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Record W2031472864 · doi:10.1109/iccse.2014.6926482

Improved radial basis function based parameterization for facial expression animation

2014· article· en· W2031472864 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFace recognition and analysis
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceFacial expressionGeodesicComputer facial animationAnimationComputer animationExpression (computer science)Radial basis functionPolygon meshFacial Action Coding SystemBasis (linear algebra)Face (sociological concept)Basis functionFunction (biology)Deformation (meteorology)Coding (social sciences)Computer visionAlgorithmArtificial intelligenceComputer graphics (images)MathematicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

This paper presents an improved method for facial expression animation based on the radial basis functions. The existing facial action coding system is adopted for expression parameterization. A set of parameters that are able to generate proper expressions is carefully selected through a series of analyses and comparisons. A deformation algorithm combining compactly supported radial basis functions with a geodesic distance metric is employed to address the difficulties in generating facial expressions, such as localized deformation and hole handling. In this work, the complex manipulation of a 3D face mesh is transformed into simple linear parameter adjustments, which is intuitive and efficient. Implementation results have demonstrated that real-time interactive mesh modification for facial expression animation is achieved.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.290

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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