Everything to Gain: Combining Area Cursors with increased Control-Display Gain for Fast and Accurate Touchless Input
Bibliographic record
Abstract
Touchless displays often use mid-air gestures to control on-screen cursors for pointer interactions. Area cursors can simplify touchless cursor input by implicitly targeting nearby widgets without the cursor entering the target. However, for displays with dense target layouts, the cursor still has to arrive close to the widget, meaning the benefits of area cursors for time-to-target and effort are diminished. Through two experiments, we demonstrate for the first time that fine-tuning the mapping between hand and cursor movements (control-display gain – CDG) can address the deficiencies of area cursors and improve the performance of touchless interaction. Across several display sizes and target densities (representative of myriad public displays used in retail, transport, museums, etc), our findings show that the forgiving nature of an area cursor compensates for the imprecision of a high CDG, helping users interact more effectively with smaller and more controlled hand/arm movements.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".