Non-contact driver cardiac physiological monitoring using video data
Why this work is in the frame
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Bibliographic record
Abstract
Driver physiological monitoring in vehicle is of great importance to provide a comfortable driving environment and prevent road accidents. In recent years, the development of non-contact techniques for such monitoring has been drawing research interests. In this paper, we present a non-contact video-based driver physiological monitoring framework to robustly acquire driver's heart rate and heart rate variability analysis using a simple consumer-level webcam. More specifically, a real-time facial feature detector as well as a joint blind source separation method is used to capture the driver's facial blood volume pulse signal. Experimental results from both laboratory and actual road driving conditions demonstrate that the proposed non-contact framework is promising HR and HRV monitoring, even with the existence of unstable light source variation.
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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 | 0.001 |
| 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