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pcl_mls_smoothing - pcl_mls_smoothing


Syntax is: pcl_mls_smoothing input.pcd output.pcd <options>

Moving Least Squares smoothing of a point cloud. For more information, use: pcl_mls_smoothing -h

where options are:

-radius X= sphere radius to be used for finding the k-nearest neighbors used for fitting (default: 0.000000)

-sqr_gauss_param X = parameter used for the distance based weighting of neighbors (recommended = search_radius^2) (default: 0.000000)

-use_polynomial_fit X = decides whether the surface and normal are approximated using a polynomial or only via tangent estimation (default: 0)

-polynomial_order X = order of the polynomial to be fit (implicitly, use_polynomial_fit = 1) (default: 2)


pcl_mls_smoothing is part of Point Cloud Library (PCL) -

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing.

This manual page was written by Leopold Palomo-Avellaneda <> with the help of help2man tool and some handmade arrangement for the Debian project (and may be used by others).

May 2014 pcl_mls_smoothing 1.7.1