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Record W1966073502 · doi:10.5555/846276.846291

Handrix: animating the human hand

2003· article· en· W1966073502 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

VenueSymposium on Computer Animation · 2003
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGuitarComputer scienceMotion (physics)Motion captureGRASPHuman–computer interactionMusical instrumentMusicalArtificial intelligenceComputer visionAcousticsVisual arts

Abstract

fetched live from OpenAlex

The human hand is a complex organ capable of both gross grasp and fine motor skills. Despite many successful high-level skeletal control techniques, animating realistic hand motion remains tedious and challenging. This paper presents research motivated by the complex finger positioning required to play musical instruments, such as the guitar. We first describe a data driven algorithm to add sympathetic finger motion to arbitrarily animated hands. We then present a procedural algorithm to generate the motion of the fretting hand playing a given musical passage on a guitar. The work here is aimed as a tool for music education and analysis. The contributions of this paper are a general architecture for the skeletal control of interdependent articulations performing multiple concurrent reaching tasks, and a procedural tool for musicians and animators that captures the motion complexity of guitar fingering.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.460

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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