Non-Contact Eye Gaze Tracking System by Mapping of Corneal Reflections
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Analysis of subject-dependent point-of-gaze estimation bias in the cross-ratios method
Proceedings of the 2008 symposium on Eye tracking research & applications
A novel non-intrusive eye gaze estimation using cross-ratio under large head motion
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Display-camera calibration using eye reflections and geometry constraints
Computer Vision and Image Understanding
Augmenting the robustness of cross-ratio gaze tracking methods to head movement
Proceedings of the Symposium on Eye Tracking Research and Applications
The effect of clicking by smiling on the accuracy of head-mounted gaze tracking
Proceedings of the Symposium on Eye Tracking Research and Applications
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Traditional cross-ratio methods (TCR) project a light pattern and use invariant properties of projective geometry to estimate the gaze position. Advantages of the TCR methods include robustness to large head movements and in general requires just a one time per user calibration. However, the accuracy of TCR methods decay significantly for head movements along the camera optical axis, mainly due to the angular difference between the optical and visual axis of the eye. In this paper we propose a depth compensation cross-ratio (DCR) method that improves the accuracy of TCR methods for large head depth variations. Our solution compensates the angular offset using a 2D onscreen vector computed from a simple calibration procedure. The length of the 2D vector, which varies with head distance, is adjusted by a scale factor that is estimated from relative size variations of the corneal reflection pattern. The proposed DCR solution was compared to a TCR method using synthetic and real data from 2 users. An average improvement of 40% was observed with synthetic data, and 8% with the real data.