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Record W2099555798 · doi:10.1109/pacrim.1999.799530

Error concealment techniques for H.263 video transmission

2003· article· en· W2099555798 on OpenAlexaff
D. Kwon, Peter F. Driessen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceError concealmentResidualMotion estimationTransmission (telecommunications)Computer visionInterpolation (computer graphics)Channel (broadcasting)Overhead (engineering)CodecMotion compensationVideo qualityArtificial intelligenceBlock (permutation group theory)Video processingVisual communicationVideo compression picture typesData compressionDecoding methodsImage (mathematics)Computer networkVideo trackingComputer hardwareMultimediaAlgorithmTelecommunications

Abstract

fetched live from OpenAlex

Error resilient video transmission over such unreliable channels as wireless and Internet has became an important research issue especially with the increasing interests in mobile multimedia communication over the next generation wideband networks. Error detection and concealment techniques, which are applicable to such block-based motion estimation video coders as H.263 and MPEG, are proposed. An error concealment scheme by post-processing to hide visual artifacts and residual errors is utilized at the decoder. Those techniques recovering the damaged areas based on characteristics of image and video signals are implemented using both spatial interpolation and temporal motion estimation. Based on the international standard H.263, experimental results including video transmission characteristics over noisy channels are presented for a bit rate of 9.6kbps and QCIF resolution. It is shown that the proposed error concealment technique by post-processing enhances the decoder performance in terms of the reconstructed image quality represented by PSNR and doesn't require sacrifice of system overhead.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.319
Teacher spread0.293 · 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
GenreEmpirical

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
Published2003
Admission routes1
Has abstractyes

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