I want to use Open3D to filter a realsense D415 pointcloud, my goal is to remove outliers and generally clean the raw pointcloud a bit. I tested the python tutorial for outlier removal and it gives nice results, but to use the “remove_radius_outlier” and “remove_statistical_outlier” functions the pointcloud first needs to be downsampled with “voxel_down_sample”. If I run the outlier removal functions on the raw pointcloud, it also works but its very slow.
So my question is:
How can I recover the original pointcloud after filtering the voxel_down_sampled pontcloud?
I checked the function “voxel_down_sample_and_trace” ,
voxel_down_pcd,org_ind = pcd.voxel_down_sample_and_trace(voxel_size=0.02,
min_bound=pcd.get_min_bound(),max_bound=pcd.get_max_bound())
this function lists the corners of the voxel cube in “org_ind”, but it does not return index of all points that contribute to form the voxel