DualCAD: Integrating Augmented Reality with a Desktop GUI and Smartphone Interaction
Bibliographic record
Abstract
Head-Mounted Displays (HMDs) combined with 3-or-more Degree-of-Freedom (DoF) input enable rapid manipulation of stereoscopic 3D content. However, such input is typically performed with hands in midair and therefore lacks precision and stability. Also, recent consumer-grade HMDs suffer from limited angular resolution and/or limited field-of-view as compared to a desktop monitor. We present the DualCAD system that implements two solutions to these problems. First, the user may freely switch at runtime between an augmented reality HMD mode, and a traditional desktop mode with precise 2D mouse input and an external desktop monitor. Second, while in the augmented reality HMD mode, the user holds a smartphone in their non-dominant hand that is tracked with 6 DoF, allowing it to be used as a complementary high-resolution display as well as an alternative input device for stylus or multitouch input. Two novel bimanual interaction techniques that leverage the properties of the smartphone are presented. We also report initial user feedback.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".