3D surface reconstruction from a sparse point cloud

Question

I have an equipment which performs radial scan. It scans an object along the green lines showing in the image(three lines in the image, but the equipment can perform more).

Thus, I can get a point cloud, which contains points from the upper and lower surfaces of the object. And I want to make surface reconstruction using the point cloud. I load the point cloud file(.txt format, xyz coordinates of each point) into Meshlab and it shows like this(yellow points are the points in the point cloud):

I then followed a blog teaching simple usage of Meshlab and clicked "Fiter——>Normals,Curtavures and Oreientation——>Smooths normals on a point set" and "Fiter——>Remeshing Simplication and Reconstruction——>Surface Reconstruction：Ball Pivoting". (both default setting)

However, the results was not I want:

It connects points within a scanned image, but the surface should be reconstructed by connecting points between adjacent scanned images.

I can think about two possible reasons:(1) I did not choose right setting in Meshlab. If so, which setting parameters can make reconstruction for the point cloud. (2)My point cloud is too sparse and I need to interpolate the point cloud to make it have more points and which interpolation method should I use?

————————————————————EDIT———————————————————

The normals computed in this image are computed using Neighbour num 10 and smooth iteration 8.

And, the normals computed in this image are computed using Neighbour num 60 and smooth iteration 8. When Neighbour num is greater than 20, normals are similar to the image below.

Answer 1

It is possible that you are having problems due to inequality directional sampling of the surface. You have high density of points in one direction, then a big gap in the other direction. This is a problem due to 'Compute normals for point sets' filter uses a parameter with the number of Neighbours to each point, so the computer normal will be byassed because there is unlikely to find neighbours in a different scanline.

So my proposal is (I will reuse parts from this tutorial )

Point Cloud Simplification and Normals Computation

• Start by increasing the number of orientations in the scan. You want to fill those gaps.
• If you need to reduce the number of point samples in the center of the object to reduce noise, go to Filters -> Point Set -> Point Cloud Simplification. Make sure Best Sample Heuristic is checked.
• After point cloud simplification, make sure to select Simplified point cloud in the Show Layer Dialog on the right hand side. If not visible, it can be opened by navigating to View -> Show Layer Dialog. Now we need to compute normals for point set.
• So go to Filters -> Point Set -> Compute normals for point sets . Enter Neighbour num between 10 - 100. Initially try with 10 and try to get a mesh and later see if this can be improved by increasing the neighbour number. For Smooth Iteration initially try with 0 value and may be later it can be tried with values between 5 - 10. I mostly use value 8.
• Make sure if your normals are properly computed by going to Render -> Show Normal.

Meshing / Poisson Surface Reconstruction

• Next we are going to use Poisson Surface reconstruction to do meshing.
  • So go to Filters ->Remeshing, Simplification and Reconstruction -> Screened Poisson Surface Reconstruction. Initially try with default parameters then later one can play around with reconstruction depth, number of samples and interpolation weight values.
  • This will create another mesh layer called Poisson in the Show layer Dialog which has surfaces now. Make sure to select that to peform further operations.
  • One can observe that it has also created some extra surfaces. To remove them go to Filters -> Selection -> Select Faces with edges longer than .... By default the value is automatically computed, just click on apply. Then click on delete face button (triangle face and three vertex with a cross over it). This will remove extra surfaces.
  • After this operation, still some noise faces can be seen. To remove them go to Filters -> Cleaning and Repairing -> Remove isolated pieces (wrt Face Num.). Use the default value and make sure Remove unreferenced vertices is checked. This will remove some noise faces.
  • Even after the above operation some noise faces are seen. To remove them go to Filters -> Selection -> Select non Manifold Vertices. Click apply. Then click on delete face button (triangle and threwe vertex with a cross over it). This will remove remaining extra faces.