An area efficient motion estimator for a new block-matching algorithm
Bibliographic record
Abstract
In this paper, an area efficient implementation of a motion estimator with full search capability, based on simplified pixel difference classification (PDC) algorithm is presented. Based on a novel approach of matching criteria, enhanced by the fixed pixel threshold technique, the hardware requirement for every single processing element was cut down at a ratio of 30-40% compared with the implementation of conventional algorithms. It is designed for a block size of 16 /spl times/ 16 pixels, search area -8/7, and can be cascaded by 4 for a search range of -16/15. It allows sequential inputs but performs parallel computations. At 100 MHz clock rate, it needs 2.5 usec to finish calculating one motion vector. Realized by TSMC O.18 /spl mu/m CMOS technology, it has a core area of 1.01 mm/sup 2/.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".