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Record W2348097582

Matching contour of 3-D objects based on B-splines curve representation

2005· article· en· W2348097582 on OpenAlex
Jianli Du

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
TopicImage Processing and 3D Reconstruction
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsCurvatureMathematicsMatching (statistics)Invariant (physics)Torsion of a curveAlgorithmTorsion (gastropod)Transformation (genetics)Rotation (mathematics)Artificial intelligencePattern recognition (psychology)GeometryComputer sciencePrincipal curvatureMean curvature
DOInot available

Abstract

fetched live from OpenAlex

Aim For recovering shape from contour of fragments.Methods The method for representing and matching 3-D curve is presented.The Curves are represented by splines fitted through sequences of points extracted from contour.In reparametrization with arcs length,the curvature and torsion is invariant to translation and rotation transformation.That possess very attractive properties such as local and stable.The curvature and torsion are viewcd as feature sets.The 3-D curve matching task is reduced into a 1D numerical string-matching problem.Results A fast algorithm matching is adopted by using ordered list so that the matching is easy and the processing time is greatly saved.,Experiments show that the matching algorithm is efficiency.Conclusion The matching algorithm has application in recovering 3-D Shape of fragments.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.190

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 communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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