Potree: Rendering Large Point Clouds in Web Browsers
Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria, (September 2016)Abstract
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.