Author manuscript, published in "10th International Conference on Virtual Reality (VRIC 2008), Laval: France (2008)" Fly Over, a 3D Interaction Technique for Navigation in Virtual Environments Independent from Tracking Devices
Bibliographic record
Abstract
A good 3D user interface associated with 3D interaction techniques is very important in order to increase the realness and the easiness of the interaction in Virtual Environments (VEs). 3D user interfaces systems often use multiple input devices, especially, tracking devices. So, the search for new metaphors and techniques for 3D interaction adapted to the navigation task, independently from devices used, is an important stage for the realization of future 3D interaction systems that support multimodality, in order to increase efficiency and usability. In this paper we propose a new tracking deviceindependent 3D interaction model called Fly Over. The core principles of Fly Over make it compatible with all 3D/2D-pointing devices.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.384 | 0.125 |
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".