부산대학교 도서관

Fast and robust gaze estimation is a key technology for wearable glasses, as it enables novel methods of user interaction as well as display enhancement applications, such as foveated rendering. State-of-the-art video-based systems lack a high update rate, integrateability, slippage robustness, and low power consumption. To overcome these limitations, we propose a model-based fusion algorithm to estimate gaze from multiple static laser feedback interferometry (LFI) sensors, which are capable of measuring distance toward the eye and the eye’s rotational velocity. The proposed system is ambient light robust and robust to glasses slippage. During evaluation, a gaze accuracy of 1.79° at an outstanding update rate of 1 kHz is achieved, while the sensors consume only a fraction of the power compared with the state-of-the-art video-based system.