8-bit partial sums of 16 luminance values for fast block motion estimation
Why this work is in the frame
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Bibliographic record
Abstract
Fast block motion estimation algorithms are needed for real-time implementations of video coding standards due to the high computational complexity of the full-search algorithm for block motion estimation. In this paper, an algorithm using 8-bit partial sums of 16 luminance values for a fast block motion estimation is proposed. The technique of using the partial sums is employed to reduce the computational complexity of not only the full-search algorithm but also some of the fast block motion estimation algorithms while maintaining their accuracy. Furthermore, it is shown that the byte-type data-parallelism on an SIMD architecture can be utilized to access and process these partial sums concurrently to accelerate the process of motion estimation. Simulation results are presented to demonstrate that the use of the partial sums can accelerate the execution of the full-search, three-step search, and four-step search algorithms on an SIMD architecture significantly.
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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