Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8–10, 2019, Proceedings

Research Article

Video Monitoring System Application to Urban Traffic Intersection

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  • @INPROCEEDINGS{10.1007/978-3-030-32216-8_32,
        author={Jin-ping Sun and Lei Chen and Rong Bao and Dan Li and Dai-hong Jiang},
        title={Video Monitoring System Application to Urban Traffic Intersection},
        proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings},
        proceedings_a={SIMUTOOLS},
        year={2019},
        month={10},
        keywords={Video monitoring Urban traffic Gauss mixture model Background subtraction method Motion detection},
        doi={10.1007/978-3-030-32216-8_32}
    }
    
  • Jin-ping Sun
    Lei Chen
    Rong Bao
    Dan Li
    Dai-hong Jiang
    Year: 2019
    Video Monitoring System Application to Urban Traffic Intersection
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-32216-8_32
Jin-ping Sun1, Lei Chen1,*, Rong Bao1, Dan Li1, Dai-hong Jiang1
  • 1: Xuzhou University of Technology
*Contact email: chenlei@xzit.edu.cn

Abstract

Intelligent video surveillance technology can reduce the burden of workers and improve the efficiency of surveillance. A project of the video monitoring system with moving target detection function has been realized and applied to the urban traffic system. The background will have weak or obvious changes as time goes on, such as, the illumination change, the environmental effect, the movement of the background, and so on. If we always use the original background model, it will cause large error. Fixed threshold is not suitable for illumination change in the environment. An improved adaptive on-line Gauss mixture model is used to acquire the background model, and the background subtraction method is used to match the moving objects. Then, the motion detection function was realized in a specific region. If there are abnormal moving targets in a specific area, the linkage alarm function will be activated and handled by manual intervention. This algorithm can effectively reduce the error probability of target recognition caused by environmental changes, and provide strong technical support for real-time monitoring of traffic abnormalities.