pcl_openni_mls_smoothing - pcl_openni_mls_smoothing

       pcl_openni_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_openni_mls_smoothing 1.7.1                      May 2014                         PCL_OPENNI_MLS_SMOOTHING(1)

       usage: pcl_openni_mls_smoothing <device_id> <options>

       whereoptionsare:-search_radius  X  =  sphere  radius  to  be  used  for  finding the k-nearest neighbors used for fitting
       (default: 0)

       -sqr_gauss_param X = parameter used  for  the  distance  based  weighting  of  neighbors  (recommended  =
       search_radius^2) (default: 0)

       -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_openni_mls_smoothing - pcl_openni_mls_smoothing