SOURCE-LINKED INTELLIGENCE
Drift Calibration in Geometric Eye Tracking Systems
Geometric eye trackers can provide the spatial accuracy required for gaze-based interaction and multimodal studies, but their measurements remain sensitive to residual session-specific calibration error. Research on correcting this error is difficult to compare because methods are typically evaluated with different devices, target layouts, and error definitions. We present a calibration-focused dataset containing 163 trials from 12 participants, with separate 18-point fitting and 32-point test grids, and use it to evaluate global, local, and composite correction functions under a common spatia
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- arXiv · AI, language, vision and robotics · 2026-08-30T12:05:44.000Z
First collected: 2026-09-21T07:31:56.984Z. This is not the publication date.