Point cloud and image 3D visualisation platform based on web

Xin Li, Ning Wang, Kunlin Song, Kun Xu and Jiancheng Huang

International Journal of Data Science, 2022, vol. 7, issue 3, 229-241

Abstract: Nowadays, the point cloud data collected by light detection and ranging (LiDAR) and image data collected by camera are increasing. How to effectively manage and visualise such massive data has always been a research hotspot for scholars. Meanwhile, the development of web technology provides a new and efficient way for the visualisation of these data. Therefore, we propose a web-based 3D visualisation method of point cloud and images. In this platform, least squares is used to achieve accurate matching of the feature of heterogeneous data. The Potree and Django framework is applied to realise 3D visualisation of web endpoint cloud images, as well as basic measurement, annotation, file output, etc. This platform can realise the online quick browsing of point cloud and image data. The visualisation smoothness of point cloud and images on the web end has been significantly improved.

Keywords: 3D visualisation; point cloud; image; web; Potree. (search for similar items in EconPapers)
Date: 2022
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