STARE: Realtime, Wearable, Simultaneous Gaze Tracking and Object Recognition from Eye Images

We propose STARE, a wearable system to perform realtime, simultaneous eye tracking and focused object recognition for daily-life applications in varied illumination environments. Our proposed method uses a single camera sensor to evaluate the gaze direction and requires neither a front-facing camera nor infrared sensors. To achieve this, we describe: 1) a model-based approach to estimate the gaze direction using red-green-blue (RGB) eye images; 2) a method to recognize objects in the scene reflected on the cornea in real time; and 3) a 3D-printable prototype of a wearable gaze-tracking device. We verify the validity of our approach experimentally with different types of cameras in different illumination settings, and with a proof-of-concept implementation of a state-of-the-art neural network. The proposed system can be used as a framework for RGB-based eye tracking and human behavior analysis.