The detection of edges in 3d objects may be the first step for the automatic processing of particular characteristics and landmarks.
Thus, I'm looking for a method to identify such edges for some of my 3d-scanned objects.
However, with all my ideas (Hough transformation, angles threshold for neighboring vertices) I didn't succeed.
Thus, I'd be quite happy if someone could point me to a solution to the edge-finding-problem for 3d point clouds which can be applied using R.
There is a nice paper from last year about this topic.
Basically, you need to compute several features, for each point, based on it's neighbors.
I usually prefer Python over R so I'm not aware of any point-cloud processing package un R. But the implementation of that paper in R should be easy.
If you can translate Python-R, you can take a look at this library that I wrote as it has already implemented the computation of all the features mentioned on that paper.
If that helps you, in this answer you can find example code on how to add the curvature for each point. You just have to replace the word curvature with the other names of features.
