Year: 2025
Type: conference-paper
Abstract: 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.
Institution: Michigan State University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409885472