Multimodal Driver Drowsiness Detection From Video Frames

Abstract

Fatigue leads to tiredness, exhaustion, and sleepiness. Driving in fatigue conditions is considered dangerous and can cause serious road accidents. According to reports about 25% of road accidents are due to driver drowsiness. The main reason behind drowsiness is fatigue. While driving continuously on long trips, drivers feel sleepy. In this paper, we proposed a novel approach that is efficient enough to detect driver drowsiness accurately. An intelligent system, that can quickly and precisely determine whether the driver is feeling drowsiness or not during driving and can also generate a warning in real-time scenarios is implemented. Thus, resulting in reducing the number of accidents that take place due to the drowsiness of the drivers as well as the death rate. In this paper, drowsiness is detected by observing facial features such as Eyes and Mouth.