文章基本信息

标题：Intelligent Analysis for Georeferenced Video Using Context-Based Random Graphs
本地全文：下载
作者：Jiangfan Feng ; Hu Song
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2013
卷号：2013
DOI：10.1155/2013/158569
出版社：Hindawi Publishing Corporation
摘要：Video sensor networks are formed by the joining of heterogeneous sensor nodes, which is frequently reported as video of communication functionally bound to geographical locations. Decomposition of georeferenced video stream presents the expression of video from spatial feature set. Although it has been studied extensively, spatial relations underlying the scenario are not well understood, which are important to understand the semantics of georeferenced video and behavior of elements. Here we propose a method of mapping georeferenced video sequences for geographical scenes and use contextual random graphs to investigate semantic knowledge of georeferenced video, leading to correlation analysis of the target motion elements in the georeferenced video stream. We have used the connections of motion elements, both the correlation and continuity, to present a dynamic structure in time series that reveals clues to the event development of the video stream. Furthermore, we have provided a method for the effective integration of semantic and campaign information. Ultimately, the experimental results show that the provided method offers a better description of georeferenced video elements that cannot be achieved with existing schemes. In addition, it offers a new way of thinking for the semantic description of the georeferenced video scenarios.