Background image understanding and adaptive imaging for vehicle tracking
Burak Uzkent, Matthew J. Hoffman, Anthony Vodacek, Bin Chen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
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.