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Record W2129539511 · doi:10.1109/tbc.2011.2105630

The Effect of Crosstalk on the Perceived Depth From Disparity and Monocular Occlusions

2011· article· en· W2129539511 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Broadcasting · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsYork University
FundersYork UniversityOntario Centres of ExcellenceMcGill University
KeywordsCrosstalkMonocularStereoscopyPerceptionDepth perceptionComputer scienceComputer visionArtificial intelligenceOpticsPsychologyPhysics

Abstract

fetched live from OpenAlex

Crosstalk in stereoscopic displays is defined as the leakage of one eye's image into the image of the other eye. All popular commercial stereoscopic systems suffer from crosstalk to some extent. Studies show that crosstalk causes distortions, reduces image quality and visual comfort, and increases perceived workload. Moreover, there is evidence that crosstalk effects depth perception from disparity. In the present paper we present two experiments. The first addresses the effect of crosstalk on the perceived magnitude of depth from disparity. The second examines the effect of crosstalk on the magnitude of depth perceived from monocular occlusions. Our data show that crosstalk has a detrimental effect on depth perceived from both cues, but it has a stronger effect on depth from monocular occlusions. Our findings taken together with previous results suggest that crosstalk, even in modest amounts, noticeably degrades the quality of stereoscopic images.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.387

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 head0.020
GPT teacher head0.229
Teacher spread0.209 · 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