Singular value decomposition

Question

I started to learn something about camera matrix and its solution method. There are some methods which in many of them I saw using of singular value decomposition of a matrix but I can't understand what is the aim for using that, Anybody can give some hints about that?

Answer 1

SVD is used to decompose a matrix into three matrices that multiplied together one way will give the original matrix, and if multiplied in reverse order will give you the inverted matrix.

This is very useful for example when trying to solve a system of equations of n equations with n unknowns.

In the case of the calibration of a camera I would assume the unknowns are the calibration parameters.

I will try and find you a good link that describes both processes.