TY  - CONF
AU  - Cristina Palmero
AU  - Oleg V Komogortsev
AU  - Sergio Escalera
AU  - Sachin S Talathi
A2  - ETRA
PY  - 2023//
TI  - Multi-Rate Sensor Fusion for Unconstrained Near-Eye Gaze Estimation
BT  - Proceedings of the 2023 Symposium on Eye Tracking Research and Applications
SP  - 1
EP  - 8
N2  - The power requirements of video-oculography systems can be prohibitive for high-speed operation on portable devices. Recently, low-power alternatives such as photosensors have been evaluated, providing gaze estimates at high frequency with a trade-off in accuracy and robustness. Potentially, an approach combining slow/high-fidelity and fast/low-fidelity sensors should be able to exploit their complementarity to track fast eye motion accurately and robustly. To foster research on this topic, we introduce OpenSFEDS, a near-eye gaze estimation dataset containing approximately 2M synthetic camera-photosensor image pairs sampled at 500 Hz under varied appearance and camera position. We also formulate the task of sensor fusion for gaze estimation, proposing a deep learning framework consisting in appearance-based encoding and temporal eye-state dynamics. We evaluate several single- and multi-rate fusion baselines on OpenSFEDS, achieving 8.7% error decrease when tracking fast eye movements with a multi-rate approach vs. a gaze forecasting approach operating with a low-speed sensor alone.
UR  - https://doi.org/10.1145/3588015.3588407
N1  - HUPBA
ID  - Cristina Palmero2023
ER  -