A Real-Time Multiple Target Tracking Algorithm using Merged Probabilistic Data Association Technique and Smoothing Particle Filter
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a tracking system that combines the merged probabilistic data association (MPDA) technique together with the smoothing particle filter to track multiple targets. The MPDA approach combines the probabilistic nearest-neighbor filter (PNNF) together with the probabilistic data association (PDA) approach, in the data association step, to track multiple targets in dense clutter environment. Due to the high uncertainty when applying a particle filter to track a maneuverable target, the smoothing particle filter is used. Results show that combining MPDA together with smoothing particle filter can achieve a robust and real-time tracking system for tracking multiple targets even in dense clutter environment.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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