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kaarigar

Least square fitting a plane question

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I have a set of 3d points in space. These points belong to a roof of a building. Using Jama Matrix package (a Java library), I have calculated a least square fitting plane for these points by solving A * X = B, which gives me X. Now I want to project all the points to this plane - how can I do that? With my limited knowledge, I know to define a plane I need normal and also a point on a plane before I can project any point to it. Can someone point me to right direction? Thanks!

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Take dot product between the normal of the plane and points computed from least square solver.

So I take it that the X calculated by the solver is the normal of the plane? Should it be normalized before using it in dot product? The dot product of a point with the normal would give a scalar - how is it to be used? Thanks!

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I assume by "projection" you mean the closest point P on the plane ax+by+cz+d=0 to a point A?

The line between P and A has the direction vector [a, b, c]

Is the [a,b,c] obtained by the matrix solving of A * X = B?

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[quote name='jameszhao00' timestamp='1318313177' post='4871348']
I assume by "projection" you mean the closest point P on the plane ax+by+cz+d=0 to a point A?

The line between P and A has the direction vector [a, b, c]

Is the [a,b,c] obtained by the matrix solving of A * X = B?
[/quote]


How is the plane represented in your least square solution?

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How is the plane represented in your least square solution?

I don't have a plane - as I have mentioned in my original post, I have a set of points and a fitted plane has been matrix solved using A * X = B. That has given me a column vector X which is the representative of the plane's A, B and C coefficients. The main problems is how I can project the original points to this plane. Being not a mathematician, this is a very complex problem for me to solve - any help is appreciated.

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