REALITY CAPTURE KNOWLEDGE · POINT CLOUDS
A point cloud is useful when it is correctly registered, has the appropriate point density, and contains the information required for the intended project outcome.
A visually impressive or extremely dense point cloud is not necessarily better. If the information required by the project can be reliably extracted from a smaller dataset, additional points may only increase file size and make processing, transfer and downstream use more difficult.
The intended deliverable matters too. A point cloud prepared for detailed mesh generation may require a very different level of density from one used for measurements, CAD documentation or integration into another platform.
For me, the most important question is therefore not how much data the point cloud contains, but whether it contains the right data for what needs to happen next.
A useful point cloud is not the one that looks impressive. It is the one that is prepared for the purpose of the project.
SEE IT IN PRACTICE
In a digital cemetery mapping project, the completed point clouds contained more data than the target platform could efficiently process. I reduced the point density while preserving the geometry required for the final application.
ABOUT THIS KNOWLEDGE SERIES
Reality Capture Knowledge is where I share short, practical answers to questions that come up across reality capture, point cloud processing and geospatial workflows.
The answers are based on more than 15 years of hands-on experience working with spatial data, field acquisition and point cloud processing.
Roland Kriston
Independent Reality Capture & Geospatial Specialist