Moving objects with 2D input devices in CAD systems and Desktop Virtual Environments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Part assembly and scene layout are basic tasks in 3D design in Desktop Virtual Environment (DVE) systems as well as Computer Aided Design (CAD) systems. 2D input devices such as a mouse or a stylus are still the most common input devices for such systems. With such devices, a notably difficult problem is to provide an efficient and predictable object motion in 3D based on their 2D motion. This paper presents a new technique to move objects in CAD/DVE using 2D input devices.The technique presented in this paper utilizes the fact that people easily recognize the depth-order of shapes based on occlusions. In the presented technique, the object position follows the mouse cursor position, while the object slides on various surfaces in the scene. In contrast to existing techniques, the movement surface and the relative object position is determined using the whole area of overlap of the moving object with the static scene. The resulting object movement is visually smooth and predictable, while avoiding undesirable collisions. The proposed technique makes use of the framebuffer for efficiency and runs in real-time. Finally, the evaluation of the new technique with a user study shows that it compares very favorably to conventional techniques.
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.
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 it