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Record W2070171532 · doi:10.1364/ol.36.004770

Cross-diffractive optical elements for wide angle geometric camera calibration

2011· article· en· W2070171532 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Letters · 2011
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalibrationOpticsDiffractionComputer scienceAperture (computer memory)Camera resectioningField of viewPhotogrammetryRemote sensingPhysicsComputer visionAcoustics

Abstract

fetched live from OpenAlex

Diffractive optical elements (DOEs) can generate multiple two-dimensional (2D) diffraction grids that can be used to calibrate cameras for photogrammetry. However, several factors limit the accuracy and the functionality of this technique. One of the most important is the DOE fabrication itself. A large DOE with wide 2D fan-out grids is very difficult and costly to develop. Consequently, the calibration is limited to small aperture cameras and/or limited angles. To overcome these problems, we present a low cost solution. We propose to use two large, commercially available, crossed phase DOEs that generate 15×15 equally spaced dots. As the DOEs are not perfect, the unwanted secondary diffractive orders are used as calibration targets to expand the calibration field of view. We show that the use of the primary and secondary diffractive orders provides a valuable calibration tool for wide angle aerial cameras.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.289
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it