A real time, webcam based, driver attention state detection/monitoring system in Python3 using OpenCV and Mediapipe
Real-time driver drowsiness and distraction detection system. EU regulation C(2023)4523 compliant gaze zone detection.
Real-time driver fatigue detection system built with Python, OpenCV and MediaPipe. Detects drowsiness using EAR, MAR, PERCLOS, head pose estimation and a fatigue scoring system with Streamlit dashboard.
Detector de somnolencia - Ultralytics RTDETR
Real-time driver drowsiness & distraction detection on a plain laptop CPU - four chained OpenVINO models + a 30s PERCLOS scorer. 25-30 FPS, <8 MB models, fully offline. No GPU, no cloud.
Real-time AI-based driver drowsiness and behavior monitoring system using computer vision, sensor fusion, and multi-level alerts.
Real-Time Driver Drowsiness Detection with CBAM-CNN
Real-time driver drowsiness detection with per-driver calibration, a simulated driver for offline evaluation, a trained classifier benchmarked against the rule-based detector, and a human-in-the-loop safety supervisor.
Reproducible evaluation of an eye-state + temporal-alerting drowsiness pipeline, with subject-disjoint testing, baselines, failure analysis and oracle decomposition.
A.W.A.K.E. 2.0 — Raspberry Pi drowsiness detection with eye tracking, pan/tilt servo control, and alarm system
Offline in-browser drowsiness monitor — PERCLOS eye-closure detection, runs entirely on-device
Real-time driver drowsiness detection system using MediaPipe, EAR, MAR, PERCLOS, head-pose estimation, and intelligent alerting.
Real-time facial analysis from a webcam: emotion, drowsiness, and a pain proxy. Re-measured on subject-disjoint splits after the leaked-split numbers were withdrawn, where EAR and PERCLOS beat the drowsiness CNN.
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