Facial recognition: An enabling technology for augmented cognition applications

Abstract

Research in Augmented Cognition (AugCog) investigates computational methods, technologies, and non-invasive neurophysiological tools to adapt computational systems to the changing cognitive state of human operators to improve task performance. Closed-loop AugCog systems contain four components: 1) operational or simulated environment, 2) automated sensors to monitor and assess cognitive state via behavior and/or physiology, 3) adaptive interface, and 4) computational decision architecture that directs AugCog adaptations. Since cognitive state is influenced by environment, a critical challenge for AugCog systems is capture of situational awareness (SA) within the decision architecture. Previously, AugCog systems have been demonstrated within simulated environments that provide SA and ground truth data to drive intelligent decision architecture. In live operating environments, electronic C4 systems (i.e., communications), provide a limited model of operator "state," but emerging facial recognition/analysis technology can provide detection, identification, and tracking of humans in the environment to increase the accuracy of the AugCog system's SA. © 2011 Springer-Verlag.