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Record W2120110455 · doi:10.1145/2702123.2702581

Tactum

2015· article· en· W2120110455 on OpenAlex
Madeline Gannon, Tovi Grossman, George Fitzmaurice

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 institutionsAutodesk (Canada)
Fundersnot available
KeywordsComputer scienceHuman–computer interactionGestureSet (abstract data type)Domain (mathematical analysis)Artificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

Skin-based input has become an increasingly viable interaction model for user interfaces, however it has yet to be explored outside the domain of mobile computing. In this paper, we examine skin as an interactive input surface for gestural 3D modeling-to-fabrication systems. When used as both the input surface and base canvas for digital design, skin-input can enable non-experts users to intuitively create precise forms around highly complex physical contexts: our own bodies. In this paper, we outline design considerations when creating interfaces for such systems. We then discuss interaction techniques for three different modes of skin-centric modeling: direct, parametric, and generative. We also present Tactum, a new fabrication-aware design system that captures a user's skin-centric gestures for 3D modeling directly on the body. Lastly, we show sample artifacts generated with our system, and share a set of observations from design professionals.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score1.000

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)0.0000.001

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 head0.037
GPT teacher head0.269
Teacher spread0.232 · 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

Citations48
Published2015
Admission routes1
Has abstractyes

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