Detecting Driver Fatigue With Eye Blink Behavior
Ali Akin, Habil Kalkan

TL;DR
This paper presents an adaptive, camera-based system for detecting driver fatigue by analyzing eye blink behavior, which improves safety by identifying sleepiness without physical contact.
Contribution
It introduces a novel driver adaptive eye blink behavior feature set and evaluates its effectiveness for fatigue detection using image-based methods.
Findings
Eye blink behavior provides useful fatigue indicators.
The system adapts to driver physical characteristics.
Effective in real-time fatigue detection.
Abstract
Traffic accidents, causing millions of deaths and billions of dollars in economic losses each year globally, have become a significant issue. One of the main causes of these accidents is drivers being sleepy or fatigued. Recently, various studies have focused on detecting drivers' sleep/wake states using camera-based solutions that do not require physical contact with the driver, thereby enhancing ease of use. In this study, besides the eye blink frequency, a driver adaptive eye blink behavior feature set have been evaluated to detect the fatigue status. It is observed from the results that behavior of eye blink carries useful information on fatigue detection. The developed image-based system provides a solution that can work adaptively to the physical characteristics of the drivers and their positions in the vehicle
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Taxonomy
TopicsSleep and Work-Related Fatigue · Ergonomics and Musculoskeletal Disorders · Traffic and Road Safety
MethodsSparse Evolutionary Training
