Cooperative hybrid multi-camera tracking for people surveillance
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
Developing and improving people surveillance in public areas has been a topic of interest over past several years. A novel hybrid visual tracking system for event detection and people tracking is proposed in this paper. Our surveillance system consists of a calibrated stationary and a pan, tilt, and zoom (PTZ) camera. The stationary camera has a wide field of view, and it detects global events. The PTZ camera is triggered once an event is detected, and it pans and tilts to center the target based on the camera geometry. Then, the camera zooms in to obtain levels of details from the target which may not be clear in the wide view of the stationary camera. By applying color-based particle filtering (PF), the active camera is able to continuously centers and tracks the target in high resolution images. Experimental results are carried to further demonstrate the practicality of our proposed event monitoring system.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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