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Photogrammetric point cloud compression for tactical networks

机译:战术网络的摄影测量点云压缩

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We report progress toward the development of a compression schema suitable for use in the Army's Common Operating Environment (COE) tactical network. The COE facilitates the dissemination of information across all Warfighter echelons through the establishment of data standards and networking methods that coordinate the readout and control of a multitude of sensors in a common operating environment. When integrated with a robust geospatial mapping functionality, the COE enables force tracking, remote surveillance, and heightened situational awareness to Soldiers at the tactical level. Our work establishes a point cloud compression algorithm through image-based deconstruction and photogrammetric reconstruction of three-dimensional (3D) data that is suitable for dissimination within the COE. An open source visualization toolkit was used to deconstruct 3D point cloud models based on ground mobile light detection and ranging (LiDAR) into a series of images and associated metadata that can be easily transmitted on a tactical network. Stereo photogrammetric reconstruction is then conducted on the received image stream to reveal the transmitted 3D model. The reported method boasts nominal compression ratios typically on the order of 250 while retaining tactical information and accurate georegistration. Our work advances the scope of persistent intelligence, surveillance, and reconnaissance through the development of 3D visualization and data compression techniques relevant to the tactical operations environment.
机译:我们向开发适用于军队的共同操作环境(COE)战术网络的压缩模式的进展。 COE通过建立数据标准和网络方法,促进传播所有战士梯队的信息,并在共同的操作环境中协调读数和控制众多传感器的数据标准和网络。当与强大的地理空间映射功能集成时,COE能够在战术层面上强制跟踪,远程监测和向士兵提高态势意识。我们的工作通过基于图像的解构和摄影测量的三维(3D)数据的重建建立了一个点云压缩算法,该数据适用于COE内的差异。开源可视化工具包用于将基于地面移动光检测和范围(LIDAR)解构为一系列图像和相关的元数据来解构基于地面移动光检测和范围(LIDAR),这些图像可以在战术网络上容易地传输。然后在接收的图像流上进行立体摄影测量重建以显示发送的3D模型。报告的方法通常拥有标称压缩比,通常大约为250,同时保留战术信息和准确的地理学。我们的工作通过开发与战术运营环境相关的3D可视化和数据压缩技术来推进持续智力,监控和侦察的范围。

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