Early warning system for drivers’ phone usage with deep learning network

被引:0
|
作者
J. H. Jixu Hou
Xiaofeng Xie
Qian Cai
Zhengjie Deng
Houqun Yang
Hongnian Huang
Xun Wang
Lei Feng
Yizhen Wang
机构
[1] Hainan Normal University,College of Physics & Electronic Engineering
[2] Hainan University,College of Mechanical & Electrical Engineering
[3] University of New Mexico,Department of Mathematics and Statistics
[4] Hainan Blue Dot Computer Network Engineering Co.,undefined
[5] Ltd,undefined
关键词
Deep learning; Driving safety; Object detection; Computer vision; Machine learning;
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学科分类号
摘要
Dangerous driving, e.g., using mobile phone while driving, can result in serious traffic problem and threaten to safety. To efficiently alleviate such problem, in this paper, we design an intelligent monitoring system to detect the dangerous behavior while driving. The monitoring system is combined by a designed target detection algorithm, camera, terminal server and voice reminder. An efficiently deep learning model, namely Mobilenet combined with single shot multi-box detector (Mobilenet-SSD), was applied to identify the behavior of driver. To evaluate the performance of proposed system, a dangerous driving dataset,consisting of 6796 images, was constructed. The experimental results show that the proposed system can achieve the accuracy of 99%, and could be used for real-time monitoring of the drivers’ status.
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