基于贝叶斯网络的群体性事件智能视频分析与判定技术

为提高群体性事件智能视频监控的可靠性,提出在传统图像处理算法实现目标检测和特征提取的基础上,采用贝叶斯网络进一步对事件特征进行分析,重点介绍人群聚集事件判定贝叶斯网络建模、参数设置和推理等关键过程,并以具体的实例进行验证。结果表明:该方法具有建模简单、对智能视频分析算法依赖性低、鲁棒性和移植性强等特点,对建立可靠的智能视频监控系统具有参考价值。

The Intelligent Video Analysis and Determination Technology Based on Bayesian Network and Used for Group Events

In order to improve the reliability of the intelligent video surveillance system used for group events, introduces a method adopting Bayesian network to analyze the more event features, based on using the image processing algorithm to realize target detection and feature extract. It focuses on the key procedure of the group events judgment Bayesian network including modeling, parameter setting and reasoning, and validated it with specific examples. The results show the method has the advantages of modeling simply, relying on the intelligent video analysis algorithms lowly, and high reliability and portability. It has reference value for building reliable intelligent video surveillance system.