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The power of the Cloud to supercharge point cloud processing

You need to remember upload time to the server and costs for

server-side storage and bandwidth if you are looking at cloud server versus desktop. However most cloud storage is approximately equal to hard drives in terms of cost when you get into the specifics, and link speeds continue to grow in line with evolving technology. There is just an increase in data transmission time, and the cloud offers the undeniable advantage of global availability.

More interestingly, for certain projects, the cloud provides the ability to

take the processing of point cloud to a completely different stage.

Advanced point cloud processing software is able to concurrently register several scans, each operation being performed on your CPU on a separate thread.

Up to 18 cores, or 36 threads, will pack cutting-edge hard drives. But the cloud will allow you to indefinitely scale up this capability. Theoretically, this allows the opportunity to perform the ‘coarse registration’ of a project of any scale simultaneously, exponentially decreasing registration times.

With conventional hardware, it will often take longer with more scans to place the scans in order setting scan pairs). You will simply keep adding threads in the cloud.

The need for automated registration

It is possible to see the opportunities and advantages of cloud computing for the development and processing of point clouds, but they still need to be realized.

Manual measures in conventional registration software at each level of alignment are one issue with supercharging the processing of point clouds in the ‘cloud’. Accessing multi-thread processing is impractical especially when using targetless scans, since manual inputs and cross-checks need to be handled through that process.

This is evolving as well. Multi-stage vector analysis software, for instance, enables coarse registration to be separated into clearly defined phases.

Rotational alignment can be accomplished independently with point clouds compressed into unique ‘vector spheres’ and then allows quick 2D This can speed up conventional hardware processing by 40 percent -80 percent . More critically, it provides a robust method for registering targetless scans, enabling front-loading of manual inputs. Entry to ‘cloud-scaled’ multi-thread processing is a fact through this automation. Survey teams are able to process scan sets of almost any size in reasonably comparable amounts of time by combining this kind of processing software with cloud capabilities and wide bandwidth packages.

Looking to the future

The stumbling blocks to efficient point cloud formation have been point cloud processing and registration. Technology has always come down to this. For some time, the ability to align scans using natural features has been around, it has just never been sufficiently successful.

Advanced computing software such that of ScanX will be able to produce aligned datasets quicker and with less manual intervention by approaching scan alignment in three different phases and leveraging the scaling capabilities of the cloud. For projects that are still difficult to forecast, the reduced costs this provides provide efficiencies that will open up the use of point clouds and 3D surveys. The survey environment is shifting, and a big part of the complex change is the cloud.