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Record W2150036968 · doi:10.1109/tbc.2009.2032801

Bit-Rate Efficiency of H.264 Encoders Measured With Subjective Assessment Techniques

2009· article· en· W2150036968 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 · 2009
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsEncoderBit (key)Bit rateComputer scienceVideo qualityBit error rateImage qualityHarmonic Vector Excitation CodingQuality (philosophy)MPEG-4Computer hardwareReal-time computingDecoding methodsComputer visionAlgorithmCoding (social sciences)MathematicsStatisticsComputer networkEngineeringImage (mathematics)

Abstract

fetched live from OpenAlex

In this study we evaluated the bit-rate efficiency of current hardware H.264 encoders as compared to that of established MPEG-2 hardware encoders. To estimate bit-rate efficiency, we measured the subjective video quality of MPEG-2 encoded material processed at three bit rates: 8, 12, and 16 Mbps, and determined the bit-rate at which H.264 encoded material produced similar subjective video quality. The MPEG-2 and H.264 bit rates that resulted in the same perceived video quality were used to estimate bit-rate efficiency.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.269
Teacher spread0.245 · 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