3-D Structured Light Scanning With Phase Domain-Modulated Fringe Patterns
Bibliographic record
Abstract
Existing 3-D structured light (SL) scanning methods require a high number of images (multifrequency phase shifting, MF-PS) or embed signals in the space domain (space domain modulation phase shifting, SDM-PS) to conduct phase unwrapping. These methods are either movement sensitive (for MF-PS) or low in accuracy (for SDM-PS). In this work, a new 3-D SL scanning method is proposed to use the theoretical minimum of three images only. Unlike existing methods that directly embed signals in the space domain, the assistance signals are modulated in the phase domain of PS images, inspired by the phase-shift keying (PSK) theory. Phase calculation in the proposed phase domain modulation phase shifting (PDM-PS) method is independent of embedded assistance signals. The signal to noise ratio (SNR) of phase codewords and the accuracy of phase unwrapping and 3-D reconstruction are well retained. Experimental results demonstrated that the proposed PDM-PS method using only three images was able to achieve comparable 3-D measurement accuracy as the traditional MF-PS method (three images vs. nine images, 0.03 mm vs. 0.02 mm); and both using three images, the proposed PDM-PS method outperformed the traditional SDM-PS method in terms of measurement accuracy (0.03 mm vs. 0.07 mm).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".