利用平面约束中的反对称性进行相机自定标

Camera Self-Calibration Using the Antisymmetry in Planar Constraints

回顾了 2幅图像中的平面约束 ,以及一个图像对的基础矩阵和同形矩阵的乘积是一个反对称矩阵的性质 ,并通过证明展示了这种反对称性质和平面约束之间的关系 给定两幅图像中的一系列对应点 ,利用反对称性质提出了一种改进的相机自定标算法 ,将利用平面约束进行相机自定标过程中求取同形矩阵 (homographymatrix)的问题转化成了方程组约束条件下的二次规划问题 ,通过解决给定的二次规划问题求解同形矩阵 ,提高了算法的鲁棒性 ,然后利用平面约束求解内参数 ,最后通过本质矩阵 (essentialmatrix)和基础矩阵 (fundamentalmatrix)之间的关系以及旋转矩阵的性质求解相机外参数 实验结果表明 。

In this paper the planar constraints are reviewed and the relationship of the antisymmetry and the planar constraints for two perspective images is discussed And given a set of correspondent points in a plane in two images, a robust improved algorithm is proposed to transform the problem of calculating the homography matrix in the process of camera self calibration with the planar constraints to a quadratic programming problem And then the intrinsic parameters can be calculated with the planar constraints and the extrinsic parameters can be calculated using the relationship between the essential matrix and the fundamental matrix The experimental results show that the algorithm is robust