Classify noise points

Classify points using the Statistical Outliers Removal (SOR) methods first described in the PCL library and also implemented in CloudCompare (see references). For each point, it computes the mean distance to all its k-nearest neighbors. The points that are farther than the average distance plus a number of times (multiplier) the standard deviation are considered noise.

Usage

classify_with_sor(k = 8, m = 6, class = 18L)

Arguments

k

numeric. The number of neighbours

m

numeric. Multiplier. The maximum distance will be: ⁠avg distance + m * std deviation⁠

class

integer. The class to assign to the points that match the condition.

Value

This stage transforms the point cloud in the pipeline. It consequently returns nothing.