Pawlak的流图扩展视频监控系统

Karol Lisowski, A. Czyżewski
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引用次数: 3

摘要

Pawlak流图的思想适用于与决策算法或数据挖掘相关的各个领域的许多问题。该流程图也可用于视频监控系统。特别是在分布式多摄像头系统中,由于操作人员的感知能力有限,难以处理。在这样的系统中,需要实现自动视频分析。该分析的重要部分是跟踪单个摄像机内和摄像机视野之间的物体。除了物体的视觉特征和相机之间的时空依赖关系外,重新识别单个真实物体所需的元素之一是行为模型。流图经过一些修改,是一种合适的数据结构,其概念是基于粗糙集理论,作为行为模型包含在其中。此外,流图还可以用来预测给定物体的未来运动。本文综述了作者在视频监控系统中应用流程图的相关研究工作。给出了基于监督区域内物体路径的流图生成方法。此外,还讨论了一种基于流图构建概率树的方法,以及一种使流图适应摄像机网络拓扑变化的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pawlak's flow graph extensions for video surveillance systems
The idea of the Pawlak's flow graphs is applicable to many problems in various fields related to decision algorithms or data mining. The flow graphs can be used also in the video surveillance systems. Especially in distributed multi-camera systems which are problematic to be handled by human operators because of their limited perception. In such systems automated video analysis needs to be implemented. Important part of this analysis is tracking object within a single camera and between cameras' fields of vision. One of element needed to re-identify the single real object besides object's visual features and spatiotemporal dependencies between cameras is a behaviour model. The flow graph after some modifications, is a suitable data structure, which concept is based on the rough set theory, to contained as a behaviour model in it. Additionally, the flow graph can be used to predict the future movement of given object. In this paper a survey of authors research works related to employing flowgraphs in video surveillance systems is contained. The flow graph creation based on the paths of objects inside supervised area will presented. Moreover, a method of building a probability tree on the basis of the flow graph and a method for adapting the flowgraph to the changing topology of the camera network are also discussed.
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