Embedded system for human augmented cognition based on face selective attention using eye gaze tracking

Abstract

This paper proposes a new embedded system which can selectively detect human face based on eye gaze information and can also incrementally recognize the human subject. The proposed embedded system comprises of one glass-type platform, two embedded modules and one android platform. The glass-type platform can detect user's eye gaze through eye camera, human faces through frontal camera and selects the face of the preferred human subject based on their gaze information. Android platform performs face recognition and information displaying operation. All modules in the system are connected and communicate wirelessly. The experimental results indicate that the proposed system is reasonable. © Springer-Verlag 2013.