A fully parallel-pipelined architecture for full-search block-based motion estimation
Bibliographic record
Abstract
The motion estimation block in the digital video encoder is the most important block and the most difficult block to design. The block-based motion estimation is simple technique for doing motion estimation and it is suitable for VLSI implementation. The full search block-based motion estimation suffers from the huge number of computations needed to look for the best match block among all the candidate blocks. To face this computation cost parallel and pipelined implementations are needed. This paper presents innovative parallel-pipelined architecture for full-search block-based motion estimation. Full search block matching algorithm is used in the proposed architecture. The proposed architecture has been prototyped, simulated and synthesized for 0.18 /spl mu/m CMOS technology using TSMC standard cells. Using 100 MHz clock frequency the proposed architecture needs 50.5 /spl mu/sec to compute the motion vectors, which enables processing of more than 10k frames per second. The prototyped architecture consumes 312.07 mW with 1.6 V supply voltage and has core area of 0.795 mm/sup 2/.
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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 | 0.000 |
| 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) | 0.004 | 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".