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Record W2141812168 · doi:10.1109/crv.2006.29

Epipolar Geometry for the Rectification of Cubic Panoramas

2006· article· en· W2141812168 on OpenAlexafffund
Florian Kangni, Robert Laganière

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEpipolar geometryFundamental matrix (linear differential equation)Computer visionArtificial intelligenceComputer scienceProjective geometryContext (archaeology)RectificationImage rectificationInterpolation (computer graphics)Computer graphics (images)GeometryCubic functionImage (mathematics)MathematicsDifferential geometryMathematical analysisGeographyEngineering

Abstract

fetched live from OpenAlex

Image panoramas are of importance for virtual navigation in remote or synthetic environments. To process these panoramas, different representations have been proposed; this paper presents a study of cubic panoramas. Standard projective geometry concepts are adapted to cubic panoramas to derive the notions of fundamental matrix, essential matrix and the equivalent of stereo rectification. Methods and results are presented which could be very helpful in obtaining solutions to disparity estimation, pose estimation and view interpolation problems in the context of cubic panoramas.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.093

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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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 designOther design
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

Citations23
Published2006
Admission routes2
Has abstractyes

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