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Big Data Oriented Novel Background Subtraction Algorithm for Urban Surveillance Systems

Big Data Oriented Novel Background Subtraction Algorithm for Urban Surveillance Systems
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摘要 Due to the tremendous volume of data generated by urban surveillance systems, big data oriented lowcomplexity automatic background subtraction techniques are in great demand. In this paper, we propose a novel automatic background subtraction algorithm for urban surveillance systems in which the computer can automatically renew an image as the new background image when no object is detected. This method is both simple and robust with respect to changes in light conditions. Due to the tremendous volume of data generated by urban surveillance systems, big data oriented lowcomplexity automatic background subtraction techniques are in great demand. In this paper, we propose a novel automatic background subtraction algorithm for urban surveillance systems in which the computer can automatically renew an image as the new background image when no object is detected. This method is both simple and robust with respect to changes in light conditions.
出处 《Big Data Mining and Analytics》 2018年第2期137-145,共9页 大数据挖掘与分析(英文)
基金 supported by the projects under the grants Nos. 2016B050502001 and 2015A050502003
关键词 BIG data BACKGROUND SUBTRACTION URBAN SURVEILLANCE systems big data background subtraction urban surveillance systems
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