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Record W2012416431 · doi:10.1109/3dtv.2013.6676650

A study on the relationship between depth map quality and the overall 3D video quality of experience

2013· article· en· W2012416431 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
TopicImage and Video Quality Assessment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQuality (philosophy)Rank correlationComputer scienceDepth mapCorrelationVideo qualityArtificial intelligenceCorrelation coefficientComputer visionSpearman's rank correlation coefficientQuality ScoreDepth perceptionRank (graph theory)FidelityPerceptionMathematicsImage (mathematics)Metric (unit)PsychologyMachine learningEngineering

Abstract

fetched live from OpenAlex

The emergence of multiview displays has made the need for synthesizing virtual views more pronounced, since it is not practical to capture all of the possible views when filming multiview content. View synthesis is performed using the available views and depth maps. There is a correlation between the quality of the synthesized views and the quality of depth maps. In this paper we study the effect of depth map quality on perceptual quality of synthesized view through subjective and objective analysis. Our evaluation results show that: 1) 3D video quality depends highly on the depth map quality and 2) the Visual Information Fidelity index computed between the reference and distorted depth maps has Pearson correlation ratio of 0.75 and Spearman rank order correlation coefficient of 0.67 with the subjective 3D video quality.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.254
GPT teacher head0.427
Teacher spread0.173 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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