Paper
11 May 2007 Role of quality of service metrics in visual target acquisition and tracking in resource constrained environments
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Monica Anderson and Phillip David "Role of quality of service metrics in visual target acquisition and tracking in resource constrained environments", Proc. SPIE 6562, Unattended Ground, Sea, and Air Sensor Technologies and Applications IX, 65620N (11 May 2007); https://doi.org/10.1117/12.717835
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Cameras

Target detection

Detection and tracking algorithms

Target acquisition

Imaging systems

Sensors

Surveillance

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