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Proceedings Paper

Role of quality of service metrics in visual target acquisition and tracking in resource-constrained environments
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Paper Abstract

Implementation of an intelligent, automated target acquisition and tracking systems alleviates the need for operators to monitor video continuously. This system could identify situations that fatigued operators could easily miss. If an automated acquisition and tracking system plans motions to maximize a coverage metric, how does the performance of that system change when the user intervenes and manually moves the camera? How can the operator give input to the system about what is important and understand how that relates to the overall task balance between surveillance and coverage? In this paper, we address these issues by introducing a new formulation of the average linear uncovered length (ALUL) metric, specially designed for use in surveilling urban environments. This metric coordinates the often competing goals of acquiring new targets and tracking existing targets. In addition, it provides current system performance feedback to system users in terms of the system's theoretical maximum and minimum performance. We show the successful integration of the algorithm via simulation.

Paper Details

Date Published: 11 May 2007
PDF: 10 pages
Proc. SPIE 6562, Unattended Ground, Sea, and Air Sensor Technologies and Applications IX, 65620N (11 May 2007); doi: 10.1117/12.717835
Show Author Affiliations
Monica Anderson, The Univ. of Alabama (United States)
Phillip David, Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 6562:
Unattended Ground, Sea, and Air Sensor Technologies and Applications IX
Edward M. Carapezza, Editor(s)

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