Work

Drowsiness Detector

Computer Vision (OpenCV)
Machine Learning
Real-Time Inference
Safety Systems

A safety-critical computer vision system that detects driver fatigue in real-time. Utilizes facial landmark detection to monitor eye aspect ratio (EAR) and issue immediate alerts.

Computer Vision Drowsiness Detection

Project Overview

Addressed the critical issue of driver fatigue with a non-intrusive monitoring system. The application uses a webcam feed to analyze facial cues and determine alert levels without requiring specialized hardware.

Key Features

  • Real-Time Detection: Prioritized low-latency inference for immediate alerts.
  • Techniques: Utilized facial landmark detection and machine learning techniques.
  • Accuracy: Tuned for high accuracy to ensure driver safety.