Abstract
With the rapid development of society, the improvement of material level and the current situation of the large-scale population flow in China, the awareness of security is becoming more and more important in people’s life. With the rapid development of image processing and computer vision technology, people try to analyze, process and understand the collected video image automatically without human intervention. The intelligent video monitoring system collects video signals of interested objects in a dynamic scene through a camera, and processes and analyzes image information by a computer. Only by establishing a reasonable and effective urban video monitoring management system can government departments find out problems in the first time. The traditional highway monitoring and commanding traffic scheduling system based on GIS, which can obtain road traffic information and conduct traffic scheduling by remote sensing, has the disadvantage of poor effect on traffic scheduling. In this paper, real-time communication technology and computer vision acquisition technology are used to build a city monitoring system. The experimental results show that this method has strong timeliness and good monitoring effect. Compared with the state-of-the-art methodologies, the proposed framework is efficient and accurate.
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11 April 2024
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s11063-024-11603-2
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Acknowledgements
Project funded by China Postdoctoral Science Foundation. Project funded by National Key R&D Program of China (No. 2017YFB0503604; No. 2017YFB0503801). Project funded by Electronic fence system project. Project funded by the Project (017/2018/A) of FDCT. Project funded by the Project of Macao Foundation.
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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11063-024-11603-2
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Li, D., Qin, B., Liu, W. et al. RETRACTED ARTICLE: A City Monitoring System Based on Real-Time Communication Interaction Module and Intelligent Visual Information Collection System. Neural Process Lett 53, 2501–2517 (2021). https://doi.org/10.1007/s11063-020-10325-5
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DOI: https://doi.org/10.1007/s11063-020-10325-5