PointCloudExtractor

Serializes the geometry of a point cloud feature into a Blob attribute, encoding the contents according to a choice of common binary point cloud formats.

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Typical Uses

  • Storing point clouds in databases that do not support specific point cloud types but do support Blobs
  • Storage of point cloud geometry, as a temporary backup within a workspace

How does it work?

The PointCloudExtractor receives point cloud features and puts a copy of the point cloud geometry into an attribute, as a Blob - a Binary Large OBject.

The Blob content may be encoded as a variety of common point cloud formats. The name of the chosen format will also be recorded in an attribute for reference when decoding.

There are no parameters in the transformer to control how the point cloud is formatted, and encoding is done based on default settings for the chosen format. If necessary, format-specific settings may be overwritten by setting format attributes on the point cloud feature, prior to using the PointCloudExtractor. Consult the appropriate format’s Writer documentation for a complete list of available attributes and format limitations.

As the point cloud exits the transformer, it has two copies of its geometry - its original geometry and a copy as a Blob in an attribute.

Examples

Usage Notes

  • When writing the point cloud Blob Attribute to a database, you may need to adjust the database User Attribute type to an unbounded data type to avoid truncation of the data. Choose an appropriate attribute type depending on the destination format.
  • The PointCloudReplacer may be used to perform the reverse operation and convert the encoded blob back to the original point cloud geometry.
  • To carry out a similar operation on vector data, use the GeometryExtractor transformer. For raster data, use the RasterExtractor.
  • To remove the original geometry after using a PointCloudExtractor (leaving only the Blob attribute version), use a GeometryRemover.
  • The AttributeFileWriter transformer can be used to write the point cloud Blob Attribute directly to a file.

Choosing a Point Cloud Transformer

FME has a selection of transformers for working specifically with point cloud data.

For information on point cloud geometry and properties, see Point Clouds (IFMEPointCloud).

Configuration

Input Ports

Output Ports

Parameters

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.

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

Dialog Options - Tables

Transformers with table-style parameters have additional tools for populating and manipulating values.

Reference

Processing Behavior

Feature-Based

Feature Holding

No

Dependencies None
Aliases  
History  

FME Community

The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.

Search for all results about the PointCloudExtractor on the FME Community.

 

Examples may contain information licensed under the Open Government Licence – Vancouver and/or the Open Government Licence – Canada.

Keywords: point "point cloud" cloud PointCloud LiDAR sonar