An improved real-time miniaturized embedded stereo vision system (MESVS-II)
Bibliographic record
Abstract
In this paper we describe a fully integrated, real-time, miniaturized embedded stereo vision system (MESVS-II), which fits within 5times5cm and consumes very low power. This is a significant improvement over the original MESVS-I system in terms of performance, quality and accuracy of results. MESVS-II running at 600MHz per core, is capable of operating at up to 20 fps, which is twice as fast as MESVS-I, due to the efficient implementation of stereo-vision algorithms, improved memory and data management, in-place processing scheme, code optimization, and the pipelined-programming model that takes advantage of the dual-core architecture of the embedded processor. The firmware incorporates sub-sampling, rectification, pre-processing, matching, LRC (Left/Right Consistency) check and post-processing. As demonstrated by our experimental results, we have also enhanced the robustness of the stereo-matching engine to radiometric variations by choosing census transform over rank transform.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".