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Proceedings Paper

Object tracking in an omni-directional mosaic
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Paper Abstract

Large gains have been made in the automation of moving object detection and tracking. As these technologies continue to mature, the size of the field of regard and the range of tracked objects continue to increase. The use of a pan-tilt-zoom (PTZ) camera enables a surveillance system to observe a nearly 360° field of regard and track objects over a wide range of distances. However, use of a PTZ camera also presents a number of challenges. The first challenge is to determine how to optimally control the pan, tilt, and zoom parameters of the camera. The second challenge is to detect moving objects in imagery whose orientation and spatial resolution may vary on a frame-by-frame basis. This paper does not address the first issue, it is assumed that the camera parameters are controlled by either an operator or by an automated control process. We address only the problem of how to detect moving objects in imagery whose orientation and spatial resolution may vary on a frame-by-frame basis. We describe a system for detection and tracking of moving objects using a PTZ camera whose parameters are not under our control. A previously published background subtraction algorithm is extended to handle arbitrary camera rotation and zoom changes. This is accomplished by dynamically learning 360°, multi-resolution, background models of the scene. The background models are represented as mosaics on 3D cubes. Tracking of local scale-invariant distinctive image features allows the determination of the camera parameters and the mapping from the current image to the mosaic cube. We describe the real-time implementation of the system and evaluate its performance on a variety of PTZ camera data.

Paper Details

Date Published: 3 September 2008
PDF: 10 pages
Proc. SPIE 7074, Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII, 707406 (3 September 2008); doi: 10.1117/12.795126
Show Author Affiliations
David Baran, Army Research Lab. (United States)
Philip David, Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 7074:
Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII
Franklin T. Luk, Editor(s)

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