This page documents generic concepts about Point Cloud Detectors.
For specific documentation per Detector, see Preferences.

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 points as a selection of main point cloud file, or as a new point cloud file.