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Record W4251578544 · doi:10.1145/508936.508939

A mesh update requirement for hierarchical adaptive meshes in mesh-based motion tracking

2002· article· en· W4251578544 on OpenAlexaff
Alfred C. H. Yu, Wael Badawy

Bibliographic record

VenueProceedings of the 2002 ACM symposium on Applied computing - SAC '02 · 2002
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPolygon meshComputer scienceBenchmark (surveying)Frame (networking)Tracking (education)Volume meshMesh generationMotion (physics)Triangle meshT-verticesTopology (electrical circuits)Computer visionComputer graphics (images)Finite element methodMathematicsEngineeringComputer network

Abstract

fetched live from OpenAlex

This paper presents a mesh update requirement for hierarchical adaptive meshes in mesh-based motion tracking. The requirement states that since hierarchical adaptive meshes are constructed according to the video contents of a predicted frame, constructing a different mesh topology for each predicted frame is necessary in order to most accurately describe the video contents in a predicted frame. It has been statistically verified in the analysis section of this paper that if the requirement is not satisfied, the prediction quality would be lowered. The analysis is performed on different QCIF benchmark sequences.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.001
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 head0.039
GPT teacher head0.250
Teacher spread0.211 · 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
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
Published2002
Admission routes1
Has abstractyes

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