Fast multi-frame motion estimation for video processing
Bibliographic record
Abstract
Motion estimation is being utilized more and more in video post-production and display for a wide range of applications. These applications require accurate motion trajectories at low computational cost. This paper presents a novel motion estimation algorithm that combines the accuracy of MAP estimation with the speed of hierarchical block-matching algorithm (BMA). This MAP estimation uses three consecutive pictures, instead of the conventional two, and one previously estimated motion field to exploit the temporal correlation between motion fields and to determine motion in occluded areas. The optimization of the MAP estimation is performed using full search and implemented by means of look-up tables. The full search ensures that the optimization converges to the global minimum, while the look-up tables dramatically reduce the computational cost. Experiment results show that the proposed algorithm provides motion trajectories that are much more accurate than those obtained using the full-search BMA and hierarchical BMA. It is much faster than the full-search BMA, but slower than the hierarchical BMA.
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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 | 0.001 |
| 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 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".