The project will be building on 8 years of DARPA/ONR/Army funded "university research" in automated visual surveillance, which has a proven track record of both close interaction with military end-users and commercialization. That work as well as Guardian Solutions'''''''' existing analysis of the needs of force protection has identified 7 key areas of research/development needed to enhance automated nocturnal surveillance: improved sensor to sensor handoffs, appearance-based type classification and nuisance rejection to reduce the number of nuisance alarms, automated camera control (including zoom), nocturnal data sets for evaluations, long-term "lighting" models, video verification of alarms including cross-sensor fusion, and systems architecture/integration and interoperability issues. Included in the improved approach to sensor handoff will be the computation of sensor-based features for increasing consistency of handoffs, and hence has a huge range of algorithms to explore. In phase I we will focus on quasi-static features, but will be designing the architecture to support dynamic features including gait analysis. By building on the substantial base of the Guardian Solutins'existing commercial GuardianWATCH system, which supports advanced video detection/tracking in low-light and thermal imagery, geo-spatial reasoning and display of tracking data and a distributed architecture, it is expected that the phase I feasibility study will develop fully functional rapid protypes for what we see as the 3 or 4 most significant of these areas
