to test both the tracker and expected performance. The results show that the performance model produces a meaningful estimate of the tracker performance over the subset of operating conditions.

Paper Details

Date Published: 24 May 2012
PDF: 12 pages
Proc. SPIE 8389, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III, 83891A (24 May 2012); doi: 10.1117/12.920763
Show Author Affiliations
G. Steven Goley, Etegent Technologies, Ltd. (United States)
Adam R. Nolan, Etegent Technologies, Ltd. (United States)


Published in SPIE Proceedings Vol. 8389:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III
Tien Pham, Editor(s)

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