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Record W2133028306 · doi:10.1145/2207676.2208297

Virtual projection

2012· article· en· W2133028306 on OpenAlex
Dominikus Baur, Sebastian Boring, Steven Feiner

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 Calgary
Fundersnot available
KeywordsComputer scienceZoomComputer visionProjectorArtificial intelligenceMobile deviceProjection (relational algebra)Computer graphics (images)Augmented realityOrientation (vector space)Lens (geology)Engineering

Abstract

fetched live from OpenAlex

Handheld optical projectors provide a simple way to overcome the limited screen real-estate on mobile devices. We present virtual projection (VP), an interaction metaphor inspired by how we intuitively control the position, size, and orientation of a handheld optical projector's image. VP is based on tracking a handheld device without an optical projector and allows selecting a target display on which to position, scale, and orient an item in a single gesture. By relaxing the optical projection metaphor, we can deviate from modeling perspective projection, for example, to constrain scale or orientation, create multiple copies, or offset the image. VP also supports dynamic filtering based on the projection frustum, creating overview and detail applications, and selecting portions of a larger display for zooming and panning. We show exemplary use cases implemented using our optical feature-tracking framework and present the results of a user study demonstrating the effectiveness of VP in complex interactions with large displays.

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: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.941

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)0.0000.001

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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

Citations53
Published2012
Admission routes1
Has abstractyes

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