CloudCompare
CloudCompare 2.13.2 is an open-source tool for large 3D point clouds and triangular meshes, with registration, distance comparison, segmentation, scalar fields, sampling and conversion.
What CloudCompare provides
CloudCompare handles laser-scanning, photogrammetry and other large point-cloud or triangular-mesh data. Its strengths include registration, cloud-to-cloud and cloud-to-mesh distance, segmentation, scalar fields, sampling and format conversion. It is not a parametric CAD system and does not infer a survey coordinate system or engineering tolerance automatically.
Precision, coordinates and measurement notes
Large geographic coordinates can lose low-order precision in finite-precision calculations. A consistent Global Shift helps keep the working data stable; record the shift and check whether it is restored during export. Distance results also depend on registration, sampling density, neighborhood settings and surface assumptions, so retain parameters and error summaries.
Stable builds and plugins
Version 2.13.2 is the stable build for Windows 64-bit, Linux and Intel or Apple Silicon macOS. A 2.14 beta may contain newer features, while Windows installer and portable packages can ship different plugins. Check the actual build and format support before a production workflow. Review date: 2026-08-23.
Save to your cloud drive
Open the cloud drive to get the file directly, or save it for convenient access on another device.
Quark Cloud Drive
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Baidu Netdisk
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CloudCompare point-cloud import, registration and distance guide
Use a copy of a small dataset to install the stable build, record Global Shift, perform coarse and fine registration, calculate a distance field and export a reproducible result.
Before you start
- Prepare read-only source copies and record coordinate system, units, scanner stations and expected accuracy.
- Match the Windows, Linux or macOS build to the device and check whether the required format plugin is included.
- Start with a cropped sample so first-run rendering does not exhaust memory or graphics resources.
Installation steps
- 01
Choose the stable package
Select the Windows installer or portable archive, Linux package or matching macOS architecture, and record the version and plugin list.
- 02
Create a coordinate-aware project
Separate source data, working copies, exports and parameter notes. When Global Shift is proposed, record the vector and use it consistently across stations.
- 03
Begin with default rendering
Check the object tree, point count, bounding box and scalar fields before enabling high-cost coloring, normals or large point sizes.
Quick start
- 01
Import and crop a sample
Verify coordinates, units, colors, normals and scalar fields, then copy a small region for experiments instead of deleting from the complete object.
- 02
Run coarse alignment and ICP
Use corresponding points for a sensible initial pose, then run ICP and record overlap, sampling, error and the transform matrix.
- 03
Calculate and export a distance
Select cloud-to-cloud or cloud-to-mesh distance for the question, check signs, neighborhoods and color ranges, then reopen the export to verify coordinates.
Usage tips
- More points do not automatically mean more accuracy; outliers, occlusion and uneven sampling affect comparisons.
- Reports should include units, color range, statistics, registration error and the exact filter parameters.
- Opening a file does not prove that every attribute or plugin-specific field was preserved.
Troubleshooting and uninstall
Why is the point cloud black, flickering or missing?
Reset the view, check object visibility, point size, Global Shift and graphics drivers, then load a cropped sample with advanced coloring disabled.
Why is ICP clearly misaligned?
Return to coarse registration, confirm sufficient overlap and scale, remove moving objects and restrict the matching region before increasing iterations.
- Archive transforms and parametersSave source files, Global Shift, registration matrices, filters, plugin versions and export notes, then inspect an export in another viewer when appropriate.
- Remove the application and temporary dataUninstall CloudCompare and clear temporary indexes or test exports only after confirming that no original point cloud or external texture is still referenced.
Frequently asked questions
Should I use 2.13.2 or a 2.14 beta build?
Use 2.13.2 for a stable workflow and test beta builds on copies. Record the version and plugin list whenever measurements or research results are produced.
Can cloud-to-cloud distance and cloud-to-mesh distance be exchanged freely?
No. They make different assumptions about sampling, neighborhoods, surfaces and normals. Choose the method that matches the data and document its parameters.
Does the download require an extraction code?
The Quark entry does not require one; the four-character code for the Baidu entry is shown beside its download entry.