Web-based visualisation of on-set point cloud data

Abstract

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.

Multimodal Visual Data Registration for Web-Based Visualization in Media Production

“…In our preliminary research in this field, we presented a similar progressive visualisation of large point cloud data, where the data is pre-processed, in an off-line step, into a hierarchical data structure [30]. Web-based rendering of very large point-clouds is tackled by [31], which uses a level-ofdetail approach to ensure the number of points rendered does not saturate the browser application.…”

“…Web-based rendering of very large point-clouds is tackled by [31], which uses a level-ofdetail approach to ensure the number of points rendered does not saturate the browser application. Only a single point cloud visualisation in a web environment was dealt with in [30], but we present algorithms and interface for the simultaneous visualisation of multiple point clouds, intertwined with 2D image and video data in a single web-based visualisation platform in this paper. The results compare favourably for transmission times for the different but related problem of mesh visualisation in [32].…”

Big Data Analysis for Media Production

“…In order to visualize the point cloud correctly, we use a progressive transfer mechanism based on our previous work [130], [131]. To begin with, the point data is linearly normalized to its axis aligned bounding box, to 16-bit precision.…”

IMPART: Big media data processing and analysis for film production

“…One of the major challenges of web-based 3D applications is related to the transmission of data from the server to the remote client. Our work is based on solutions for the progressive download of very large point-cloud data [11] generated within the project, which are comparable in efficiency to the state-of-the art proposed for the more widely studied progressive download of meshes (see [12], for instance).…”