本文为奥地利维也纳科技大学（作者：Markus Schuetz）的毕业论文，共92页。

本文介绍了一种基于Web的大点云渲染器Potree。它允许用户在标准Web浏览器中实时查看具有数十亿个点的数据集，这些点来自激光雷达或摄影测量等。Web浏览器中点云可视化的一个主要优点是，它允许用户与客户机或公众共享其数据集，而无需安装第三方应用程序并提前传输大量数据。重点放在大型点云和各种测量工具上，还允许用户使用Potree来查看、分析和验证原始点云数据，而无需花费存在大量时间和潜在代价的网格化步骤。在Web浏览器中，无需预先加载大量数据即可实现数十亿个点的流式处理和呈现，这是通过一种分层结构实现的，该结构以不同分辨率存储原始数据的子样本。低分辨率数据存储在根节点中，随着每一级别的增加，分辨率逐渐增加。该结构允许Potree剔除视图平截体之外的点云区域，并以较低的细节级别呈现遥远的区域。其结果是一个开源的点云查看器，它能够在Web浏览器中实时呈现高达5970亿点的点云数据集，压缩后大约1.6TB。

This thesis introduces Potree, a web-based renderer for large point clouds. It allows users to view data sets with billions of points, from sources such as LIDAR or photogrammetry, in real time in standard web browsers. One of the main advantages of point cloud visualization in web browser is that it allows users to share their data sets with clients or the public without the need to install third-party applications and transfer huge amounts of data in advance. The focus on large point clouds, and a variety of measuring tools, also allows users to use Potree to look at, analyze and validate raw point cloud data, without the need for a time-intensive and potentially costly meshing step. The streaming and rendering of billions of points in web browsers, without the need to load large amounts of data in advance, is achieved with a hierarchical structure that stores subsamples of the original data at different resolutions. A low resolution is stored in the root node and with each level, the resolution gradually increases. The structure allows Potree to cull regions of the point cloud that are outside the view frustum, and to render distant regions at a lower level of detail. The result is an open source point cloud viewer, which was able to render point cloud data sets of up to 597 billion points, roughly 1.6 terabytes after compression, in real time in a web browser.

1 引言

2 本文相关工作

3 数据结构

4 点云渲染

5 具体实现及相关特征

6 结果

7 结论与未来研究展望 

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