blue-stone-j/cloud-sample

Some algorithm for downsampling point cloud.

cloud downsample and filter

Some algorithms to downsample or filter point cloud.

Cloud files are stored in folder assets. You can get more clouds as example from here.

interface

This is base class for all sample_filter class.

far_outliers_removal(skip)

farthest_point_sampling

farthest_point_sampling is a greedy algorithm that samples from a point cloud data iteratively. It starts from a random single sample of point. In each iteration, it samples from the rest points that is the farthest from the set of sampled points.

grid_sample(skip)

kmeans_sample(skip)

mirror_reflection_removal(skip)

normal_space_sample(skip)

Less points are reserved where normal changes slowly, more where faster.

poisson_disk_sample(skip)

radius_outlier_removal

Only points that have enough neighbors will be reserved.

statistical_outlier_removal

statistical_outlier_removal removes points that are further away from their neighbors compared to the average for the point cloud.