Feedback scheme for thermal-visible video registration, sensor fusion, and people tracking
Why this work is in the frame
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Bibliographic record
Abstract
In this work, we propose a feedback scheme for simultaneous thermal-visible video registration, sensor fusion, and tracking for online video surveillance applications. The video registration is based on a RANSAC trajectory-to-trajectory matching that estimates an affine transformation matrix that maximizes the corresponding trajectory points and overlapping of foreground thermal and visible pixels. Sensor fusion uses the aligned images to compute sum-rule blobs for thermal and visible images and constructs the thermal-visible blobs. Finally, the multiple object tracking gets blobs constructed in sensor fusion as the input and outputs the trajectories of moving humans in the scene. We tested our method on long-term indoor and outdoor video sequences and demonstrate the effectiveness of our feedback design in obtaining better quality for both image registration and tracking.
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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 | 0.000 | 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