Monitoring Driver’s Drowsiness Status at Night Based on Computer Vision

Drivers drowsiness and fatigue decreases the vehicle management skills of a driver. The operator driving vehicle in night has become a significant downside today. Driver in a drowsiness state is the one among the important reason of increasing amount of road accidents and death. Hence the drowsiness detection of driver is considering as most active research field. Many ways are created recently to detect the drowsiness of driver. Existing methods can be classified in three categories based on physiological measures, performance measures of vehicles and ocular measures. Few ways are intrusive and distract the driver from comfortable driving. Some of the methods need expensive sensors for information handling. Therefore, a low cost, real time system to detect the driver’s drowsiness is developed in this paper. In this proposed system, real time video of driver records using a digital camera. Using some image processing techniques, face of the driver is detected in each frame of video. Facial landmarks points on the driver’s face is localized using one shape predictor and calculating eye aspect ratio, mouth opening ratio, yawning frequency subsequently. Drowsiness is detected based on the values of these parameters. Adaptive thresholding method is used to set the thresholds. Machine learning algorithms were also implemented in an offline manner. Proposed system tested on the Face Dataset and also tested in real-time. The experimental results shows that the system is accurate and robust.