Real-Time Sleepiness Detection for Driver State Monitoring System
Journal:
arXiv
Published Date:
Apr 21, 2025
Abstract
A driver face monitoring system can detect driver fatigue, which is a
significant factor in many accidents, using computer vision techniques. In this
paper, we present a real-time technique for driver eye state detection. First,
the face is detected, and the eyes are located within the face region for
tracking. A normalized cross-correlation-based online dynamic template matching
technique, combined with Kalman filter tracking, is proposed to track the
detected eye positions in subsequent image frames. A support vector machine
with histogram of oriented gradients (HOG) features is used to classify the
state of the eyes as open or closed. If the eyes remain closed for a specified
period, the driver is considered to be asleep, and an alarm is triggered.
