2 research outputs found
Relative Pose Estimation of Calibrated Cameras with Known Invariants
The invariants of a pose include its rotation angle and
screw translation. In this paper, we present a complete comprehensive study of
the relative pose estimation problem for a calibrated camera constrained by
known invariant, which involves 5 minimal problems in total.
These problems reduces the minimal number of point pairs for relative pose
estimation and improves the estimation efficiency and robustness. The
invariant constraints can come from extra sensor measurements
or motion assumption. Different from conventional relative pose estimation with
extra constraints, no extrinsic calibration is required to transform the
constraints to the camera frame. This advantage comes from the invariance of
invariants cross different coordinate systems on a rigid body
and makes the solvers more convenient and flexible in practical applications.
Besides proposing the concept of relative pose estimation constrained by
invariants, we present a comprehensive study of existing
polynomial formulations for relative pose estimation and discover their
relationship. Different formulations are carefully chosen for each proposed
problems to achieve best efficiency. Experiments on synthetic and real data
shows performance improvement compared to conventional relative pose estimation
methods
On Relative Pose Recovery for Multi-Camera Systems
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