MétaCan
Menu
Back to cohort
Record W1528201305 · doi:10.1109/iswc.1999.806928

The WristCam as input device

2003· article· en· W1528201305 on OpenAlexaff
Andrew Vardy, John A. Robinson, Li-Te Cheng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer visionComputer scienceWearable computerArtificial intelligenceComputer graphics (images)Rest (music)Movement (music)Position (finance)Set (abstract data type)WristBase (topology)Movement controlAcousticsMathematicsEmbedded systemPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

We show how images of a user's hand from a video camera attached to the underside of the wrist can be processed to yield finger movement information. Discrete (and discreet) movements of the fingers away from a rest position are translated into a small set of base symbols. These are interpreted as input to a wearable computer, providing unobtrusive control.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.176
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1760.051

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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations69
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicHand Gesture Recognition SystemsFrench-language works237,207