I am reading the following paper: SVO: Semi-Direct Visual Odometry for Monocular and Multi-Camera Systems , and I am having some problem understanding some concepts.
Before starting I have to say that I am new to visual odometry, so maybe some simple concepts are not clear to me.
The chapter of the paper i cannot undesrtand is the one related to relaxation and refinement at pag.4 of the paper.
For what I have understood here, the paper says that for perfoeming image alignment, instead of using an image from the enviroment, it is better to use an image from a frame, so a 2D image instead of a 3D image, and in particular it is used the oldest frame in which the image was first reconstructed, and it is done because the oldest frame minimizes the feature drift (I don't undestand why).
Moreover, it says that by doing this, there is the problem of having a reprojection error.
After this, there is a more mathematical analysis, which is also really unclear to me.
I know that it is a lot to ask an explaination on a full chapter of a paper, but can somebody please help me?