# Real-Time Sleepiness Detection for Driver State Monitoring System

arXiv: https://arxiv.org/abs/2504.14807 · HTML: https://mlsanity.com/paper/2504.14807/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 20 references that are in the map.
- First posted on arXiv 21 Apr 2025.

## Abstract (arXiv)

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.