library: OpenGV
pages:   http://laurentkneip.github.io/opengv
brief:   OpenGV is a collection of computer vision methods for solving
         geometric vision problems. It contains absolute-pose, relative-pose,
         triangulation, and point-cloud alignment methods for the calibrated
         case. All problems can be solved with central or non-central cameras,
         and embedded into a random sample consensus or nonlinear optimization
         context. Matlab and Python interfaces are implemented as well. The link
         to the above pages also shows links to precompiled Matlab mex-libraries.
         Please consult the documentation for more information.
author:  Laurent Kneip, The Australian National University
contact: kneip.laurent@gmail.com


In folders: 2018AMMPoseSolver/include/opengv/optimization_tools/  and 2018AMMPoseSolver/src/optimization_tools/ you can find the headers/source code of the algorithm described in the paper.
In folder https://github.com/pmiraldo/2018AMMPoseSolver/blob/master/test/ you can find our algorithms testes under the names results_*