An affine-based algorithm and SIMD architecture for video compression with low bit-rate applications
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new affine-based algorithm and SIMD architecture for video compression with low bit rate applications. The proposed algorithm is used for mesh-based motion estimation and it is named mesh-based square-matching algorithm (MB-SMA). The MB-SMA is a simplified version of the hexagonal matching algorithm [1]. In this algorithm, right-angled triangular mesh is used to benefit from a multiplication free algorithm presented in [2] for computing the affine parameters. The proposed algorithm has lower computational cost than the hexagonal matching algorithm while it produces almost the same peak signal-to-noise ratio (PSNR) values. The MB-SMA outperforms the commonly used motion estimation algorithms in terms of computational cost, efficiency and video quality (i.e., PSNR). The MB-SMA is implemented using an SIMD architecture in which a large number of processing elements has been embedded with SRAM blocks to utilize the large internal memory bandwidth. The proposed architecture needs 26.9 ms to process one CIF video frame. Therefore, it can process 37 CIF frames/s. The proposed architecture has been prototyped using Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-/spl mu/m CMOS technology and the embedded SRAMs have been generated using Virage Logic memory compiler.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 it