normals Compute normal vectors of activated points. ------------------------------------------------------------------------------ DESCRIPTION/NOTES * The components of the normal vectors are saved into the attribute structure of the point cloud: * x component of n -> obj.A.nx * y component of n -> obj.A.ny * z component of n -> obj.A.nz * Additionally a roughness value corresponding to the standard deviation of the residuals is saved as roughness attribute: * roughness -> obj.A.roughness ------------------------------------------------------------------------------ INPUT 1 [searchRadius] Search radius for normal estimation. 2 ['MinNoNeighbours', minNoNeighbours] Minimum number of nearest neighbours. If less than minNoNeighbours neighbours are found within the specified search radius, the normal vector components are set to NaN. 3 ['MaxNoNeighbours', maxNoNeighbours] Maximum number of nearest neighbours to use for normal vector estimation. ------------------------------------------------------------------------------ OUTPUT 1 [obj] Updated object. ------------------------------------------------------------------------------ EXAMPLES 1 Compute normals for a subset of points and visualize them. pc = pointCloud('Lion.xyz'); pc.select('UniformSampling', 3); pc.normals(1); pc.plot('Color', 'r', 'MarkerSize', 5); pc.plotNormals('Color', 'y', 'Scale', 5); ------------------------------------------------------------------------------ philipp.glira@gmail.com ------------------------------------------------------------------------------