DocumentCode
1074519
Title
Knowledge-Based Segmentation for Tracking Through Deep Turbulence
Author
Vela, Patricio A. ; Niethammer, Marc ; Pryor, Gallagher D. ; Tannenbaum, Allen R. ; Butts, Robert ; Washburn, Donald
Author_Institution
Georgia Inst. of Technol., Atlanta
Volume
16
Issue
3
fYear
2008
fDate
5/1/2008 12:00:00 AM
Firstpage
469
Lastpage
474
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.
Keywords
Bayes methods; image processing; target tracking; turbulence; Bayesian modeling; active contour algorithm; deep turbulence; kowledge-based segmentation; noisy imagery; simulated imagery; target tracking; tip tracking; Active contours; Bayesian statistics; geometric flows; tracking; turbulence;
fLanguage
English
Journal_Title
Control Systems Technology, IEEE Transactions on
Publisher
ieee
ISSN
1063-6536
Type
jour
DOI
10.1109/TCST.2007.899723
Filename
4454452
Link To Document