Point cloud web renderer

Point clouds are an efficient way to represent 3D models. A significant amount of interest has emerged for this type of visual data, due to the recent advances in acquisition and compression technologies. Yet, rendering solutions that allow manual adjustments in a per-point basis are required to display high-quality point cloud models.

In the framework of [1], a prototype implementation of an open source web-based point cloud renderer was developed. The renderer is built on top of the well-established three.js library, ensuring compatibility across different devices and operating systems. The renderer supports visualization of point clouds with real-time interaction, while viewing conditions can be configured. The user is able to choose between either an adaptive, or a fixed splat size rendering mode in order to display the models. The renderer supports both PLY and PCD point cloud file formats. The current settings have been optimized for voxelized contents, without this limiting its usage, since any point cloud can be displayed independently of its geometric structure (i.e., regular or irregular).

In particular, the software consists of three applications: (a) a simple point cloud viewer through which a user can visualize and interact with single models, (b) a customisable subjective quality assessment testbed, and (c) a view grabber which can be used to exports views of the model given the camera parameters.

Example of the subjective quality assessment testbed.
The depicted point cloud is part of the M-PCCD dataset (original model source: link, creator: Megan Bystricky, license: CC Attribution)


The software can be downloaded from the following GitHub repository.

Please instruct the README files for further information on the structure and the usage.

You may also read [1] for more details about the software and the experiment that was used.

Conditions of use

If you wish to use any of the provided material in your research, we kindly ask you to cite [1].


  1. Alexiou, E., Viola, I., Borges, T., Fonseca, T., De Queiroz, R., & Ebrahimi, T. (2019). A comprehensive study of the rate-distortion performance in MPEG point cloud compression. APSIPA Transactions on Signal and Information Processing, 8, E27. doi: 10.1017/ATSIP.2019.20