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Optical Engineering

A Real-Time Video Tracking System
Author(s): A. L. Gilbert; M. K. Giles; G. M. Flachs; R. B. Rogers; Yee Hsun U
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Paper Abstract

Real-time pattern recognition as applied to 2-D imagery has been limited to trivial or near trivial algorithms due to the severe constraints on processing speed and information bandwidth. Object identification and tracking applications of pattern recognition at video rates is a problem of wide interest, with previous attempts limited to very simple threshold or correlation (restricted window) methods. New high-speed algorithms together with fast digital hardware have produced a system for missile and aircraft identification and tracking that possesses an "intelligence" that far exceeds previously implemented real-time tracking capabilities. Adaptive statistical clustering and projection based classification algorithms are applied in real time to identify and track objects that change in appearance through complex and nonstationary background/foreground situations. Fast estimation and prediction algorithms combine linear and quadratic estimators to provide speed and sensitivity. Weights are determined to provide a measure of confidence in the data and resulting decisions. Strategies based on maximizing the probability of maintaining track are developed. This paper emphasizes the theoretical aspects of the system and discusses the techniques used to achieve real-time implementation.

Paper Details

Date Published: 1 February 1979
PDF: 8 pages
Opt. Eng. 18(1) 180125 doi: 10.1117/12.7972315
Published in: Optical Engineering Volume 18, Issue 1
Show Author Affiliations
A. L. Gilbert, U. S. Army White Sands Missile Range (United States)
M. K. Giles, U. S. Army White Sands Missile Range (United States)
G. M. Flachs, New Mexico State University (United States)
R. B. Rogers, New Mexico State University (United States)
Yee Hsun U, New Mexico State University (United States)


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