Fitting a plane through a 3D point data
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For example, i have 3d point cloud data [xi, yi, zi] as the attachment .txt file. I want to fit a plane to a set of 3D point data. What kind of method to do that?
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Matt J
2018-5-6
How does one know that M and L are different planes and not just noise? Is there a known upper bound on the noise? A known lower bound on the separation distance between M and L?
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Matt J
2018-5-6
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ha ha
2018-5-6
Matt J
2018-5-6
No, I do not.
Matt J
2018-5-6
However, you may be able to modify this RANSAC line fitting routine
ha ha
2018-5-6
One approach you might consider is to take planar cross sections of your data. This will give 2D data for a line, with outliers. Then you can apply a ready-made RANSAC line-fitter, like the one I linked you to. From line fits in two or more cross-secting planes you should be able to construct the desired plane K.
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Walter Roberson
2018-5-6
data = load('1.txt');
coeffs = [data(:,1:2), ones(size(data,1),1)]\data(:,3);
The equation of the plane is then coeffs(1)*x + coeffs(2)*y - coeffs(3) = z
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xyz=load('1.txt');
xyz(xyz(:,2)>40, :)=[];
mu=mean(xyz,1);
[~,~,V]=svd(xyz-mu,0);
normal=V(:,end).';
d=normal*mu';
The equation of the plane is then xyz*normal.' = d
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