NAME

       pcl_mls_smoothing - pcl_mls_smoothing

DESCRIPTION

       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)

AUTHOR

       pcl_mls_smoothing is part of Point Cloud Library (PCL) - www.pointclouds.org

       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 <leo@alaxarxa.net> with the help
       of help2man tool and some handmade arrangement for the Debian project (and may be used  by
       others).