🔷Euclidean Clustering Point Cloud Segmentation

Function Description

This operator performs clustering segmentation on input point clouds based on the Euclidean distance between points. It aggregates spatially adjacent points into independent clusters. If a point’s distance to any point in an existing cluster is less than the set "search radius", or if it can connect to a point within the radius, then this point is assigned to that cluster. The operator finally outputs a point cloud list where each point cloud represents a segmented cluster.

Usage Scenarios

  • Instance segmentation: Segmenting physically separated objects in a scene into independent point cloud clusters. For example, segmenting multiple parts on a conveyor belt, or multiple cups on a table.

  • Noise removal: By setting the "minimum points per cluster", it can effectively filter out point cloud clusters with too few points, which may be background noise or sensor error-generated points.

  • Point cloud preprocessing: Before performing tasks such as object recognition and pose estimation, segmenting raw point clouds or ROI point clouds into units representing different objects.

  • Very similar functionality to the "Connected Component Segmentation" operator, both typically utilize spatial proximity for clustering.

Input Output

Input

Point clouds: Input point cloud or point cloud list to be segmented.

EuclideanSegmentation input

Output

Segmented point clouds: Point cloud cluster list obtained after segmentation.

EuclideanSegmentation output

Parameter Description

This operator has two versions:

  • Euclidean Clustering Point Cloud Segmentation: Processes point clouds without normal information.

  • Euclidean Clustering Point Cloud Segmentation (With Normals): Processes point clouds with normal information.

Both have identical core functionality and parameters, differing only in the point cloud data types they process.

Search Radius

Parameter Description

Defines the maximum distance threshold within which a point can be added to a cluster during the clustering process. This is also the search radius for finding neighboring points.

Parameter Adjustment

  • Decreasing this value: Makes clustering conditions stricter, only very close points will be assigned to the same cluster, potentially causing one object to be split into multiple small clusters, or making it easier to separate closely positioned objects.

  • Increasing this value: Makes clustering conditions more lenient, points at slightly farther distances may also be grouped into one cluster, potentially merging different objects.

Parameter Range

[0, 200], default value: 5, unit: mm

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Search radius=5mm

Search radius=10mm

Search radius=15mm

Minimum Points per Cluster

Parameter Description

The minimum number of points that a valid cluster must contain.

Parameter Adjustment

Used to filter out overly small point cloud clusters. Increasing this value can remove more small clusters (usually considered noise), but if set too large, it may filter out small but valid objects.

Parameter Range

[1, 4000000], default value: 100

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Minimum points per cluster=20

Minimum points per cluster=100

Minimum points per cluster=1000

Maximum Points per Cluster

Parameter Description

The maximum number of points that a valid cluster is allowed to contain.

Parameter Adjustment

Used to filter out overly large point cloud clusters. Suitable for scenarios where background, ground, or other oversized clustering results need to be excluded. Usually keep the default value (a very large number) unless there are special requirements.

Parameter Range

[1, 4000000], default value: 4000000

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Maximum points per cluster=2000

Maximum points per cluster=5000

Maximum points per cluster=4000000

Keep All Results

Parameter Description

Determines whether to output all clustering results that meet the size criteria.

Parameter Adjustment

  • Enabled (default): Keep all clusters that pass the minimum/maximum point count filtering.

  • Disabled: Only keep the top N clusters with the most points, where N is specified by the "Number of Results to Keep" parameter.

Number of Results to Keep

Parameter Description

Takes effect when "Keep All Results" is set to disabled. Specifies the number of clusters with the most points to keep.

Parameter Adjustment

The operator will first sort all segmentation results by point cloud count from largest to smallest. Setting this parameter to N will output only the top N point cloud clusters after sorting. For example, setting it to 1 means only outputting the cluster with the most points.

Parameter Range

[1, 1000], default value: 1

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Number of results to keep=1

Number of results to keep=5

Number of results to keep=10

Sort Results

Parameter Description

Determines whether to sort the final output point cloud cluster list by point cloud count from largest to smallest.

Parameter Adjustment

  • Enabled (default): Output point cloud list is sorted by point count from most to least.

  • Disabled: Output point cloud list order is indeterminate.

If subsequent processing depends on the size order of point cloud clusters, this option should remain enabled.

Enable Node

Parameter Description

Controls whether this operator executes computations.

Parameter Adjustment

  • Enabled (default): Normal operation of the operator functionality.

  • Disabled: The operator performs no operations and directly outputs the input data.