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Proceedings Paper

Adaptive Gate Multifeature Bayesian Statistical Tracker
Author(s): W. B. Schaming
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Paper Abstract

A statistically based tracking algorithm is described which utilizes a powerful segmentation algorithm. Multiple features such as intensity, edge magnitude, and spatial frequency are combined to form a joint probability distribution to characterize a region containing a target and its immediate surround. These distributions are integrated over time to provide a stable estimate of the target region and background statistics. A Bayesian decision rule is implemented using these distributions to classify individual pixels as target or nontarget. An adaptive gate process is used to estimate desired changes in the tracking window size.

Paper Details

Date Published: 17 March 1983
PDF: 9 pages
Proc. SPIE 0359, Applications of Digital Image Processing IV, (17 March 1983); doi: 10.1117/12.965948
Show Author Affiliations
W. B. Schaming, RCA Advanced Technology Laboratories (United States)

Published in SPIE Proceedings Vol. 0359:
Applications of Digital Image Processing IV
Andrew G. Tescher, Editor(s)

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