Optimising virtual object position for efficient eye-gaze interaction in Hololens2
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our study explored eye-tracking technology in the Hololens2 HMD. We assessed the effectiveness of eye-gaze interactions in a 3D environment, particularly in text entry applications. Existing recommendations for the placement and size of virtual objects are often followed without empirical validation. Therefore, we evaluated text entry target selection rates within the manufacturer’s specified optimal gaze interaction zone. We measured the spatial accuracy and precision of eye gaze data and optimised target positions for enhanced text entry performance. By establishing confidence ellipses covering 95% of gaze points per target, we derived an Area of Interest (AOI) recalibration function. Applying a receiver operating characteristic-based method, we quantified the recalibrated tracker’s performance at various AOIs. Our results indicate an optimal recalibrated AOI radius is 0.036 m, and the ideal object-plane distance from the eye-plane is 2.25 m. This recalibrated specification allows to efficiently interact with Hololens2 via eye movement, achieving target selection rates exceeding 90%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it