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Record W2151996881 · doi:10.1109/icme.2011.6012225

A rate control algorithm for ×264 high definition video conferencing

2011· article· en· W2151996881 on OpenAlexaff
Abbas Javdtalab, Mona Omidyeganeh, Shervin Shirmohammandi, Mojtaba Hosseini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCodecComputer scienceEncoderVideoconferencingBandwidth (computing)Video qualityHigh-definition videoAlgorithmReal-time computingVideo streamingComputer networkMultimediaComputer hardwareOperating system

Abstract

fetched live from OpenAlex

Current rate control algorithms developed in the H.264 encoder are unable to address High Definition video streaming requirements over best effort networks such as the Internet. We propose a rate controller (RC) for H.264 high definition video conferencing (HDVC), specifically developed in the x264 codec: an open source and high performance H.264/AVC encoder. Called the Dynamic Constant Rate Factor (DCRF), our RC tries to provide the best possible quality in terms of the current bandwidth available at a given instance of video streaming. The proposed method is analyzed from different aspects including network bandwidth, frame size, PSNR and SSIM measurements. In addition to the objective tests, DCRF is evaluated by human observers for subjective performance evaluation. The results prove that DCRF provides better results than current RC methods for HDVC.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.089
GPT teacher head0.247
Teacher spread0.158 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2011
Admission routes1
Has abstractyes

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