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Conference Paper

3D Gaze Estimation using Eye Vergence

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Citation

Gutierrez Mlot, E., Bahmani, H., Wahl, S., & Kasneci, E. (2016). 3D Gaze Estimation using Eye Vergence. In J. Gilbert, A. Azhari, & H. Ali (Eds.), BIOSTEC 2016: Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (pp. 125-131). Setúbal, Portugal: Scitepress.


Cite as: https://hdl.handle.net/21.11116/0000-0006-FFB1-3
Abstract
We propose a fast and robust method to estimate the 3D gaze position based on the eye vergence information extracted from eye-tracking data. This method is specially designed for Point-of-Regard (PoR) estimation in non-virtual environments with the aim to make it applicable to the study of human visual attention deployment in natural scenarios. Our approach starts with a calibration step at different depth distances in order to achieve the best depth approximation. In addition, we investigate the distance range, for which state-of-the-art eyetracking technology allows 3D gaze estimation based on eye vergence. Our method provides a mean accuracy of 1.2◦ at a working distance between 200 mm and 400 mm from the user without requiring calibrated lights or cameras.