Driver’s Illegal Driving Behavior Detection with SSD Approach
Tao Yang, Jin Yang, Jicheng Meng · 2021
In this paper, an advanced detection approach of illegal driving behavior is proposed using Single Shot MultiBox Detector (SSD) based on deep learning. The detection of driver’s illegal driving behavior includes cellphone usage, cigarette smoke and no fastening seat belt. Doing this can greatly reduce the occurrence of traffic accidents. In order to validate the detection effect using SSD on small target objects, such as cigarette in complex environment, we use not only three online databases, i.e. HMDB human motion database, WIDER FACE Database, Hollywood-2 Database, but also a real database collected by ourselves. The experimental results show that the SSD approach has a better performance than the Faster Regions with Convolutional Neural Network (Faster R-CNN) for detecting driver’s illegal driving behavior.