  The point correspondence (PC) and affine correspondence (AC) are widely used
for relative pose estimation. An AC consists of a PC across two views and an
affine transformation between the small patches around this PC. Previous work
demonstrates that one AC generally provides three independent constraints for
relative pose estimation. For multi-camera systems, there is still not any
AC-based minimal solver for general relative pose estimation. To deal with this
problem, we propose a complete solution to relative pose estimation from two
ACs for multi-camera systems, consisting of a series of minimal solvers. The
solver generation in our solution is based on Cayley or quaternion
parameterization for rotation and hidden variable technique to eliminate
translation. This solver generation method is also naturally applied to
relative pose estimation from PCs, resulting in a new six-point method for
multi-camera systems. A few extensions are made, including relative pose
estimation with known rotation angle and/or with unknown focal lengths.
Extensive experiments demonstrate that the proposed AC-based solvers and
PC-based solvers are effective and efficient on synthetic and real-world
datasets.
