Symmetry and Orbit Detection in Point Clouds
Published:
Symmetry and orbit are important global features for point clouds but the detection remains a huge challenge. In this project, I studied the paper: Symmetry and Orbit Detection via Lie-Algebra Voting. The main idea is to embedding patches into a Lie algebra $\mathfrak{sim}(d)$ with an optimal distance metric. Then RANSAC or Mean-shift is used to extract correponding structures.
In this project, I achieved the following goals:
Adapted the algorithm to 2D point clouds and implemented it in Python, to facilitate the visualization and parameter tuning.
Implemented the algorithm on 3d point clouds in C++, which allows a fast computation on big point cloud.
Studied the influence of different parameters
Requirements
2D Case
- >= Python 3
- Numpy, Sklearn, matplotlib
3D Case
- CGAL
- Eigen
- cpp 11+