A single camera eye-gaze tracking system with free head motion
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Theoretical or conceptualConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: none
- Teacher disagreement score
- 0.820
- Threshold uncertainty score
- 0.451
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.205 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Eye-gaze as a form of human machine interface holds great promise for improving the way we interact with machines. Eyegaze tracking devices that are non-contact, non-restrictive, accurate and easy to use will increase the appeal for including eye-gaze information in future applications. The system we have developed and which we describe in this paper achieves these goals using a single high resolution camera with a fixed field of view. The single camera system has no moving parts which results in rapid reacquisition of the eye after loss of tracking. Free head motion is achieved using multiple glints and 3D modeling techniques. Accuracies of under 1 ° of visual angle are achieved over a field of view of 14x12x20 cm and over various hardware configurations, camera resolutions and frame rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Topic
- Gaze Tracking and Assistive Technology
- Field
- Computer Science
- Canadian institutions
- University of British Columbia
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Keywords
- GazeComputer visionComputer scienceArtificial intelligenceHead (geology)Eye trackingTracking (education)Computer graphics (images)Motion (physics)Tracking systemGeologyPsychology
- Has abstract in OpenAlex
- yes