AI & ML
What Mean Error Misses: Device-Clock Diagnostics for Evaluating Eye Tracking across Three Virtual Reality Headsets
arXiv cs.HC0 views
arXiv:2610.32915v1 Announce Type: new Abstract: Gaze research in virtual reality needs eye trackers of known error. Thirty participants completed the same protocol on the Meta Quest Pro (QP), HTC VIVE Pro Eye (PE) and HTC VIVE Focus Vision (FV); to our knowledge, this is the first evaluation of the FV eye tracker. In a random-saccade task, median participant mean error was 1.04{\deg} on QP, 1.50{\deg} on PE and 2.41{\deg} on FV, which remained least accurate after linear recalibration. In a later block with a darker background, PE error rose by 0.70{\deg}. FV samples were positively correlated: dispersion was 9.8 times the sample-to-sample root mean square. The device clocks showed losses that mean error hides. QP paused for up to 6.04 s, and FV skipped single samples. During instructed eye closures, QP flagged every sample valid while gaze moved 9.74{\deg}. Evaluations should report repeated timestamps, loss composition on the device clock and validity during eye closures.
Source:https://arxiv.org/abs/2610.32915PreviousWhen Should I Trust This? Designing and Evaluating Factuality Indicators for LLM-based ChatbotsNextValidating the Comparison, Not Just the Scorer: Why Overall Accuracy Can Mislead in Interactive LLM Evaluation
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