基于操作日志的监控人员行为分析技术

Chuandong Lv, Yang Yang, Qiyue Sun, Bin Zhou, Peng Xu
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引用次数: 0

摘要

监控人员打开监控视频会产生大量的操作日志,本文在这些操作日志的基础上,利用数据挖掘、机器学习等方法对监控人员的行为可视化、自动异常检测和异常行为分析进行了研究。通过以上方法和研究,本文可以从操作日志中挖掘出有价值的信息,帮助监控人员在工作中实现行为可视化,发现异常行为问题,从而有效避免因监控人员操作不当导致安全事件的发生,降低监控过程中的潜在风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surveillance Personnel Behavior Analysis Technology based on Operation Log
A large number of operation logs will be generated when surveillance personnel open surveillance video and based on these operation logs, this paper studies the behavior visualization, automatic anomaly detection and abnormal behavior analysis of the surveillance personnel by using data mining, machine learning and other methods. Using the above methods and research, this paper can mine valuable information from the operation log, which can help the surveillance personnel to realize behavior visualization and find abnormal behavior problems during the work, thus effectively avoid the occurrence of security incidents caused by improper operation of the surveillance personnel, and reduce the potential risks in the surveillance process.
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