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http://dx.doi.org/10.56977/jicce.2022.20.3.226

Video Road Vehicle Detection and Tracking based on OpenCV  

Hou, Wei (Department of Electrical Engineering, Shaanxi Polytechnic Institute)
Wu, Zhenzhen (Weifang University of Science and Technology)
Jung, Hoekyung (Department of Computer Engineering, PaiChai University)
Publication Information
Journal of information and communication convergence engineering / v.20, no.3, 2022 , pp. 226-233 More about this Journal
Abstract
Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.
Keywords
Background model; CAMSHIFT algorithm; OpenCV; Static background; Vehicle tracking; Video surveillance;
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Times Cited By KSCI : 2  (Citation Analysis)
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