Overall biometric system performance depends on data quality, the strength of the biometric matching algorithms, the compatibility of data quality with matching algorithms, and quality of the overall integrated system. For long-range face image acquisition and processing for tactical biometrics, there are many issues to consider for these dependencies, both obvious and subtle. Our team has spent the previous decade working on this exact problem and brings to this effort the best research and technology available for tactical biometrics. Securics, Inc. is the industry leader in long-range facial biometrics. For this effort, we have partnered with Animetrics Inc., the leading developer of next-generation 2D-to-3D face recognition and face creation solutions and the CGI Group, Inc., an enterprise level technology solutions provider with operational expertise in biometric deployments. The proposed Phase II effort will focus on improved approaches for motion deblurring, the development of multi-algorithm fusion and temporal fusion approaches, a refined 2D-3D matching process all culminating in the construction of a field ready prototype, called the Automatic Low Light Observer (ALLO), incorporating each component developed in this project. With our transition partners, we will provide the marketplace with the most accurate 2D-to-3D matching system available in any domain.
Keywords: Tactical Biometrics, Standoff Biometrics, Long-Range Identification, Fusion, Deblurring, Metarecognition
