cloudcompare/cccorelib — explained in plain English
Analysis updated 2026-07-21 · repo last pushed 2026-06-20
Build a C++ application that loads and cleans LiDAR scan data for surveying projects.
Create 3D point cloud filtering and analysis tools for autonomous vehicle development.
Develop software that connects point measurements into surface meshes using triangulation.
Construct a custom 3D scanning pipeline for archaeology or construction sites.
| cloudcompare/cccorelib | peng-zhihui/imgui-template | peng-zhihui/grblhost | |
|---|---|---|---|
| Stars | 197 | 189 | 187 |
| Language | C++ | C++ | C++ |
| Last pushed | 2026-06-20 | 2023-01-14 | 2021-05-26 |
| Maintenance | Maintained | Dormant | Dormant |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 3/5 |
| Audience | developer | developer | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
Requires CMake to build from source and optional external dependencies like CGAL for triangulation or Intel TBB for parallel processing.
CCCoreLib is a toolkit for programmers who need to work with 3D point cloud data, the dense collections of millions of spatial measurements you might get from a laser scanner (LiDAR) or photogrammetry software. Instead of building core data handling from scratch, developers can use this library to get immediate access to the structures and math needed to process, filter, and analyze 3D point sets. The library was originally bundled inside CloudCompare, a popular open-source 3D point cloud processing application. The maintainers split it out into its own standalone repository so that other projects could use the underlying engine without pulling in the entire CloudCompare application. It's written in C++, runs on Linux, macOS, and Windows, and is designed to be plugged into other software rather than used directly by end users. The README doesn't go into detail about the specific algorithms included, but it does mention a few optional capabilities. There's support for Delaunay 2.5D triangulation (a way to connect points into a surface mesh) through an external library called CGAL, and there are options for parallel processing to speed things up using either Intel's Threading Building Blocks or Qt's concurrent processing tools. The people who'd use this are developers building tools for industries like surveying, construction, archaeology, or autonomous vehicles, fields where you regularly capture real-world 3D scans and need to manipulate that data programmatically. If you're building an app that needs to load, clean, or analyze LiDAR scans, this library handles the heavy mathematical lifting so you don't have to. One tradeoff worth noting: documentation is still listed as a to-do item, and contribution guidelines haven't been formalized yet. The project is also LGPL-licensed, which allows it to be used in both open-source and commercial software under certain conditions, making it broadly accessible to the developer community.
A C++ library for handling 3D point cloud data from laser scanners or photogrammetry. It provides the core data structures and math to load, filter, and analyze dense spatial measurements, extracted from the CloudCompare application for standalone use.
Mainly C++. The stack also includes C++, CGAL, Intel TBB.
Maintained — commit in last 6 months (last push 2026-06-20).
Free to use in both open-source and commercial software, but you must share any modifications you make to the library itself and include the license notice.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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