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3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers

3D gaze information is important for scene-centric attention analysis, but accurate estimation and analysis of 3D gaze in real-world environments remains challenging. We present a novel 3D gaze estimation method for monocular head-mounted eye trackers. In contrast to previous work, our method does not aim to infer 3D eye- ball poses, but directly maps 2D pupil positions to 3D gaze directions in scene camera coordinate space. We first provide a detailed discussion of the 3D gaze estimation task and summarize different methods, including our own. We then evaluate the performance of different 3D gaze estimation approaches using both simulated and real data. Through experimental validation, we demonstrate the effectiveness of our method in reducing parallax error, and we identify research challenges for the design of 3D calibration procedures.

Dataset available here.

Contact: Andreas Bulling,

The software is only to be used for non-commercial scientific purposes. If you use this software in a scientific publication, please cite the following paper:

  1. 3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers

    3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers

    Mohsen Mansouryar, Julian Steil, Yusuke Sugano, Andreas Bulling

    Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), pp. 197-200, 2016.

    Abstract Links BibTeX Project