Geometric video projector auto-calibration
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we address the problem of geometric calibration of video projectors. Like in most previous methods we also use a camera that observes the projection on a planar surface. Contrary to those previous methods, we neither require the camera to be calibrated nor the presence of a calibration grid or other metric information about the scene. We thus speak of geometric auto-calibration of projectors (GAP). The fact that camera calibration is not needed increases the usability of the method and at the same time eliminates one potential source of inaccuracy, since errors in the camera calibration would otherwise inevitably propagate through to the projector calibration. Our method enjoys a good stability and gives good results when compared against existing methods as depicted by our experiments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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