3D gaze estimation from 2D pupil positions on monocular head-mounted eye
trackers
Poster abstracts
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Mansourya, Mohsen
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Steil, Julian
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Sugano, Yusuke
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Bulling, Andreas
Proceedings of the 2016 Symposium on Eye Tracking Research &
Applications
2016-03-14
p.197-200
© Copyright 2016 ACM
Summary: 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 eyeball 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.