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24 May 2012 Performance modeling of a feature-aided tracker
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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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. Steven Goley and 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);

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