Using the clusterization tool
Once the parameters are set and the area to be analyzed has been considered, it is possible to begin the detection by clicking on “Start”. The clusterization tool will mark the points to be analyzed (influenced by any segmentation in the point cloud and the downsample size), regroup them into clusters following the detection parameters and finally give each detected cluster a set of dimensions.
Once the clusters are detected, a list of clusters will be populated. The clusters are assigned a unique name and a random color. Each cluster also contains 3 attributes: length, width and height. These attributes determine the bounding box for that specific cluster.
A number of tools are available for the management of these clusters - many of them are shown in the cluster toolbar. The clusters are displayed in a list and may be expanded to show their specific attributes. A few icons are available to delete and identify clusters, as well as draw and erase cluster points. Drawing the points from the cluster allows the user to visualize points contained within a specific cluster. There is also an option to add selected clusters to a library where the clusters can be stored for later use. A description of each icon in the toolbar is available here:
| Icon | Description |
|---|---|
| Deletes all selected clusters from the list |
| Identifies a cluster by picking it on screen |
| Draws the points for the selected clusters |
| Erases the points for the selected clusters |
| Adds selected clusters to the library |
| Renames selected clusters with the specified text with an incremental suffix |
| This field allows the user to classify selected clusters to a specified class |
By right-clicking on a cluster in the list, there is a contextual menu which offers additional options.
Copy dimensions for filter will duplicate the size of the current cluster in the current cluster category as size values, so that if the filter is activated.
Zoom to cluster will recenter the main view on the selected cluster.
It is possible to draw and erase points of the cluster as well as delete or restore points from the point cloud. There is a difference to be made between deleting and erasing: erasing points will simply erase drawn points from the screen (if they had been drawn previously) whereas deleting points will mark them as deleted and will no longer be visible or be considered for future calculations. Deleting the cluster will simply delete the definition of the cluster.
