The Hedgehog: A Novel Optical Tracking Mecbod for Spatially Irnmersive Displays
Bibliographic record
Abstract
Existing commercial technologies do not adequately meet the requirements for tracking in fully-enclosed VR displays. We present the Hedgehog, which overcomes several limitations imposed by existing sensors and tracking technology. The tracking system robustly and reliably estimates the 6DOF pose of the device with high accuracy and a reasonable update rate. The system is composed of several cameras viewing the display walls and an arrangement of laser diodes secured to the user. The light emitted from the lasers projects onto the display walls and the 2D centroids of the projections are tracked to estimate the 6DOF pose of the device. The system is able to handle ambiguous laser projection configurations, static and dynamic occlusions of the lasers, and incorporates an intelligent laser activation control mechanism that determines which lasers are most likely to improve the pose estimate. The Hedgehog is also capable of performing auto-calibration of the necessary camera parameters through the use of the SCAAT algorithm. A preliminary evaluation reveals that the system has an angular resolution of 0.01 degrees RMS and a position resolution of 0.2 mm RMS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".