A Centralized Omnidirectional Multi-Camera System with Peripherally-Guided Active Vision and Depth Perception
Why this work is in the frame
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Bibliographic record
Abstract
The growing popularity of omnidirectional vision technology has spawned numerous multi-camera designs that integrate various different camera types. This paper presents an omnidirectional vision system that combines a catadioptric camera, a fisheye camera and an active perspective camera. Aligning these cameras vertically provides a number of beneficial features, such as allowing simple peripherally-guided active vision, depth perception and a near spherical composite omnidirectional field of view. By having the active camera rotate around the outer perimeter, it can attain complete spherical access to the environment. The triangulation performance is evaluated experimentally using a target fixed to a long translation stage. Static positions of the target are estimated using a stereo pair that consists of one active perspective camera and one omnidirectional camera. Overall, the system provides sufficient accuracy to facilitate further surveillance research.
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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 | 0.000 |
| 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