Adaptive point cloud denoising

Organization of the repository:

• code:
  • viewer: 2D point cloud denoising with a discrete Mean Curvature Flow approach
  • 3dviewer: 3D point cloud anistropic denoising
  • python: python bindings for the 2D case
• report: final master report
• pres: slides for the presentations (team meeting and oral defense)

Dependencies

• CGAL >=4.7
• Eigen
• CMake
• Qt5

Python bindings:

• Boost.Python
• Boost.NumPy (git submodule update --init)
• NumPy, SciPy, matplotlib

Building the code

mkdir build && cd build && cmake .. && make