I have noisy 3D point cloud [x,y,z] plane for which, I fit a 2D plane (z = ax+by+c) by computing the coefficients [a,b,c] using least-squares. How can I project the points [x,y,z] onto this plane. I somewhat understand the math behind this but I am unsure how to program this in python.
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martineau
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Gokul Hari
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Does this answer your question? [How to project a point onto a plane in 3D?](https://stackoverflow.com/questions/9605556/how-to-project-a-point-onto-a-plane-in-3d) – woblob Jan 30 '22 at 06:01
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Unless your points were specifically measured as heights, a better way to fit your plane is with principal component analysis (https://en.wikipedia.org/wiki/Principal_component_analysis). The smallest eigenvector of the covariance matrix is the best normal vector for the plane, which should pass through the mean point. – Matt Timmermans Jan 30 '22 at 22:51