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Record W2150792958 · doi:10.1109/tabletop.2006.19

Gesture Registration, Relaxation, and Reuse for Multi-Point Direct-Touch Surfaces

2006· article· en· W2150792958 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGestureComputer scienceHuman–computer interactionUsabilitySet (abstract data type)GeneralityReuseConstructiveFocus (optics)Point (geometry)Multi-touchInteraction techniqueInteraction designEmbodied cognitionGesture recognitionArtificial intelligenceProgramming languageEngineering

Abstract

fetched live from OpenAlex

Freehand gestural interaction with direct-touch computation surfaces has been the focus of significant research activity. While many interesting gestural interaction techniques have been proposed, their design has been mostly ad-hoc and has not been presented within a constructive design framework. In this paper, we develop and articulate a set of design principles for constructing - in a systematic and extensible manner - multi-hand gestures on touch surfaces that can sense multiple points and shapes, and can also accommodate conventional point-based input. To illustrate the generality of these design principles, a set of bimanual continuous gestures that embody these principles are developed and explored within a prototype tabletop publishing application. We carried out a user evaluation to assess the usability of these gestures and use the results and observations to suggest future design guidelines.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.322

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 communication0.0000.001
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations177
Published2006
Admission routes1
Has abstractyes

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