Bit-rate estimation for bit-rate reduction H.264/AVC video transcoding in wireless networks
Why this work is in the frame
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Bibliographic record
Abstract
Multimedia applications such as video streaming and mobile TV are emerging as the most promising applications over wireless networks. The increased coding efficiency and network friendly architecture of the latest video coding standard H.264/AVC has facilitated the delivery of coded video content to wireless users. However, wireless networks allow lower transmission bit-rates than wired networks while the display resolution of mobile devices is generally smaller than that of standard definition (SD) TV. This calls for fast bit-rate reduction techniques through video transcoding that can deliver the best video quality to the mobile receiver while adhering to the bit-rate constraints of the wireless network. In this paper, we present a bit-rate estimation model that speeds up the transcoding process by predicting the transcoded video bit-rate for different spatial resolution reduction ratios and quantization steps. We demonstrate that, on average, our proposed model can accurately estimate the bit-rate of the transcoded video to within 5% of the actual bit-rate of the transcoded video.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it