A scalability study of fractional motion estimation for H.264 encoding
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.
Bibliographic record
Abstract
Fractional motion estimation (FME) is an important part of the H.264/AVC video encoding standard. The algorithm can significantly increase the compression ratio of video encoders while at the same time improve video quality. The FME algorithm, however, is also computationally expensive and can consist of over 45% of the total motion estimation process. To maximize the performance and efficiency of the FME implementations on Field-Programmable Gate Arrays (FPGAs), one needs to effectively exploit the inherent parallelism in the algorithm. In this work, we define two scalability approaches in order to intelligently parallelize the computing hardware. We implemented five scaled FME designs on a Xilinx XC5VLX330T (Virtex-5) FPGA. We found that scaling vertically with an 4 × 4 subblock is more efficient than scaling horizontally across several subblocks. It is shown that the best vertically scaled design can achieve 128 fps when encoding full 1920 × 1088 progressive HDTV video with only 20.7K LUTS and 23.4K registers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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