Title:
Knowledge-Based Segmentation for Tracking Through Deep Turbulence
Knowledge-Based Segmentation for Tracking Through Deep Turbulence
Author(s)
Vela, Patricio A.
Niethammer, Marc
Pryor, Gallagher D.
Tannenbaum, Allen R.
Butts, Robert
Washburn, Donald
Niethammer, Marc
Pryor, Gallagher D.
Tannenbaum, Allen R.
Butts, Robert
Washburn, Donald
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Abstract
A combined knowledge-based segmentation/active contour algorithm is used for target tracking through turbulence. The algorithm utilizes Bayesian modeling for segmentation of noisy imagery obtained through longrange, laser imaging of a distance target, and active contours for tip tracking. The algorithm demonstrates improved target tracking performance when compared to weighted centroiding. Open-loop and closed-loop comparisons of the algorithms using simulated imagery validate the hypothesis. Index Terms—Active contours, Bayesian statistics, geometric flows, tracking, turbulence.
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Date Issued
2008-05
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Text
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Article