RadEye: Tracking Eye Motion Using FMCW Radar

Eye motion tracking plays a vital role in many applications such as human-computer interaction (HCI), virtual reality, and disease detection. Camera-based eye tracking, albeit accurate and easy to use, may raise privacy concerns and appear to be unreliable in poor lighting conditions. In this paper, we present RadEye, a radar system capable of detecting fine-grained human eye motions from a distance. RadEye is realized through an integrated hardware and software design. It customizes a sub-6GHz FMCW radar so as to detect millimeter-level eye movement while extending its detection range using low frequency. It further employs a deep neural network (DNN) to refine the detection accuracy through camera-guided supervisory training. We have built a prototype of RadEye. Extensive experimental results show that it achieves 90% accuracy when detecting human eye rotation directions (up, down, left, and right) in various scenarios.

• Human-centered computing → Human computer interaction (HCI); • Hardware → Printed circuit boards.