Biometrically Inferred Observations for Determining Access and Tracking (BIODAT)

Robust facial recognition technologies that can rapidly provide access to restricted areas are needed. Currently, to reduce traffic delays at base access points, a single occupant’s Common Access Card (CAC) is used to permit every passenger’s access to the facility. Visible and thermal wavelength cameras are present at perimeter access points; however, they are mostly used in a forensic nature. An intelligent camera system, as proposed here, can transform a passive camera to an automated 24-hour authentication system. By automating routine entries at busy access points, Guards can focus their attention on the greater security needs of the base environment. Lynntech and our collaborators at The University of Notre Dame propose the development of the Biometrically Inferred Observations for Determining Access and Tracking (BIODAT) camera system. BIODAT will use advanced polarimetry and computer vision algorithms to capture vehicle occupants’ facial features for authentication from inside their vehicles, despite windshield glare, while traveling at speeds of five to ten miles per hour. Guards will no longer have to handle CAC cards, and BIODAT can be used to authenticate passengers. BIODAT, once delivered, will monitor camera feeds 24 hours a day, identifying multiple individuals simultaneously, while flagging unauthorized or unrecognized persons for additional processing. BIODAT’s modular design permits integration with existing systems, such as the Homeland Advanced Recognition Technology’s AWS GovCloud identification database.