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Record W2168783993 · doi:10.1109/70.897784

Multiple camera model-based 3-D visual servo

2000· article· en· W2168783993 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

VenueIEEE Transactions on Robotics and Automation · 2000
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer visionArtificial intelligenceJacobian matrix and determinantComputer scienceKinematicsPoseRobotVideo trackingTranslation (biology)Rotation (mathematics)ServoVisual servoingObject (grammar)Mathematics

Abstract

fetched live from OpenAlex

A multiple camera, visual servo system is presented that tracks and aligns rigid objects in 3D using wire-frame models. The system is capable of achieving frame-rate (30 Hz between two cameras) object tracking while using nonlinear iterative pose estimation. Tracking begins with a rough estimate of the positions of the objects. The relative rotation and translation of the cameras (external calibration) is calculated from the images. Six degree-of-freedom object pose estimates are computationally fused to provide tracking that is both stable and robust to occlusion. The tracking data is used to move (servo) the objects together while performing online robot Jacobian estimation. The robot is controlled in real time by joint angles with no prior knowledge of its kinematics.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score0.428

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 head0.263
Teacher spread0.250 · 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