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Record W2325451640

Handheld projector interaction

2009· article· en· W2325451640 on OpenAlexaff
Xiang Cao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMobile deviceHuman–computer interactionComputer scienceProjectorMobile interactionInteraction techniqueDisplay sizeAugmented realityMultimediaDisplay deviceGestureComputer visionWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

The recent trend towards miniaturization of projection technology indicates that handheld devices will soon have the ability to project information onto any surface, thus enabling interaction and applications that are not possible with current handheld devices. This opens up an emerging research area on interaction using handheld projectors. With the ability to project information, a handheld device can surmount the limitations of its small internal screen by creating a larger information display on an external surface. By doing so, the display and interaction space can be expanded to cover almost an entire physical environment. Large amounts of data can be displayed, a rich interaction vocabulary can be supported, and multiple co-located people can share the viewing experience at the same time. In this thesis, I investigate research issues involved in the design, implementation, and user performance and behaviors regarding the usage of interactive handheld projectors. I create a handheld projector interaction prototype platform, and explore interaction concepts and techniques to support both single and multi-user interaction using one or several handheld projectors. I also empirically investigate the user behaviors

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.494

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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 teacher head, 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

Citations11
Published2009
Admission routes1
Has abstractyes

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