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24 May 2012Performance modeling of a feature-aided tracker
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.
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G. Steven Goley, Adam R. Nolan, "Performance modeling of a feature-aided tracker," Proc. SPIE 8389, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III, 83891A (24 May 2012);