Down-Sample Point Cloud

You are currently viewing the documentation for the latest version (2.1.2). To access a different version, click the "Switch version" button located in the upper-right corner of the page.

■ If you are not sure which version of the product you are currently using, please feel free to contact Mech-Mind Technical Support.

Function

This Step is used to down-sample a point cloud to reduce the number of points.

Usage Scenario

This Step is usually used for point cloud preprocessing when there are too many point cloud points to be processed, to improve the project running speed.

Input and Output

input and output

Parameter Description

Sampler Type

Description: This parameter is used to select the sampling method you want to use.

Value list: UniformSampler, VoxelGridSampler

  • UniformSampler: Uniform sampling method. Divide the point cloud into 3D grids of fixed size, and only the point closest to the grid center will be retained in each grid to reduce the point cloud density.

  • VoxelGridSampler: Voxel sampling method. Divide the point cloud into 3D grids of fixed size, calculate the average normals and positions of all points in each gird, generate a new point from the average, and discard the other points to reduce point cloud density.

Default value: VoxelGridSampler

Tuning recommendation: It is recommended to use the default value.

Sampling Interval

Description: This parameter is used to set the edge length of the 3D grid during downsampling. The larger the value, the sparser the downsampled point cloud will be.

Default value: 10.000 mm

Is this page helpful?

You can give a feedback in any of the following ways:

We Value Your Privacy

We use cookies to provide you with the best possible experience on our website. By continuing to use the site, you acknowledge that you agree to the use of cookies. If you decline, a single cookie will be used to ensure you're not tracked or remembered when you visit this website.