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Record W2048212480 · doi:10.1145/2512349.2512351

Interactive surfaces for interaction with stereoscopic 3d (ISIS3D)

2013· article· en· W2048212480 on OpenAlexaff
Florian Daiber, Bruno R. de Araújo, Frank Steinicke, Wolfgang Stuerzlinger

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsYork University
Fundersnot available
KeywordsStereoscopyComputer science3D interactionHuman–computer interactionMulti-touchComputer graphics (images)Mobile deviceGraphicsVirtual realityMultimediaComputer visionWorld Wide Web

Abstract

fetched live from OpenAlex

With the increasing distribution of multi-touch capable devices multi-touch interaction becomes more and more ubiquitous. Multi-touch interaction offers new ways to deal with 3D data allowing a high degree of freedom (DOF) without instrumenting the user. Due to the advances in 3D technologies, designing for 3D interaction is now more relevant than ever. With more powerful engines and high resolution screens also mobile devices can run advanced 3D graphics, 3D UIs are emerging beyond the game industry, and recently, first prototypes as well as commercial systems bringing (auto-) stereoscopic display on touch-sensitive surfaces have been proposed. With the Tutorial and Workshop on ``Interactive Surfaces for Interaction with Stereoscopic 3D (ISIS3D)'' we aim to provide an interactive forum that focuses on the challenges that appear when the flat digital world of surface computing meets the curved, physical, 3D space we live in.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.062
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0620.011

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 head0.260
Teacher spread0.247 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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