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Load and View Point Cloud Data

Open Lidar Labeler App

To open the Lidar Labeler app, at the MATLAB® command prompt, enter this command.


Alternately, you can open the app from the Apps tab of the MATLAB toolstrip, under Image Processing and Computer Vision. The app opens to an empty session.

Import Point Cloud Data

You can load point clouds from multiple types of data sources into the Lidar Labeler app. On the app toolstrip, select Import > Add Point Cloud > From File to open the Select Point Cloud dialog box, when enables you to specify a file from which to load a point cloud.

Import Point Cloud Sequence

In the Select Point Cloud dialog box, the default value of Source Type parameter is Point Cloud Sequence.

Select Point Cloud dialog box.

  1. To specify Folder Name parameter, select Browse and navigate to the folder that contains the sequence of point cloud data (PCD) files you want to load and click Select Folder.

  2. To specify timestamps using a MATLAB workspace variable, set the Timestamps parameter to From Workspace and, in the Import From Workspace dialog box, select the variable and click OK. Otherwise, set Timestamps to Use Default.

    Import From Workspace dialog box.

  3. In the Select Point Cloud dialog box, select OK. The app loads the specified point cloud sequence.


When Source Type is Point Cloud Sequence, the app reads point cloud frames lexicographically, where the arrangement of characters, words, or numbers is in alphabetical order.

Other Import Options

You can also import data from these sources into the app.

 Velodyne Lidar Data

 Custom Source

 LAS/LAZ file

 Rosbag File

Alternately, select Import > Add Point Cloud > From Workspace to import data from the MATLAB workspace.

Visualize Point Cloud Data

Labeling 3-D point cloud data is a challenging task due to the sparse and unstructured nature of the data. The Lidar Labeler app provides a variety of visualization options on the LIDAR tab of the app toolstrip, enabling you to more easily label 3-D data points.

Color Controls

On the LIDAR tab of the app toolstrip, you can choose color options to control the display of the point cloud.

Colormap section on app toolstrip


 Colormap Value

 Background Color

Camera View Options

Use these camera options to view, adjust, and compare your point cloud and label data.

Camera views

 ROI View

 XY View

 YZ View

 XZ View

 Bird's Eye View

 Chase View

 Ego View

 Ego Direction

 Camera View

Ground View Options

Lidar Labeler ground views

  1. Set Ground View to specify whether the visualization displays all the points, only the ground points, or only the nonground points in the point cloud.

  2. Select Ground Settings to change the ground segmentation algorithm and tune the corresponding parameters.

    Lidar Labeler ground settings dialog

  3. In the Hide Ground dialog box, select a segmentation algorithm from the list. The dialog box then displays the parameters for the selected algorithm, along with their values, and a slider for each with which to adjust that parameter value, to fine-tune your ground segmentation results. The app supports these algorithms:

    • Range-based floodfill (default) — Segment the ground plane in organized point cloud data using the segmentGroundFromLidarData function.

    • Fit ground plane — Segment the ground plane in organized point cloud data using the pcfitplane function.

    • Segment ground SMRF — Segment the ground plane in either organized or unorganized point cloud data using the segmentGroundSMRF function. Use this algorithm for non-uniform ground planes and aerial lidar data. The default parameters have been tuned for aerial data. For ground lidar data, decrease the Max Window Radius parameter to 5 and the Elevation Threshold parameter to a value in the range [0.2, 0.3].

See Also



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