基于加权加速正交迭代算法的相机位姿估计

Pose estimation of camera based on weighted accelerated orthogonal iterative algorithm

单目视觉中的位姿估计是三维测量中的一个关键问题,在机器视觉、精密测量等方面运用广泛。该问题可通过n点透视(PnP)算法求解,正交迭代算法(OI)作为PnP算法的代表,因其高精度的优点在实际中得到了广泛运用。为了进一步提高OI算法的稳健性和计算效率,提出了一种加权加速正交迭代算法(WAOI)。该方法首先根据经典正交迭代算法推导出加权正交迭代算法,通过构建加权共线性误差函数,利用物点重投影误差更新权值,达到迭代优化位姿估算结果的目的;在此基础上,通过自适应权值,整合每次迭代过程中平移向量以及目标函数的计算,减少迭代过程中的计算量,从而实现算法的加速。实验表明,在12个参考点中存在两个粗差点的情况下,WAOI的参考点重投影精度为0.64 pixel,运算时间为8.02 ms,精度高且运行速度快,具有较强的工程实用价值。

Pose estimation in monocular vision is a key problem in three-dimensional measurement,which is widely used in machine vision,precision measurement and so on.This problem can be solved by n-point perspective(PnP)algorithm.Orthogonal iterative algorithm(OI),as the representative of PnP algorithm,has been widely used in practice because of its high precision.In order to further improve the robustness and computational efficiency of OI algorithm,a weighted accelerated orthogonal iterative algorithm(WAOI)is proposed in this paper.Firstly,the weighted orthogonal iterative algorithm is deduced according to the classical orthogonal iterative algorithm.The weighted collinearity error function is constructed and the weight is updated by using the object point reprojection error to achieve the purpose of iteratively optimizing the pose estimation results.Secondly on this basis,through adaptive weights,the calculation of translation vector and objective function in each iteration is integrated to reduce the amount of calculation in the iterative process,so as to accelerate the algorithm.The experimental results show that when there are two rough points in the 12 reference points,the reprojection accuracy of the reference point of WAOI is 0.64 pixel,the operation time is 8.02 ms,the accuracy is high and the running speed is fast,so it has strong engineering practical value.