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Record W2716651052 · doi:10.1162/pres.2006.15.1.108

The Hedgehog: A Novel Optical Tracking Method for Spatially Immersive Displays

2006· article· en· W2716651052 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

VenuePRESENCE Virtual and Augmented Reality · 2006
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsYork University
Fundersnot available
KeywordsComputer visionComputer scienceArtificial intelligenceTracking (education)CentroidDistortion (music)Tracking systemProjection (relational algebra)Constraint (computer-aided design)CalibrationWorkspaceLaser trackerVirtual realityLaserOpticsKalman filterEngineeringPhysicsAlgorithm

Abstract

fetched live from OpenAlex

Existing commercial technologies do not adequately meet the requirements for tracking in fully enclosed Virtual Reality displays. We present a novel six degree of freedom tracking system, the Hedgehog; which overcomes several limitations inherent in existing sensors and tracking technology. The system reliably estimates the pose of the user's head with high resolution and low spatial distortion. Light emitted from an arrangement of lasers projects onto the display walls. An arrangement of cameras images the walls and the two-dimensional centroids of the projections are tracked to estimate the pose of the device. The system is able to handle ambiguous laser projection configurations, static and dynamic occlusions of the lasers, and incorporates an auto-calibration mechanism due to the use of the SCAAT (single constraint at a time) algorithm. A prototype system was evaluated relative to a state-of-the-art motion tracker and showed comparable positional accuracy (1–2 mm RMS) and significantly better absolute angular accuracy (0.1° RMS).

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.317
Teacher spread0.284 · 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