Design of a Spatially Anchoring Framework Using an Augmented Reality Head-Mounted Device and Fisheye Lens
Bibliographic record
Abstract
<p>The development of improved Augmented Reality (AR) Head-Mounted Devices (HMDs) have led to many potential applications for augmented reality. In the case of surgery, an HMD could be used as an assistive tool to address some deficits that popular neuronavigation devices have, such as a disturbance to surgical workflow and surgeon comfort.</p> <p>This thesis aims to bring an HMD-based overlay framework that can be used in the operating room. Through a combination of Android Studio, OpenCV, and OpenGL, a method to localize an HMD (ODG R9s) was created. This framework used a fisheye lens and a marker-based tracking method to localize the headset and renders a spatially-anchored 3D model in real time. A “Focus” mode was also developed in stabilizing the camera pose estimation and translational and rotational errors were quantified.</p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".