Hi Mr. Agarwal,
Many thanks for the reply here and suggestion at stackoverflow.
I am a grad student and me and my supervisor are working on methods for solving linear systems. We are developing a particular one that seems to be promising and I would like to insert them on ceres for test/comparison with other current methods.
I noticed that ceres has quite a few methods such as conjugate gradient method, QR factorization, Cholesky and so on for dense and sparse matrices. I want to put my method in a 'side-by-side' fashion manner. For that I need to have access for the normal equations Hx=b (I mean the Hessian matrix H and the independent vector b). I could not find the exact place where to find it.
We are interested in use that in Computer Vision problems. Currently, we are using OpenMVG, that uses ceres for least-square minimization during Bundle Adjustment step (I am sure you understand very well this problem. I read your paper on that). In this particular case, ceres apparently uses Schur decomposition for solving the linear systems.
In my particular machine, I am using Ubuntu 16.04 with the latest ceres version. I know that the code is well commented, but I still could not figure it out what function really performs the linear system solution. Most likely are several functions/methods one for each linear system solution method. I would be very happy if you could tell me to which class they belong and how to access the Hessian matrix H and the independent vector b of normal equations Hx=b in each iteration.
Again, many thanks for the help and for making ceres open source. Definitely, it is an incredible contribution for the Computer Vision and Optimization communities and many others.
Diego.