robust algorithm for surface reconstruction from 3

Question

I am trying to figure out what algorithms there are to do surface reconstruction from 3D range data. At a first glance, it seems that the Ball pivoting algorithm (BPA) and Poisson surface reconstruction are the more established methods?

• What are the established, more robust algorithm in the field other than BPA and Poisson surface reconstruction algorithm?
• Recommended research publications?
• Is there available source code?

Answer 1

Here on GitHub, is a open source Mesh Processing Library in C++ by Dr. Hugues Hoppe, in which the surface reconstruction program Recon is a good option for your problem...

Answer 2

You might be interested in Alpha Shapes.

Answer 3

As I had this problem too, I did develop and implement my own point cloud crust algorithm. The sources as well as the documentation can be found on github.com: https://github.com/ricebean-net/PointCloudCrust. The algorithm is implemented in Java.

Maybe, this can help you. You can find also a short python script on the page which illustrates how to use the library. Have fun!

Answer 4

There is 3D Delaunay tool by Geometric Tools. This tool is used DirecX and OpenGL. Unfortunately, you may need buy a book to see actual example code of the library. You still read the code and figure out.

Matlab also introduced a surface reconstruction tool using Delaunay, delaunayTriangulation class.

Answer 5

If you want make some direct experiments with various surface reconstruction algorithms you should try MeshLab, the mesh-processing system, it is open source and it contains implementations of many of the previously cited surface reconstruction algorithms, like:

• Poisson Surface Recon
• a couple of MLS based approach,
• a ball pivoting implementation
• a variant of the Curless volume based approach
• Delaunay based techniques (Alpha shapes and Voronoi filtering)
• tools for computing normals from scattered point sets
• and many other tools for comparing/measuring/cleaning/simplifying the resulting meshes.

Sources are protected by GPL, so you could not use them in a commercial closed source project, but it is very important to get the right feeling about the properties of the various surface reconstruction algorithms (how sensitive to noise they are, the speed, the robustness to outliers, how they preserve fine details etc etc) before starting to implement one of them.

Answer 6

You might start looking at some recent work in the field - currently something like Fast low-memory streaming MLS reconstruction of point-sampled surfaces by Gianmauro Cuccuru, Enrico Gobbetti, Fabio Marton, Renato Pajarola, and Ruggero Pintus. Its citations can get you going through the literature pretty quickly.