Projector-based augmented reality with simultaneous 3D inspection using a single DMD
Bibliographic record
Abstract
This paper presents an industrial augmented reality system that simultaneously measures a component, identifies possible defects and displays the inspection result directly on the component. The processing is done in real time using a single DMD-based projector for both the inspection and augmented reality. The use of a single DMD eliminates the issue of registration between the component being inspected and an auxiliary augmented reality projector. The use of a single projection system also eliminates possible occlusion due to parallax between both projection systems. The system uses an algorithm that computes at video frame rate the temporal sequences of micromirror positions that, when imaged by a high-speed camera, contains a set of structured-light patterns. The temporal sequences are designed such that a human observer sees the desired augmented information. The proposed prototype can acquire 12 range images per second. The range uncertainty at 1-σ is 14 μm and each range image contains approximately one million 3D points.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".