I have a 3D point cloud that I attained from tracing out the outline of a shape with sensors attached to my fingertips. The resulting data has non-uniform density with large gaps between some of the points.
What are some good surface reconstruction algorithms to use on this kind of data that is recorded by hand and therefore has issues of varying density?
I have been attempting to use the Cocone, Robust Cocone, and Tight Cocone Surface Reconstruction algorithms from Tamal Dey to reconstruct the shape, but I am having difficulty because I believe my data is much less uniform than the example point sets provided with the algorithms. I have read Tamal's literature on each reconstruction algorithm because there are variables that can be altered in the algorithms, but I have been unable to find the right settings to get my data to work with any of the Cocone algorithms.
Does anyone understand the user settings in these algorithms?
What would be the best settings for very non-uniform data points? I can provide the 3D point data of the shape upon request.