In this paper we present a system for progressive encoding, storage, transmission, and web based visualization of large point cloud datasets. Point cloud data is typically recorded on-set during a film production, and is later used to assist with various stages of the post-production process. The remote visualization of this data (on or off-set, either via desktop or mobile device) can be difficult, as the volume of data can take a long time to be transferred, and can easily overwhelm the memory ...
In this paper we present a system for progressive encoding, storage, transmission, and web based visualization of large point cloud datasets. Point cloud data is typically recorded on-set during a film production, and is later used to assist with various stages of the post-production process. The remote visualization of this data (on or off-set, either via desktop or mobile device) can be difficult, as the volume of data can take a long time to be transferred, and can easily overwhelm the memory of a typical 3D web or mobile client. Yet web-based visualization of this data opens up many possibilities for remote and collaborative workflow models. In order to facilitate this workflow, we present a system to progressively transfer point cloud data to a WebGL based client, updating the visualisation as more information is downloaded and maintaining a coherent structure at lower resolutions. Existing work on progressive transfer of 3D assets has focused on well-formed triangle meshes, and thus is unsuitable for use with raw LIDAR data. Our work addresses this challenge directly, and as such the principal contribution is that it is the first published method of progressive visualization of point cloud data via the web.
+
