Eye-Gaze Tracking Based on Head Orientation Estimation Using FMCW Radar Sensor

Abstract

In this article, we propose an eye-gaze tracking method based on head orientation estimation that uses a single 60-GHz frequency-modulated continuous-wave (FMCW) radar sensor. The FMCW radar data are acquired for cases, in which the radar is illuminating the front or side of the face. Because the variation in facial muscles caused by eye blinking is more pronounced when a human gazes at the radar, the orientation of the human head can be estimated by analyzing the received radar signal. First, an approximate range-angle map is generated to identify whether a human exists. When a human is detected, the received signal is projected onto the lower subspace of interest. Subsequently, a super-resolution algorithm is applied to the projected signal to obtain a precise target spectrum. The accumulated spectrogram is used as input to MobileNet to classify radar signal images corresponding to different orientations of the human head. The classification results show that the proposed method can identify the orientation of a human head with an accuracy exceeding 90%.