This page documents generic concepts about Point Cloud Detectors.

Use the tooltip on the parameters to know more about the use and impact of the parameter.
For additional documentation on adjusting parameters, see Use cases adjusting Parameters for Detectors.

Detectors: semi-automated and fully automated measurements. Preferences of Detectors define set of user parameters which can be changed depending on quality of input data and requirements for the output.
For semi-automated measurements changing of the parameters is applied immediately while for fully automated detectors values from Preferences are read only on new feature extraction Project creation.

• Reset parameters back to default.
• Save the parameters of the selected detector into an *.xml file.
• Open to load an existing *.xml containing preferences for the selected Detector.

These parameters impact how detection algorithms work.

Restrict or filter specified point cloud classes to be used for feature detection.

• Integer values, comma separated.
• If no class is specified all classes are used, no class is excluded.

These parameters impact only the final presentation of detected results.

A moving average algorithm can be used to smooth line features. The average of the 4 neighboring points and the current position are used to calculate an updated position of a point or vertex. We allow 6 levels of smoothing, which corresponds to how many times the moving average is used. Level 0 means no smoothing is done, level 5 means the line points are moved 5 times.

Export the feature point cloud as a selection linked to the source point cloud resource file, or as a new point cloud resource file.

Significant time is required to create point cloud selection. Point cloud file and derived vector data creation (e.g. outline on ground) is only possible if selection is created.