Working With Point Clouds and BIM


March 16, 2015 â”‚Nikunj Patel

 It is interesting how point cloud models of various buildings, sections of buildings and landscapes can be easily obtained by using sophisticated laser scanners. However, these point clouds cannot be used right away for Revit family creation or BIM. Expert intervention is always required in order to convert these point cloud models into surface models that can be used for BIM.

3D Laser scanners are used to measure millions of points across a building and to capture all the details, dimensions and demarcations. These point cloud models are given to 3D modelers as input data in order to develop building information models. So what is the role of a 3D modeler here?

Just trace over a Point Cloud – And you have BIM!  – Sounds easy!!

A lot is talked about scan to BIM, where the common perception seems to be that, the point cloud data is traced upon and TADA!!! A BIM ready model is there. However working with point cloud is much more than just tracing over existing models, and only a modeler or a BIM expert can tell you that.

This reminds me of a project I was working on, where our team received nearly 300+ scans in .pcg format. These scans included the architectural and structural details of every section of the building. Our team developed 3D models of the ‘as built’ structure with 10mmaccuracy and LOD 300 as requested by the client.

Working with Point Cloud and Scan to BIM challenges!!

Now, Point clouds can be highly complex, and working with these, requires experience and deft handling. However, the biggest challenge in our project was that the scanned data provided to us by the client, had several missing sections and a lot of inconsistencies. This will happen most of the times, and it depends on the acumen of BIM experts and engineers how they handle these inconsistencies.

Our engineers studied the point clouds and identified errors and missing parts. As the data volume of Point Cloud was high we had to divide the data into subsections and this required a lot of management and collaboration between the team. The missing data also had to be constructed using engineering assumptions; this was done with the help of existing scanned data and reference images provided by the client.

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