CloudCompare forum

Hi,

I would advise you to certain issue. I need to make an inventory of road using point clouds aquired by my drone. To processing my data I have to remove noisy scattered data points and get smoothed set of points in order to prepare proper point cloud to further process. As the result I need to reconstruct surface that is the best adjusted and approximated to the real road surface.

I have read about Moving Least Squares (MLS) surface reconstruction. It looks great but I have a doubt it distorts the model of the surface. Always when I use this method the final surface is slightly below the whole point cloud. But I need to adjust my surface to agglomeration of points (exclude noisy points).

I am attaching a image of example points to submit what I mean.

Thank you for any suggestion in this case.

Best wishes,
Jacob

Hi Jacob,

Sadly I don't know much about the MLS function. It's part of the qPCL plugin and therefore it's only a portage of the PCL "MLS" functions (see http://pointclouds.org/documentation/tu ... mpling.php).

Luca Penasa (the author of the plugin) may be able to give you more info about it. Or the PCL community more probably.

You can try SOR (Statistical outlier removal) before MLS algorithm that would improve the quality of the surface.