An overview of a probabilistic tracker for multiple cooperative tracking agents
Why this work is in the frame
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Bibliographic record
Abstract
An overview of a probabilistic cooperative tracking approach is presented in this paper. First, a new tutorial-like detailed explanation of the condensation algorithm by Isard and Blake, (1998) is described. Then we apply the probabilistic tracker to track an object (easily extendable to multiple objects) according to multiple degrees of freedom of the cameras that are able to pan, tilt and zoom. To increase the robustness of the tracking system we extend the one camera tracking method to multiple camera case and each camera is considered as an agent that can communicate with a central unit or it can act based on its own decision. Each camera will gain a level of reliability during the tracking that is used in probabilistic tracking method to improve the performance
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.002 | 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