(Conference Paper) Driver's Illegal Driving Behavior Detection with SSD Approach
Tao Yang ¹, Jin Yang ², Jicheng Meng 孟继成 ²
¹ Shanghai Huawei Technology Co., Ltd, Shanghai, China
中国 上海 上海华为技术有限公司
² School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
中国 成都 中国电子科技大学自动化工程学院
2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML), 2021-08-26

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.
Driver's Illegal Driving Behavior Detection with SSD Approach_1
Driver's Illegal Driving Behavior Detection with SSD Approach_2
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