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Proceedings Paper

Wide-area surveillance with multiple cameras using distributed compressive imaging
Author(s): Christopher Huff; Robert Muise
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Paper Abstract

In order to image a large area with a required resolution, a traditional camera would have to scan a smaller field-of-view until the entire area of interest is covered, thus losing persistence. Using a large sensor would result in high bandwidth data streams along with expensive and heavy equipment. Ideally, one would like to sense (or measure) a large number of pixels with a very limited set of measurements. In such a scenario the theory of compressive sensing may be put to use. A single sensor compressive imager for the wide area surveillance problem has been postulated and shown to be effective in detecting moving targets in a wide area. In this paper we look at the compressive imaging problem by assuming we have multiple cameras at our disposal. We show that we can get significant benefit in image reconstruction from multiple cameras measuring overlapped fields-of-view without any intra-camera communications and under significant transmission bandwidth constraints. We also show analysis and experiments which suggest that we can register these multiple cameras given only the random projective measurements from each camera.

Paper Details

Date Published: 26 April 2011
PDF: 9 pages
Proc. SPIE 8055, Optical Pattern Recognition XXII, 80550D (26 April 2011); doi: 10.1117/12.890758
Show Author Affiliations
Christopher Huff, Univ. of Central Florida (United States)
Robert Muise, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 8055:
Optical Pattern Recognition XXII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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