GATOR: an automatic multiple-target tracking system

Sharon X. Wang; Gary Chen; Travis Knight

doi:10.1117/12.317513

30 July 1998 GATOR: an automatic multiple-target tracking system

Sharon X. Wang, Gary Chen, Travis Knight

Proceedings Volume 3365, Acquisition, Tracking, and Pointing XII; (1998) https://doi.org/10.1117/12.317513
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

Tracking multiple targets in a cluttered environment using Electro-Optical (EO) and IR imagery is important to airborne video surveillance (AVS). However, existing system often fail when a target encounters occlusion, changes in direction, or stops in transit. To counter this problem, a new software package named GATOR has been developed, which can automatically initiate, maintain, terminate, and reacquire tracking of multiple targets under these challenging conditions. The tracking performance of the system is measured by the discriminative signal to noise ratio and the peak sharpness. The system is implemented in C/C⁺⁺. Using caches for memory addressing the pipeline programing, high speed processing and dynamic target handling are achieved simultaneously. Compared with other multiple target tracking systems, the distinguishing feature of GATOR is that it integrates a suite of tightly structured advanced computer vision algorithms to achieve very rugged performance and fast processing speed. The strength of the system resides in its ruggedness and automation, which is fundamental to many demanding applications such as video image exploitation for UAV, border control, treaty enforcement, and other large area surveillance systems.

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Sharon X. Wang, Gary Chen, and Travis Knight "GATOR: an automatic multiple-target tracking system", Proc. SPIE 3365, Acquisition, Tracking, and Pointing XII, (30 July 1998); https://doi.org/10.1117/12.317513

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KEYWORDS

Target detection

Detection and tracking algorithms

Video

Automatic tracking

Wavelets

Neural networks

Algorithm development

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