GitHub repository
A simple, multi-language implementation of the Iterative Closest Point algorithm for 3D point cloud registration.
What is GitHub repository?
simpleICP is a collection of straightforward implementations of the Iterative Closest Point (ICP) algorithm in C++, Julia, Matlab, Octave, and Python. It solves the problem of aligning two 3D point clouds by estimating a rigid-body transformation (rotation and translation) that minimizes the distance between them. The algorithm is particularly useful when point clouds are sampled differently or only partially overlap.
Researchers, engineers, and developers working in fields like computer vision, robotics, photogrammetry, and geospatial analysis who need a simple, readable ICP implementation for point cloud registration.
Developers choose simpleICP for its clean, multi-language codebase that emphasizes readability over optimization, its use of point-to-plane distance for better convergence, and its support for partial overlaps and parameter observation (in Python).
Overview
Implementations of a rather simple version of the Iterative Closest Point algorithm in various languages.
Use Cases
Best For
- Aligning 3D scans from LiDAR or photogrammetry
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