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Record W4392862526 · doi:10.32920/25417252

FPCB Mirror Based 1D Retroreflected Laser Scanning for Projector Interactivity Implementation

2024· preprint· en· W4392862526 on OpenAlexaff
Kevin Lin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsProjectorInteractivityRetroreflectorLaser scanning3d scanningOpticsComputer scienceComputer graphics (images)LaserMaterials scienceComputer visionPhysics

Abstract

fetched live from OpenAlex

This thesis presents a flexible printed circuit board (FPCB) mirror-based scanner used in 1D retroreflected laser scanning for the implementation of projector interactivity. A 12 mm x 12 mm square aperture FPCB mirror was designed and fabricated. The FPCB mirror can be actuated to a maximum of 116° and has a fundamental frequency of approximately 72 Hz. Using a novel scanning method with FPCB mirrors, position sensing detectors, and retroreflection, the average absolute error and the average standard deviation was found to be approximately 0.41° and 0.31° respectively. This system was used to implement interactivity for an ordinary long-throw projector with a screen size of 1535 mm x 1160 mm. The average absolute error of the interactive projector system at 5 Hz was found to be approximately 19.4 mm. Using both a finger and marker, the system was capable of various functionalities such as drawing, button pressing, and swiping.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.877
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.057
GPT teacher head0.401
Teacher spread0.345 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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