Algorithm for simplifying 3d surface?

Question

I have a set of 3d points that approximate a surface. Each point, however, are subject to some error. Furthermore, the set of points contain a lot more points than is actually n

Answer 1

It's simpler to simplify a point cloud without the constraints of mesh triangles and indices.

smoothing and simplification are different tasks though. To simplify the cloud you should first get rid of noise artefacts by making a profile of the kind of noise that you have, it's frequency and directional caracteristics and do a noise profile compared type reduction. good normal vectors are helfpul for that.

here is a document about 5-6 simplifications using delauney, voronoi, and k nearest neighbour maths:

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.10.9640&rep=rep1&type=pdf

A later version from 2008: http://www.wseas.us/e-library/transactions/research/2008/30-705.pdf

here is a recent c++ version: https://github.com/tudelft3d/masbcpp/blob/master/src/simplify.cpp