*first steps in JuMP*

How can I solve the PnP problem using JuMP?

I have a set of labeled 2d points with the corresponding 3d points.

The camera matrix K is known.

For any given R(3-element unit quaternion representing rotation) and T(3-element vector) the reprojection error is

is the mean squared distance between actual 2d-points and projected 3d-points

I want to use Levenberq-marquedt to minimize the reprojection error.

I don’t want to supply gradients or jacobians by hand , but I want some magic to do auto differentiating for me.

This optimization problem need to be re-usable and to run fast…I have about 8ms to spare.