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Record W1594878354 · doi:10.1109/3dpvt.2004.22

A unified representation for interactive 3D modeling

2004· article· en· W1594878354 on OpenAlexaff
D. Tubic, P. Hébert, Jean-Daniel Deschênes, Denis Laurendeau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRepresentation (politics)Computer science3D modelingGeometric modelingVisualizationSolid modelingRange (aeronautics)Surface (topology)Data modelingProcess (computing)Data structureEuclidean vectorTheoretical computer scienceInteractive visualizationAlgorithmObject (grammar)Artificial intelligenceMathematicsGeometry

Abstract

fetched live from OpenAlex

Interactive 3D modeling is the process of building a 3D model of an object or a scene in real-time while the 3D (range) data is acquired. This is possible only if the computational complexity of all involved algorithms is linear with respect to the amount of data. We propose a new framework for 3D modeling where a complete modeling chain meets with this requirement. The framework is based on the use of vector fields as an implicit surface representation. Each modeling step, registration, surface reconstruction, geometric fusion, compression and visualization is solved and explained using the vector fields without any intermediate representations. The proposed framework allows model reconstruction from any type of 3D data, surface patches, curves, unorganized sets of points or a combination of these. 1.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.005

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 head0.052
GPT teacher head0.357
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2004
Admission routes1
Has abstractyes

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