Facial Landmark and Drowsiness Detection using EAR | Python, OpenCV and Dlib

Описание: Real-Time Facial Landmark & Drowsiness Detection System
This project showcases a live computer vision system that detects facial landmarks and monitors drowsiness using the Eye Aspect Ratio (EAR) technique.

What’s Included in the Video:

• Real-time face detection using HOG & CNN models
• 68-point facial landmark detection
• Eye Aspect Ratio (EAR) computation
• Drowsiness detection based on eye closure duration
• Visual alerts when fatigue is detected
• Smooth webcam integration for live monitoring

Use Cases:
• Driver fatigue detection
• Workplace safety and monitoring
• Human-computer interaction (HCI)

#ai #computervision #dlib #opencv #facedetection #drowsinessdetection #faciallandmarks #EAR