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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