变电站环境监控视频异常模式的识别方法

随着变电站自动化程度的提高,视频监控系统在变电站得到广泛应用,为了提高监控的智能化水平,及时发现异常,提出一种识别无人值守变电站环境监控视频中异常模式的方法。对变电站环境监控中的运动目标进行分类(涉及到人、动物、普通火焰(红黄颜色火焰)、白色火焰等),并对行人进行跟踪,描绘其运行轨迹。针对待分类目标提取多种特征,基于混淆矩阵产生层次化分类器结构,以支持向量机(SVM)作为基本的两类分类器。对多段视频数据进行实验,实验结果表明提出的方法能够较好地实现人、动物、火焰的分类,并跟踪行人,排除干扰物(白炽灯)的影响,为实现无人值守变电站防火防盗提供必要的条件。

A Recognition Method of Abnormal Patterns for Video Surveillance in Substation Environment

With the improvement of substation automatic level,video surveillance systems are widely used in substations.In order to improve the intelligent level of monitoring and timely detect abnormalities,an identification method of abnormal patterns of surveillance video in unmanned substation environment is proposed.Object classification is implemented in substation environment video surveillance(related to people,animals,ordinary flames(red and yellow flames),white flames,and so on).Then people are tracked and t...