Paper
1 September 2009 Ultra-scale vehicle tracking in low spatial resolution and low frame-rate overhead video
Author Affiliations +
Abstract
Overhead persistent surveillance systems are becoming more capable at acquiring wide-field image sequences for long time-spans. The need to exploit this data is becoming ever greater. The ability to track a single vehicle of interest or to track all the observable vehicles, which may number in the thousands, over large, cluttered regions while they persist in the imagery either in real-time or quickly on-demand is very desirable. With this ability we can begin to answer a number of interesting questions such as, what are normal traffic patterns in a particular region or where did that truck come from? There are many challenges associated with processing this type of data, some of which we will address in the paper. Wide-field image sequences are very large with many thousands of pixels on a side and are characterized by lower resolutions (e.g. worse than 0.5 meters/pixel) and lower frame rates (e.g. a few Hz or less). The objects in the scenery can vary in size, density, and contrast with respect to the background. At the same time the background scenery provides a number of clutter sources both man-made and natural. We describe our current implementation of an ultrascale capable multiple-vehicle tracking algorithm for overhead persistent surveillance imagery as well as discuss the tracking and timing performance of the currently implemented algorithm which is aimed at utilizing grayscale electrooptical image sequences alone for the track segment generation.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Carmen J. Carrano "Ultra-scale vehicle tracking in low spatial resolution and low frame-rate overhead video", Proc. SPIE 7445, Signal and Data Processing of Small Targets 2009, 744504 (1 September 2009); https://doi.org/10.1117/12.825187
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Cited by 9 scholarly publications.
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KEYWORDS
Image segmentation

Detection and tracking algorithms

Buildings

Cameras

Video

Image processing algorithms and systems

Automatic tracking

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