Enhancing Smartphone Eye Tracking with Cursor-Based Interactive Implicit Calibration

The limited accuracy of eye-tracking on smartphones restricts its use. Existing RGB-camera-based eye-tracking relies on extensive datasets, which could be enhanced by continuous fine-tuning using calibration data implicitly collected from the interaction. In this context, we propose COMETIC (Cursor Operation Mediated Eye-Tracking Implicit Calibration), which introduces a cursor-based interaction and utilizes the inherent correlation between cursor and eye movement. By filtering valid cursor coordinates as proxies for the ground truth of gaze and fine-tuning the eye-tracking model with corresponding images, COMETIC enhances accuracy during the interaction. Both filtering and fine-tuning use pre-trained models and could be facilitated using personalized, dynamically updated data. Results show COMETIC achieves an average eye-tracking error of 278.3 px (1.60 cm, 2.29°), representing a 27.2% improvement compared to that without fine-tuning. We found that filtering cursor points whose actual distance to gaze is 150.0 px (0.86 cm) yields the best eye-tracking results.