Foveated imaging has been explored for compression and tele-presence, but gaps exist in the study of foveated imaging
applied to acquisition and tracking systems. Results are presented from two sets of experiments comparing simple
foveated and uniform resolution targeting (acquisition and tracking) algorithms. The first experiments measure
acquisition performance when locating Gabor wavelet targets in noise, with fovea placement driven by a mutual
information measure. The foveated approach is shown to have lower detection delay than a notional uniform resolution
approach when using video that consumes equivalent bandwidth. The second experiments compare the accuracy of
target position estimates from foveated and uniform resolution tracking algorithms. A technique is developed to select
foveation parameters that minimize error in Kalman filter state estimates. Foveated tracking is shown to consistently
outperform uniform resolution tracking on an abstract multiple target task when using video that consumes equivalent
bandwidth. Performance is also compared to uniform resolution processing without bandwidth limitations. In both
experiments, superior performance is achieved at a given bandwidth by foveated processing because limited resources
are allocated intelligently to maximize operational performance. These findings indicate the potential for operational
performance improvements over uniform resolution systems in both acquisition and tracking tasks.
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