Abstract
Video surveillance has become the main tool due to its rich, intuitive and accurate information. However, with the large-scale construction of video surveillance systems all over the world, problems such as “useful information and clues cannot be found immediately with video big data” decrease detecting efficiency during crime prediction and public security governance. This paper concludes a novel architecture for next generation public security system, and the “front+back” pattern is adopted. Under the architecture, cloud computing technologies such as distributed storage and computing, data retrieval of huge and heterogeneous data are introduced, and multiple optimized strategies to enhance the utilization of resources and efficiency of tasks.
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Acknowledgements
This work was supported in part by the National Science and Technology Major Project under Grant 2013ZX01033002-003, in part by the National High Technology Research and Development Program of China (863 Program) under Grant 2013AA014601, in part by the National Science Foundation of China under Grant 61300202, 61300028, in part by the Project of the Ministry of Public Security under Grant 2014JSYJB009, in part by the China Postdoctoral Science Foundation under Grant 2014M560085, and in part by the Science Foundation of Shanghai under Grant 13ZR1452900.
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Xu, Z., Yan, Z., Mei, L., Zhang, H. (2016). The Big Data Analysis of the Next Generation Video Surveillance System for Public Security. In: Sugumaran, V., Yoon, V., Shaw, M. (eds) E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life. WEB 2015. Lecture Notes in Business Information Processing, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-319-45408-5_16
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DOI: https://doi.org/10.1007/978-3-319-45408-5_16
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