Import, Export, and Visualization
R2026bThe toolbox enables you to import and visualize point cloud data in MATLAB®. You can read data from various file formats, such as PLY, PCD, LAS, LAZ, E57, Ibeo data container, Velodyne® PCAP, Ouster® PCAP, and Hesai® PCAP.
To process large point cloud data that might not fit into memory, you can use the
blockedPointCloud object to represent the point cloud as a collection of
smaller blocks and process each one independently.
You can also export processed data to the PLY, PCD, LAS, and LAZ file formats. To learn how to work with lidar data, see Read, Process, and Write Lidar Point Cloud Data.
Apps
| Point Cloud Analyzer | View, edit, and analyze point cloud data |
Functions
Blocks
 | Point Cloud Viewer | Visualize streaming point cloud data sequence (Since R2023a) |
Topics
- Introduction to Lidar
High-level overview of lidar concepts and applications.
- Coordinate Systems in Point Cloud Toolbox
Overview of coordinate systems in Point Cloud Toolbox™.
- What Are Organized and Unorganized Point Clouds?
Define unorganized and organized point clouds and how to convert the former to latter.
- The PLY Format
The Stanford Triangle Format.
- Choose a Point Cloud Viewer
Compare visualization functions.
- Overview of Large Point Cloud Processing
Understand block processing for large point clouds that do not fit in memory.
Featured Examples
Read Point Cloud Data from LAZ File
Create a lasFileReader object to use to read point cloud data and header information from a LAZ file.
Read Lidar and Camera Data from Rosbag File
Read and save images and point cloud data from a rosbag file. This example also shows how to prepare the data for lidar camera calibration.
Read, Process, and Write Lidar Point Cloud Data
Read a point cloud into the workspace, select a desired set of points, and then write the selected points to a point cloud file format.
Color Point Clouds in pcviewer
Control point cloud coloring in pcviewer. You will learn how to:
Visualize LAS Classification Labels
Read classification attributes from a LAS file and color the point cloud by class in pcviewer. Point cloud data from collection methods like aerial surveys often includes per-point classification labels (ground, vegetation, buildings) following the ASPRS standard.
Color Point Clouds by Point Properties
Use per-point properties from a lidar point cloud to color the visualization in pcviewer. Coloring by point properties helps you identify patterns that are not visible in raw XYZ or RGB data, such as surface roughness, vegetation penetration, and acquisition geometry. The example demonstrates coloring by density, curvature, distance to ground, laser return number, scan angle, and elevation blending.
Export Point Cloud Segmentations to KML Files
Export segmented point cloud data to Keyhole Markup Language (KML) files and read and visualize the KML data using different tools.
Publish and Receive Point Cloud ROS Messages
Work with point cloud ROS messages and deploy them as a ROS node using MATLAB®.
