Perspective and Geometry Approaches to Mouse Cursor Control in Spatial Augmented Reality
Bibliographic record
Abstract
Spatial augmented reality (SAR) can extend desktop computing out of the monitor and into our surroundings, but extending the standard style of mouse input is challenging due to real-world geometry irregularity, gaps, and occlusion. We identify two general approaches for controlling a mouse cursor in SAR: perspective-based approaches based on raycasting, such as Nacenta et. al’s Perspective Cursor, and geometry-based approaches that closely associate cursor movement with surface topology. For the latter, we introduce Everywhere Cursor, a geometry-based approach for indirect mouse cursor control for complex 3D surface geometry in SAR. A controlled experiment compares approaches. Results show the geometry-based Everywhere Cursor improves accuracy and precision by 29% to 60% on average in a tracing task, but when traversing long distances, the perspective-based Perspective Cursor and Raycasting techniques are 22% to 49% faster, albeit with 4% to 10% higher error rates.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".