Effective multi-program broadcasting of prerecorded video using VBR MPEG-2 coding
Bibliographic record
Abstract
The tradeoff between picture quality and bandwidth usage is a prominent issue in the world of broadcasting. Since broadcasters are able to transmit multiple streams simultaneously in a channel, they face the challenge of guaranteeing the contracted picture quality required by each of the transmitted video streams while maximizing the number of video streams carried in each channel. We have developed an easy to implement MPEG-2 based multi-program video coding system suitable for digital TV broadcast, video on demand, and high definition TV over broadcast satellite networks with limited bandwidth. Compared to present broadcast systems and for the same level of contracted picture quality, our system greatly increases the number of video streams transmitted in each channel. As a result, either a large number of transponders can be freed to carry real-time broadcasting or the level of picture quality can be significantly increased. By switching from tape storage to video server technology, the need for numerous playback (VTR) systems at the headend is eliminated. In addition, the most of the complete MPEG-2 encoders are replaced by much less complex MPEG-2 transcoders. All this means a much more cost-effective solution for broadcast stations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".