Detecting Driver Fatigue With Eye Blink Behavior
This addresses the problem of traffic accidents caused by driver fatigue, offering a non-contact solution, but it appears incremental as it builds on existing camera-based methods.
The study tackled driver fatigue detection by evaluating an adaptive eye blink behavior feature set, finding that it carries useful information for this purpose, and developed an image-based system that works adaptively to drivers' physical characteristics and positions.
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