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Record W2069631400 · doi:10.1145/1344471.1344531

Remote point-of-gaze estimation requiring a single-point calibration for applications with infants

2008· article· en· W2069631400 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGazeComputer scienceComputer visionArtificial intelligenceCalibrationPupilPoint (geometry)RangingEye trackingMathematicsOpticsStatisticsPhysics

Abstract

fetched live from OpenAlex

This paper describes a method for remote, non-contact point-of-gaze estimation that tolerates free head movements and requires a simple calibration procedure in which the subject has to fixate only on a single point. This method uses the centers of the pupil and at least two corneal reflections that are estimated from eye images captured by at least two cameras. Experimental results obtained with three adult subjects exhibited RMS point-of-gaze estimation errors ranging from 7 to 12 mm (equivalent to about 0.6 -- 1° of visual angle) for head movements in a volume of about 1 dm3. Preliminary results with two infants demonstrated the ability of a system that requires a single-point calibration procedure to estimate infants' point-of-gaze. The ability to record infants' visual scanning behavior can be used for the study of visual development, the determination of attention allocation and the assessment of visual function in preverbal infants.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.256
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations59
Published2008
Admission routes1
Has abstractyes

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