Six-Point Method for Multi-Camera Systems with Reduced Solution Space
<|reference_start|>Six-Point Method for Multi-Camera Systems with Reduced Solution Space: Relative pose estimation using point correspondences (PC) is a widely used technique. A minimal configuration of six PCs is required for generalized cameras. In this paper, we present several minimal solvers that use six PCs to compute the 6DOF relative pose of a multi-camera system, including a minimal solver for the generalized camera and two minimal solvers for the practical configuration of two-camera rigs. The equation construction is based on the decoupling of rotation and translation. Rotation is represented by Cayley or quaternion parametrization, and translation can be eliminated by using the hidden variable technique. Ray bundle constraints are found and proven when a subset of PCs relate the same cameras across two views. This is the key to reducing the number of solutions and generating numerically stable solvers. Moreover, all configurations of six-point problems for multi-camera systems are enumerated. Extensive experiments demonstrate that our solvers are more accurate than the state-of-the-art six-point methods, while achieving better performance in efficiency.<|reference_end|>
@article{guan2024six-point,
    title={Six-Point Method for Multi-Camera Systems with Reduced Solution Space},
    author={Banglei Guan, Ji Zhao, Laurent Kneip},
    journal={arXiv preprint arXiv:2402.18066},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.18066},
    primaryClass={cs.CV}
}