Solving for a matrix using least squares

linear algebra

I am trying to understand equation 26 given equation 25.

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I know that generally, if we have an overdetermined system of linear equations of the form

$Ax = b$

the least squares solution is

$\hat{x} = (A^TA)^{-1}A^Tb$

Applying it to the above equation of

$D [R|t] = C$

where $[R|t]$ is the unknown matrix, we get

$\hat{[R|t]} = (D^TD)^{-1}D^TC$

but that's not exactly what's shown in equation 26. How did (26) come from (25) if they are "solving linearly"?

K is a 3×3 “camera matrix”, R is a 3×3 rotation matrix, and t is a 3×1 translation vector

Thanks!

Best Answer

In fact, equation 25 is $ [R|t] D = C$ and not $D [R|t] = C$ , and indeed $ [R|t] DD^T = CD^T$ , yielding $\hat{[R|t]}= CD^T*(DD^T)^{-1}$

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