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Record W2147722715 · doi:10.1109/crv.2006.38

Handling Occlusions in Real-time Augmented Reality : Dealing with Movable Real and Virtual Objects

2006· article· en· W2147722715 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
TopicAugmented Reality Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAugmented realityVirtual realityComputer scienceComputer visionComputer graphics (images)Mixed realityHuman–computer interactionComputer-mediated realityArtificial intelligenceReal-time computing

Abstract

fetched live from OpenAlex

Realistic rendering in real-time augmented reality applications leads one to consider physical interactions between real and virtual worlds. One of these interactions is mutual occlusions in the rendered viewpoint. This paper presents two approaches for handling occlusions when the real objects can be displaced or deformed. The first approach is model-based. It is suited for a static viewpoint and relies only on a tracked bounding volume model within which the object’s silhouette is carved. The second approach is depthbased and makes it possible to change the viewpoint by exploiting a handheld stereo camera. Both approaches are devised to minimize the effect of real object tracking errors in the rendered viewpoint.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score0.987

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 communication0.0000.000
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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

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