High-speed three-dimensional surface measurement using band-limited illumination profilometry (BLIP)
Bibliographic record
Abstract
High-speed three-dimensional (3D) surface imaging by structured-light profilometry is currently driven by industrial needs, medical applications, and entertainment. However, the limitation of pattern projection speed has prevented the structured illumination to reach the kilohertz (kHz) level. The limited bandwidth of the data transmission has prevented the camera from streaming data continuously, which thus has brought difficulties in kHz-level image acquisition, processing, and display of 3D information during the occurrence of dynamic events (i.e., in real time). Besides, the tradeoff between the camera’s sensor readout rate and the activated pixel numbers has strained the existing methods from reaching a large field of view (FOV) at kilohertz (kHz)-level acquisition. To overcome these limitations, we have developed highspeed band-limited illumination profilometry (BLIP) in two configurations. The first configuration, employing a single camera with a CoaXPress interface (CI), enables real-time 3D surface information reconstruction at 1 kHz. The second configuration, employing two cameras with a CI, uses temporally interlaced acquisition (TIA) to improves the 3D imaging over 1000 frames per second on a field of view (FOV) of up to 180×130 mm<sup>2</sup> (corresponding to 1180×860 pixels) in captured images. We have demonstrated the systems’ performance by imaging various static and fast-moving 3D objects. CI-BLIP has been applied to fluid mechanics by imaging dynamics of a flag, which allowed observation of the wave propagation, gravity-induced phase mismatch, and asymmetric flapping motion. Meanwhile, TIA-BLIP has empowered the 3D visualization of glass vibration induced by sound. We expect BLIP systems to find diverse scientific and industrial applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".