Driver Safety Approach Using Efficient Image Processing Algorithms for Driver Distraction Detection and Alerting

摘要

Currently, due to different reasons, the road accidents are increasing. Road accidents are prone to number human deaths. There are different reasons which lead to road accidents, but drivers fatigue or distraction is main threat in major accidental cases. Therefore, recently various methods are explained by many authors for untimely identification of driver sleepiness in the manner of prohibiting mischance on road. In this paper, we are presenting the novel approach called hybrid method in which automatic care of driver safety and hospitality management services. Our approach aims at determining first if a driver is distracted or not based yawing, eye position, head position, mouth position etc., second if driver is detected as distracted instance alarming will perform on both driver side and near hospital services in order to be available in case of accident happen. Based on computer vision techniques, we propose four different modules for features extraction, focusing on arm position, face orientation, facial expression and eye behaviour, and then, the outputs of all these phases combined together and feed to the classifier feed-forward neural network (FFNN) for alarming the distraction detection and type of distraction. The outcome of this paper is efficient driver safety approach by considering the RGB-D sensor and image processing algorithms.