Relative pose estimation using point correspondences (PC) is a widely used technique. A minimal configuration of six PCs is required for two views of generalized cameras. In this paper, we present several minimal solvers that use six PCs to compute the 6DOF relative pose of multi-camera systems, 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 the superior accuracy and efficiency of our solvers compared to state-of-the-art six-point methods. The code is available at https://github.com/jizhaox/relpose-6pt

翻译：基于点对应（PC）的相对位姿估计是一种广泛应用的技术。对于广义相机的双视图，需要六点对应的最小配置。本文提出了多种使用六点对应计算多相机系统六自由度相对位姿的最小求解器，包括一个针对广义相机的最小求解器，以及两个针对双相机装置实际配置的最小求解器。方程构建基于旋转与平移的解耦：旋转采用凯莱参数化或四元数表示，平移则可通过隐变量技术消除。当部分点对应关联相同相机在双视图中的关系时，我们发现并证明了射线束约束条件，这是减少解数量并生成数值稳定求解器的关键。此外，本文系统枚举了多相机系统六点问题的所有配置。大量实验表明，相较于现有最先进的六点法，我们的求解器在精度与效率上均表现出优越性。代码发布于 https://github.com/jizhaox/relpose-6pt