pcl_mls_smoothing - pcl_mls_smoothing

       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).

pcl_mls_smoothing 1.7.1                             May 2014                                PCL_MLS_SMOOTHING(1)

       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 - pcl_mls_smoothing