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PointCloudThinner

Outputs point cloud features that have fewer points than the original input features. This transformer is typically used to reduce data volume by identifying a set of points to keep and discarding the remaining points.

Input Ports

Output Ports

Parameters

Examples

Thinning Type Amount Result
Every Nth Point (Interval) 5 Every 5th point of the input cloud feature will be present in the output point cloud.
Every Nth Point (Maximum Number of Points) 100 The output cloud will have a maximum of 100 points, evenly spaced throughout the input.
First N Points 100 The first 100 points from the input will be kept.

In this example, the output point cloud on the right keeps every 50th point from the source point cloud on the left:

Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

Transformer Categories

Point Clouds

Related Transformers

The transformer can be used with PointCloudCombiner to make mosaics of large areas from smaller tiles.

 

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Search for samples and information about this transformer on the FME Knowledge Center.

Tags Keywords: point "point cloud" cloud PointCloud resample thin LiDAR sonar PointCloudSampler