基于法化矩阵降维的多相机快速光束法平差算法

针对多相机系统的高精度快速光束法平差问题,提出一种采用法化矩阵降维的多相机快速光束法平差新算法。充分考虑多相机系统中主从相机间的固定位姿参数关系,设置维数为3N(相机个数)×4的系统位姿变换矩阵,根据此矩阵可快速由主相机参数得到每个从相机的参数,并将此变换关系带入光束法平差算法中完成为对从相机位姿的求取。从相机的外参优化算法中便只需要对主相机的外参变化进行更新,由此将所有相机捆绑为一个整体,使雅可比矩阵与法化矩阵的维数相对下降,在一次迭代更新中可以完成对多个相机特征图像的运算,因此算法的精度与速度得到了大幅提高。根据仿真实验与实测实验表明,文中算法的优化精度比传统的光束法平差精度提高到了15.5%,运算效率提升了7.8%,能够满足实际工程的应用需求。

Multi-camera fast bundle adjustment algorithm based on normalized matrix dimensionality reduction

Aiming at the problem of high-precision and fast bundle adjustment of multi-camera systems, a multi-camera fast bundle adjustment algorithm based on normalized matrix dimensionality reduction was proposed. Considering the fixed pose parameter relationship between the master and slave cameras in a multi-camera system, the system pose transformation matrix with the dimension of 3N (number of cameras)×4 was used. According to this matrix, each slave camera parameters could be quickly obtained from the master camera parameters, and the transformation relationship was taken into the bundle adjustment algorithm to get the posture of all slave cameras. For external parameters optimization of all cameras, only the external parameter of main camera need to be updated. So all cameras were bundled as a whole, which made the dimension of the Jacobian matrix and the normalized matrix relatively reduce. The calculation of multiple camera feature images could be implemented in one iteration, so the accuracy and speed of the algorithm have been greatly improved. According to simulation and practical measurement experiments, the optimization accuracy of the proposed algorithm is 15.5% higher than traditional bundle adjustment, and the operation efficiency is improved by 7.8%. These precise results can meet the practical engineering application requirements.