Expressway All-weather Illegal Parking Detection Algorithm Based on Vehicle Tracking
Effectively detecting illegal parking vehicles is particularly challenging in complex daytime and nighttime expressway environments.Focusing on solving this problem,this study proposed an all-weather illegal parking detection algorithm for daytime and nighttime environments,targeting the complex factors,e.g.,high traffic volume,high density,and lighting variations in expressway surveillance videos.By constructing the expressway vehicle image dataset,combining the global attention mechanism and target detection model,and adding data enhancement strategies for nighttime images,the lack of high-quality vehicle images in these complex environments was overcome.The vehicle detection accuracy was significantly improved.The Hungarian algorithm was used to predict the vehicle location.The update was realized according to the high and low score matching frames.Simultaneously,the feature matching model was used to extract the vehicle features,and further track the vehicle to realize the determination on suspected illegal parking vehicle.The result indicates that it works best on the constructed test dataset of surveillance videos with and without parking violation.The algorithm accuracy and recall rate reach 97.32%and 96.57%,which verifies the superiority and feasibility of the algorithm in practical application.The innovation of all-weather illegal parking detection based on vehicle tracking is to propose an all-weather illegal parking detection algorithm for expressway surveillance video,achieving good detection accuracy and performance in the test.It can accurately detect the illegal parking at night,and has been successfully applied to the traffic monitoring cloud platform.It provides strong support for early warning and rapid rescue of traffic accidents,effectively ensuring the traffic safety and improving the traffic management level.
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