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

翻译：交通事故每年在全球造成数百万人死亡和数十亿美元经济损失，已成为一个重大问题。这些事故的主要原因之一是驾驶员困倦或疲劳。近年来，各种研究聚焦于使用基于摄像头的非接触式方案检测驾驶员睡眠/清醒状态，从而提升易用性。本研究除了眨眼频率外，还评估了驾驶员自适应的眨眼行为特征集以检测疲劳状态。从结果观察到，眨眼行为携带了用于疲劳检测的有效信息。所开发的基于图像的系统提供了一种能够自适应驾驶员生理特征及其在车内位置的解决方案。