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Record W2106331364 · doi:10.1109/tbc.2014.2306038

Improved Tile Format of Stereoscopic Video for 3-D TV Broadcasting

2014· article· en· W2106331364 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

VenueIEEE Transactions on Broadcasting · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsTileStereoscopyComputer scienceHigh-definition televisionComputer graphics (images)Broadcasting (networking)Frame (networking)Computer visionMPEG-2Block (permutation group theory)Artificial intelligenceComputer hardwareTelecommunicationsMathematicsComputer networkGeography

Abstract

fetched live from OpenAlex

Tile format is a new frame packing arrangement for the first generation of 3-D TV broadcasting services. It puts the left- and right-eye images of each stereoscopic image pair into a single composition frame that allows the service provider to reuse existing production and distribution infrastructure for offering 3-D TV services. Different from frame compatible formats, the tile format composition does not down-sample the left- and right-eye images and, thus, provides a higher video quality for both 3-D and 2-D display. The problem with the tile format is that it creates artificial edges in the right-eye image and introduces visible tiling artifacts around the artificial edges after compression. This brief paper presents a simple modification to the tile format composition method that significantly reduces the tiling artifacts. Experimental results show that local PSNRs around artificial edges are improved by over 1 dB.

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 categoriesMeta-epidemiology (narrow)
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 score0.800
Threshold uncertainty score1.000

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 head0.015
GPT teacher head0.240
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