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Proceedings Article

Background image understanding and adaptive imaging for vehicle tracking

[+] Author Affiliations
Burak Uzkent, Matthew J. Hoffman, Anthony Vodacek, Bin Chen

Rochester Institute of Technology (United States)

Proc. SPIE 9460, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII, 94600F (May 19, 2015); doi:10.1117/12.2177494
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From Conference Volume 9460

  • Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII
  • Daniel J. Henry; Gregory J. Gosian; Davis A. Lange; Dale Linne von Berg; Thomas J. Walls; Darrell L. Young
  • Baltimore, Maryland, United States | April 20, 2015

abstract

We describe our effort to create an imaging-based vehicle tracking system that uses the principles of dynamic data driven applications systems to observe, model, and collect new within a dynamic feedback loop. Several unique aspects of the system include tracking of user-defined vehicles, the use of an adaptive sensor that can change modality, and a reliance on background image understanding to improve tracking and minimize error. We describe the system and show results demonstrated within the DIRSIG image simulation model that show improved tracking results for the system. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Burak Uzkent ; Matthew J. Hoffman ; Anthony Vodacek and Bin Chen
" Background image understanding and adaptive imaging for vehicle tracking ", Proc. SPIE 9460, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII, 94600F (May 19, 2015); doi:10.1117/12.2177494; http://dx.doi.org/10.1117/12.2177494


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