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Proceedings Paper

Feature-aided multiple target tracking in the image plane
Author(s): Andrew P. Brown; Kevin J. Sullivan; David J. Miller
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Paper Abstract

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Paper Details

Date Published: 9 May 2006
PDF: 12 pages
Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 62290Q (9 May 2006); doi: 10.1117/12.666143
Show Author Affiliations
Andrew P. Brown, Toyon Research Corp. (United States)
Kevin J. Sullivan, Toyon Research Corp. (United States)
David J. Miller, Pennsylvania State Univ. (United States)


Published in SPIE Proceedings Vol. 6229:
Intelligent Computing: Theory and Applications IV
Kevin L. Priddy; Emre Ertin, Editor(s)

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