Overcoming the Bottlenecks of Today's Dense Point Clouds

摘要

The most prominent bottleneck in the visualisation of today's dense point clouds is data size. Today, just one scan position generated by a decent 3D laser scanner is almost 1GB. In contemporary projects, scanned environments generally have huge dimensions (airport terminals, factories, etc.) and acquiring these spaces properly can require tens or even hundreds of scan positions so that almost always results in 'big data'. Most of the 3D point cloud software currently on the market cannot handle that amount of data. The second most important bottleneck is the quality of the visualisation, which is directly connected to the data size issue. In the era of high-quality rendering in games and movies, the visualisation quality of point clouds is not sufficient. Last but not least, another bottleneck is the interaction with 3D point clouds. Most of the time, users want to work in CAD software environments, but point cloud software generally offers limited integration with them. Although there are plug-ins for CAD software for easier integration, users still face a clash of different file types and hard-to-manage workflows. We overcome these bottlenecks with state-of-the-art algorithms and tools.