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http://dx.doi.org/10.6109/jkiice.2021.25.8.1026

Deep Learning Image Processing Technology for Vehicle Occupancy Detection  

Jang, SungJin (Department of Computer Engineering, Dong-Eui University)
Jang, JongWook (Department of Computer Engineering, Dong-Eui University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.8, 2021 , pp. 1026-1031 More about this Journal
Abstract
With the development of global automotive technology and the expansion of market size, demand for vehicles is increasing, which is leading to a decrease in the number of passengers on the road and an increase in the number of vehicles on the road. This causes traffic jams, and in order to solve these problems, the number of illegal vehicles continues to increase. Various technologies are being studied to crack down on these illegal activities. Previously developed systems use trigger equipment to recognize vehicles and photograph vehicles using infrared cameras to detect the number of passengers on board. In this paper, we propose a vehicle occupant detection system with deep learning model techniques without exploiting existing system-applied trigger equipment. The proposed technique proposes a system to detect vehicles by establishing triggers within images and to apply deep learning object recognition models to detect real-time boarding personnel.
Keywords
Object detection; HOV(High-occupancy vehicle) lane; Deep learning; Vehicle occupant detection;
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