大型城市视觉重构的地理空间管理与利用

Clemens Arth, Jonathan Ventura, D. Schmalstieg
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引用次数: 1

摘要

在这项工作中,我们描述了我们的方法来有效地创建,处理和组织大规模的城市环境的运动结构重建。为了获取大量数据,我们使用了一个Point Grey Ladybug 3全方位相机和一个带有差分GPS传感器的定制背包系统。稀疏点云重建是在离线过程中生成并与世界对齐的。最后,所有数据都存储在地理空间数据库中。我们整合了来自多个众包数据库的额外数据,例如OpenStreetMap的地图或Flickr或Instagram的图像。我们讨论了我们的系统如何在增强现实领域的潜在应用场景中使用。
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Geospatial Management and Utilization of Large-Scale Urban Visual Reconstructions
In this work we describe our approach to efficiently create, handle and organize large-scale Structure-from-Motion reconstructions of urban environments. For acquiring vast amounts of data, we use a Point Grey Ladybug 3 omni directional camera and a custom backpack system with a differential GPS sensor. Sparse point cloud reconstructions are generated and aligned with respect to the world in an offline process. Finally, all the data is stored in a geospatial database. We incorporate additional data from multiple crowd-sourced databases, such as maps from OpenStreetMap or images from Flickr or Instagram. We discuss how our system could be used in potential application scenarios from the area of Augmented Reality.
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