  Stereo relative pose problem lies at the core of stereo visual odometry
systems that are used in many applications. In this work, we present two
minimal solvers for the stereo relative pose. We specifically consider the case
when a minimal set consists of three point or line features and each of them
has three known projections on two stereo cameras. We validate the importance
of this formulation for practical purposes in our experiments with motion
estimation. We then present a complete classification of minimal cases with
three point or line correspondences each having three projections, and present
two new solvers that can handle all such cases. We demonstrate a considerable
effect from the integration of the new solvers into a visual SLAM system.
