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Record W1968837137 · doi:10.1117/12.474093

Improving the visual comfort of stereoscopic images

2003· article· en· W1968837137 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

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsComputer visionComputer scienceArtificial intelligenceStereoscopyComputer graphics (images)Frame (networking)StereopsisStereo camera

Abstract

fetched live from OpenAlex

We compared the visual comfort and apparent depth of stereoscopic images for three camera configurations: parallel (without image shift), image-shifted and converged. In the parallel and image-shifted configurations, the stereo cameras were pointed straight ahead. In the converged configuration the cameras were toed-in. In the image-shifted configuration the image frame was shifted perpendicularly with respect to the line of sight of the camera. The parallel configuration produces images with uncomfortably large disparities for objects near the camera. By converging the cameras or by shifting the image, these large disparities can be reduced and visual comfort can be improved. However, the converged configuration introduces keystone distortions into the image, which can produce visual discomfort. The image-shifted configuration does not introduce keystone distortions, but affects the width of the image frame. It also requires unusual camera hardware or computer post-processing to shift the images. We found that converged and image-shifted configurations improved the visual comfort of stereoscopic images by an equivalent amount, without affecting the apparent depth. Keystone distortions in the converged configuration had no appreciable negative effect on visual comfort.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.235
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