Noncontact Binocular Eye-Gaze Tracking for Point-of-Gaze Estimation in Three Dimensions
Why this work is in the frame
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Bibliographic record
Abstract
Binocular eye-gaze tracking can be used to estimate the point-of-gaze (POG) of a subject in real-world 3-D space using the vergence of the eyes. In this paper, a novel noncontact model-based technique for 3-D POG estimation is presented. The noncontact system allows people to select real-world objects in 3-D physical space using their eyes, without the need for head-mounted equipment. Remote 3-D POG estimation may be especially useful for persons with quadriplegia or Amyotrophic Lateral Sclerosis. It would also enable a user to select 3-D points in space generated by 3-D volumetric displays, with potential applications to medical imaging and telesurgery. Using a model-based POG estimation algorithm allows for free head motion and a single stage of calibration. It is shown that an average accuracy of 3.93 cm was achieved over a workspace volume of 30 x 23 x 25 cm (W x H x D) with a maximum latency of 1.5 s due to the digital filtering employed. The users were free to naturally move and reorient their heads while operating the system, within an allowable headspace of 3 cm x 9 cm x 14 cm.
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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 | 0.000 | 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