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I have 3 sets of point cloud that represent one surface. I want to use these point clouds to construct triangular mesh, then use the mesh to represent the surface. Each set of point cloud is collected in different ways so their representation to this surface are different. For example, some sets can represent the surface with smaller "error". My questions are: (1) What's the best way to evaluate such mesh-to-surface "error"? (2) Is there a mature/reliable way to convert point cloud to triangular mesh? I found some software doing this but most requests extensive manual adjustment. (3) After the conversion I get three meshes. I want to use a fourth mesh, namely Mesh4, to "fit" the three meshes, and get an "average" mesh of the three. Then I can use this Mesh4 as a representation of the underlying surface. How can I do/call this "mesh to mesh" fitting? Is it a mature technique? Thank you very much for your time!

Aaron
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  • Hi, as for point 3, what are you after? Some kind of optimisation where you minimise an error function? I posted my answers for point 1 and 2. – Nic Aug 29 '16 at 13:50

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Please find below my answers for point 1 and 2:

  1. as a metric for mesh-to-surface error you can use Hausdorff distance. For example, you could use Libigl to compare two meshes.
  2. To obtain a mesh from a point cloud, have a look at PCL
Nic
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