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Record W2982296756 · doi:10.1109/3dv.2019.00030

Frequency Shift Triangulation: A Robust Fringe Projection Technique for 3D Shape Acquisition in the Presence of Strong Interreflections

2019· article· en· W2982296756 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsProjectorPixelComputer scienceStructured lightComputer visionArtificial intelligenceProjection (relational algebra)Image resolutionTriangulationEncoding (memory)Computer graphics (images)MathematicsAlgorithm

Abstract

fetched live from OpenAlex

We present the Frequency Shift Method, a new structured light technique allowing 3D shape acquisition in the presence of strong interreflections. The intensity signal of each camera pixel is represented by one or several peaks in the Fourier domain. If there is no interreflection, only a single peak appears, otherwise several peaks are present. Each peak represents a projector pixel participating in the illumination of the surface point imaged at the camera pixel. In the baseline version of the proposed approach, the number of patterns required is proportional to the number of projector pixels. We also propose a modification that significantly reduces the required number of patterns by subdividing and encoding the projector into multiple virtual low-resolution projectors. A method based on dynamic programming is used to separate direct and indirect illuminations. Our experimental results illustrate the effectiveness of our method compared to existing ones.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.069
GPT teacher head0.313
Teacher spread0.245 · 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