Precise Photogrammetric Reconstruction Using Model-Based Image Fitting for 3D Beam Deformation Monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Periodic structural health monitoring of infrastructure systems is important to avoid economic losses and human casualties. Traditionally, deformation monitoring has been done through surveying techniques. Recently, with the increased availability of inexpensive off-the-shelf cameras, photogrammetry has become a viable noncontact alternative for complete three-dimensional reconstruction of the object or surface of interest. This paper aims at combining two methodologies of photogrammetric reconstruction—image-matching-based reconstruction and model-based image fitting—to achieve submillimeter precision for the estimation of both vertical deflections and horizontal displacements. The proposed methodology was tested with data collected using a photogrammetric system at a structures laboratory where a concrete beam was subjected to different loading conditions by a hydraulic actuator. The experimental results showed that the photogrammetric system was capable of monitoring both static and dynamic deformations. The methodology used exhibited a high level of automation and the final results yielded a root-mean-square error (RMSE) of half a millimeter.
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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 | 0.000 |
| 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 it