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VISUALIZING DISTRIBUTED DYNAMIC GEOSPATIAL INFORMATION IN GOOGLE EARTH

机译:可视化Google地球中的分布式动态地理空间信息

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The emergence of Google Earth (GE) as an integrative platform for the visualization of geolocated information is presenting the geospatial community with unique application opportunities and corresponding scientific challenges. In this paper we discuss the extension of GE to function as a four-dimensional (x,y,z,t) virtual spatiotemporal environment through the overlay in it of georectified video feeds, and feeds from geosensor networks deployed in an area of interest. We have created a Virtual model of our University Campus, exported it to GE, and use it to visualize diverse feeds from sensors distributed in our campus. In the paper we present the architecture of a prototype system that uses GE to visualize such sensor feeds. The system allows us to visualize locations and temporal stamps for our datasets, thus enabling a user to select feeds of a specific type for a specific location and time (e.g. video of a building corner at 2:15 an text feeds from a neighboring spot at 2:20). Selected datasets can then be overlaid in GE for visual inspection. In particular we emphasize in particular on issues related to video feeds. We present our approaches to register feeds captured by surveillance cameras located on top of buildings, and video feeds captured by mobile phone cameras. We also discuss the visualization in GE of information extracted from such video feeds (e.g. trajectories of individuals tracked in video). This hierarchical navigation through information presents unique opportunities for visual exploration of geospatial datasets. In our paper and presentation we present theoretical problems and demo our prototype.
机译:谷歌地球(GE)的出现作为地理位理信息可视化的一体化平台,呈现出地理空间界,具有独特的应用机会和相应的科学挑战。在本文中,我们讨论GE的扩展通过覆盖在地球连接视频馈送中的覆盖层,从覆盖物中覆盖,并从部署在感兴趣区域中的地磁传感器网络的馈送。我们创建了大学校园的虚拟模型,将其导出到GE,并使用它来从校园中分布的传感器可视化不同的饲料。在论文中,我们介绍了使用GE以可视化此类传感器馈送的原型系统的体系结构。该系统允许我们对我们的数据集进行可视化位置和时间戳,从而使用户能够为特定位置和时间选择特定类型的馈送(例如,在2:15在邻近斑点的文本馈送中2:20)。然后可以在GE中覆盖所选数据集以进行视觉检查。特别是我们特别强调关于与视频源相关的问题。我们介绍我们的方法来注册由位于建筑物顶部的监控摄像机捕获的饲料,以及手机摄像机捕获的视频饲料。我们还讨论了从这些视频馈送中提取的信息的GE中的可视化(例如,在视频中追踪的个人轨迹)。通过信息的分层导航为地理空间数据集的视觉探索提供了独特的机会。在我们的论文和演示文稿中,我们呈现了理论上的问题和演示我们的原型。

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