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.
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Acknowledgements
This work is partly supported by the Natural Science Foundation of Jiangsu Province of China (No. BK20161165), the Key Laboratory of Intelligent Industrial Control Technology of Jiangsu Province Research Project (JSKLIIC201705), Xuzhou Science and Technology Plan Projects (KC18011, KC16SH010, KC17072), Ministry of Housing and Urban-Rural Development Science and Technology Planning Project (2016-R2-060).
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Sun, Jp., Chen, L., Bao, R., Li, D., Jiang, Dh. (2019). Video Monitoring System Application to Urban Traffic Intersection. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_32
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DOI: https://doi.org/10.1007/978-3-030-32216-8_32
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