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Record W1984922550 · doi:10.1117/12.430835

<title>Performance enhancement of field-sequential stereoscopic video systems</title>

2001· article· en· W1984922550 on OpenAlex
Wa James Tam, Demin Wang, Ronald Renaud, A. Vincent

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 · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsComputer scienceStereoscopyAdapter (computing)Computer visionDepth of fieldArtificial intelligenceLens (geology)SoftwareComputer graphics (images)ShutterField of viewComputer hardwareOpticsPhysics

Abstract

fetched live from OpenAlex

A field-sequential stereoscopic acquisition system based on off-the-shelf equipment and on in-house developed software for interpolating fields to interlaced frames is described. The software relies on object-based image analysis and the scheme is relatively robust for different types of scenes, including those with relatively fast motion and those with occluded and newly exposed areas. The off-the-shelf hardware consisted of a Sony DSR-PD1 with a Nu-View SX2000 Adapter. The adapter is a lens attachment that allows to views to be recorded: a view through the lens and a view displaced from the lens. Thus, a left-eye view is recorded in the odd (even) field and the right-eye view is recorded in the even (odd) field. After processing, the stereoscopic images could be played back at 120 Hz field rate and viewed without flicker and with smooth motion using standard electronic shutter glasses that are synchronized with the display of the odd and even fields.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.668

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 science0.0010.000
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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