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Record W1840630759 · doi:10.1109/cvpr.1991.139712

Constrained deformable superquadrics and nonrigid motion tracking

2002· article· en· W1840630759 on OpenAlexaff
Dimitris Metaxas, Demetri Terzopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of Toronto
Fundersnot available
KeywordsTrajectoryParameterized complexityComputer scienceMotion (physics)Point (geometry)Artificial intelligenceTracking (education)Computer visionObject (grammar)Deformation (meteorology)Face (sociological concept)AlgorithmMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

A physically based approach to the recovery of nonrigid 3-D motion and the tracking of nonrigid objects is presented. The approach makes use of deformable superquadrics, dynamics models that offer global deformation parameters which capture large-scale features and local deformation parameters which capture the details of complex shapes. The equations of motion governing the behavior of the models make them responsive to externally applied forces. The authors extend their prior formulation of these equations to include globally parameterized tapering and bending deformations. They further generalize the formulation to handle physically based point-to-point constraints between models. Such constraints enable one to automatically assemble object models from interconnected deformable superquadric parts. These composite models may be used to track the motions of articulated, flexible objects.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.187
Teacher spread0.165 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations116
Published2002
Admission routes1
Has abstractyes

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