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3D gaze information is important for scene-centric attention analysis butaccurate estimation and analysis of 3D gaze in real-world environments remainschallenging. We present a novel 3D gaze estimation method for monocularhead-mounted eye trackers. In contrast to previous work, our method does notaim to infer 3D eyeball poses but directly maps 2D pupil positions to 3D gazedirections in scene camera coordinate space. We first provide a detaileddiscussion of the 3D gaze estimation task and summarize different methods,including our own. We then evaluate the performance of different 3D gazeestimation approaches using both simulated and real data. Through experimentalvalidation, we demonstrate the effectiveness of our method in reducing parallaxerror, and we identify research challenges for the design of 3D calibrationprocedures.

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