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Record W3144998485 · doi:10.1109/camp.2007.4350376

3D Reconstruction of Dynamic Scenes Dedicated to an Image Sensor of a Visual intracortical stimulator

2006· article· en· W3144998485 on OpenAlexafffund
Alexandra Delia Doljanu, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsPolytechnique Montréal
FundersCanada Research Chairs
KeywordsComputer visionComputer scienceArtificial intelligenceStereoscopyHigh dynamic rangeImage sensorIterative reconstructionDynamic rangeComputer graphics (images)

Abstract

fetched live from OpenAlex

This paper presents a global architecture of a range finder system based on the stereoscopic principle. The proposed system is dedicated to a visual intracortical stimulator in order to create artificial vision for people suffering from visual blindness. The 3D analysis of the environment is required allowing a better autonomy to the patient. The proposed device consists of an emitter projecting a light pattern from an infrared light source reflecting on a micromirror matrix. Images from the illuminated scene are captured by a camera. The three-dimensional range is reconstructed from the distortions in the reflected and captured image. Our approach to encode light patterns consists of taking advantage of a high-speed camera and adapting the Gray coded patterns to dynamic scenes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.381

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)0.0000.000

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 head0.003
GPT teacher head0.234
Teacher spread0.230 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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