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Record W2013399540 · doi:10.1145/1095034.1095043

ViewPointer

2005· article· en· W2013399540 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
TopicGaze Tracking and Assistive Technology
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceHeadsetComputer visionWearable computerContext (archaeology)Artificial intelligenceBluetoothObject (grammar)Mobile deviceWirelessEmbedded system

Abstract

fetched live from OpenAlex

We introduce ViewPointer, a wearable eye contact sensor that detects deixis towards ubiquitous computers embedded in real world objects. ViewPointer consists of a small wearable camera no more obtrusive than a common Bluetooth headset. ViewPointer allows any real-world object to be augmented with eye contact sensing capabilities, simply by embedding a small infrared (IR) tag. The headset camera detects when a user is looking at an infrared tag by determining whether the reflection of the tag on the cornea of the user's eye appears sufficiently central to the pupil. ViewPointer not only allows any object to become an eye contact sensing appliance, it also allows identification of users and transmission of data to the user through the object. We present a novel encoding scheme used to uniquely identify ViewPointer tags, as well as a method for transmitting URLs over tags. We present a number of scenarios of application as well as an analysis of design principles. We conclude eye contact sensing input is best utilized to provide context to action.

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: Methods · Consensus signal: none
Teacher disagreement score0.907
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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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

Citations58
Published2005
Admission routes1
Has abstractyes

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