In this paper, a new Driver Assistance System (DAS) for automatic driver’s drowsiness detection based on visual information and image processing is presented. This algorithm works on several stages using Viola and Jones (VJ) object detector, expectation maximization algorithm, the Condensation algorithm and support vector machine to compute a drowsiness index. The goal of the system is to help ...

Drowsiness is a major risk factor for road safety, contributing to serious injury, death, and economic loss on the road. Driving performance decreases because of increased drowsiness. In several different applications, such as facial movement analysis driver blink detection an essential requirement that used. The extremely rapid rate, other hand, makes automatic challenging task. This research ...

Advancements in globalization have significantly seen a rise road travel. This has also led to increased car accidents and fatalities, which become global cause of concern. Driver's behavior, including drowsiness, contributes many the deaths. The main objective this study is develop system diminish mishaps caused by driver's drowsiness. Recently deep convolutional neural networks been used mult...

The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG a...