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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Context-Aided Tracking With Adaptive Hyperspectral Imagery

Context-Aided Tracking With Adaptive Hyperspectral Imagery

Rice, Andrew C.
Air Force Institute of Technology

Paperback

Technology & EngineeringGeneral Education

ISBN10: 1249415675
ISBN13: 9781249415671
Publisher: Biblioscholar
Published: Sep 17 2012
Pages: 158
Weight: 0.51
Height: 0.34 Width: 6.14 Depth: 9.21
Language: English

A methodology for the context-aided tracking of ground vehicles in remote airborne imagery is developed in which a background model is inferred from hyperspectral imagery. The materials comprising the background of a scene are remotely identified and lead to this model. Two model formation processes are developed: a manual method, and method that exploits an emerging adaptive, multiple-object-spectrometer instrument. A semi-automated background modeling approach is shown to arrive at a reasonable background model with minimal operator intervention. A novel, adaptive, and autonomous approach uses a new type of adaptive hyperspectral sensor, and converges to a 66% correct background model in 5% the time of the baseline { a 95% reduction in sensor acquisition time. A multiple-hypothesis-tracker is incorporated, which utilizes background statistics to form track costs and associated track maintenance thresholds. The context-aided system is demonstrated in a high-fidelity tracking testbed, and reduces track identity error by 30%.

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