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Detecting Driver Fatigue With Eye Blink Behavior

arXiv 2407.02222 ↗First posted 2 Jul 2024cs.CVcited by 0

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Abstract (arXiv)

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

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 13 references that are in the map. First posted on arXiv 2 Jul 2024.

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References · 1

  1. 2020Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithmcited by 3

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