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Proceedings Paper

Multiple-hypothesis tracking of multiple ground targets from aerial video with dynamic sensor control
Author(s): Pablo O. Arambel; Jeff Silver; Jon Krant; Matthew Antone; Thomas Strat
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Paper Abstract

The goal of the DARPA Video Verification of Identity (VIVID) program is to develop an automated video-based ground targeting system for unmanned aerial vehicles that significantly improves operator combat efficiency and effectiveness while minimizing collateral damage. One of the key components of VIVID is the Multiple Target Tracker (MTT), whose main function is to track many ground targets simultaneously by slewing the video sensor from target to target and zooming in and out as necessary. The MTT comprises three modules: (i) a video processor that performs moving object detection, feature extraction, and site modeling; (ii) a multiple hypothesis tracker that processes extracted video reports (e.g. positions, velocities, features) to generate tracks of currently and previously moving targets and confusers; and (iii) a sensor resource manager that schedules camera pan, tilt, and zoom to support kinematic tracking, multiple target track association, scene context modeling, confirmatory identification, and collateral damage avoidance. When complete, VIVID MTT will enable precision tracking of the maximum number of targets permitted by sensor capabilities and by target behavior. This paper describes many of the challenges faced by the developers of the VIVID MTT component, and the solutions that are currently being implemented.

Paper Details

Date Published: 9 August 2004
PDF: 10 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.541208
Show Author Affiliations
Pablo O. Arambel, ALPHATECH, Inc. (United States)
Jeff Silver, ALPHATECH, Inc. (United States)
Jon Krant, ALPHATECH, Inc. (United States)
Matthew Antone, ALPHATECH, Inc. (United States)
Thomas Strat, DARPA (United States)

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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