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Proceedings Paper

Feature-aided tracking with hyperspectral imagery
Author(s): Joshua Blackburn; Michael Mendenhall; Andrew Rice; Paul Shelnutt; Neil Soliman; Juan Vasquez
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Paper Abstract

Target tracking in an urban environment presents a wealth of ambiguous tracking scenarios that cause a kinematic-only tracker to fail. Partial or full occlusions in areas of tall buildings are particularly problematic as there is often no way to correctly identify the target with only kinematic information. Feature aided tracking attempts to resolve problems with a kinematic-only tracker by extracting features from the data. In the case of panchromatic video, the features are often histograms, the same is true for color video data. In the case where tracks are uniquely different colors, more typical feature aided trackers may perform well. However, a typical urban setting has similar size, shape, and color tracks, and more typical feature aided trackers have no hopes in resolving many of the ambiguities we face. We present a novel feature aided tracking algorithm combining two-sensor modes: panchromatic video data and hyperspectral imagery. The hyperspectral data is used to provide a unique fingerprint for each target of interest where that fingerprint is the set of features used in our feature aided tracker. Results indicate an impressive 19% gain in correct track ID with our hyperspectral feature aided tracker compared to the baseline performance with a kinematic-only tracker.

Paper Details

Date Published: 25 September 2007
PDF: 12 pages
Proc. SPIE 6699, Signal and Data Processing of Small Targets 2007, 66990S (25 September 2007); doi: 10.1117/12.734937
Show Author Affiliations
Joshua Blackburn, Air Force Institute of Technology (United States)
Michael Mendenhall, Air Force Institute of Technology (United States)
Andrew Rice, Air Force Institute of Technology (United States)
Paul Shelnutt, Air Force Institute of Technology (United States)
Neil Soliman, Air Force Institute of Technology (United States)
Juan Vasquez, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6699:
Signal and Data Processing of Small Targets 2007
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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