Question about the logic behind determining covariance of priors in Gauss Newton optimizations.

I could not understand the covariance assignment of priors in Gauss-Newton optimization codes of Sparse Image Alignment part.

https://github.com/uzh-rpg/rpg_svo_pro_open/blob/ca371f304637e7fb355cf4624d0a02da4e3da220/svo_img_align/src/sparse_img_align_base.cpp#L83-L84

What is the logic behind this operation, i.e. looking at Hessian matrix entries to determine the information's weight? Same operation is also applied in reprojection error minimization part for rotation priors.

https://github.com/uzh-rpg/rpg_svo_pro_open/blob/ca371f304637e7fb355cf4624d0a02da4e3da220/svo/src/pose_optimizer.cpp#L321-L322

uzh-rpg / rpg_svo_pro_open

Question about the logic behind determining covariance of priors in Gauss Newton optimizations. #57