估计基本矩阵的一个新方法

A New Approach to Estimating Fundamental Matrix

基本矩阵在机器视觉中有着广泛的应用。提出了估计基本矩阵的一个新的线性方法。该方法基于正交最小二乘技术,利用对应最小特征值的两个特征向量,构造了一个3×3的广义特征值问题,该问题的解不仅给出了基本矩阵,而且给出了相应的极点。与其它方法比较,该方法可以获得更精确的结果。

The fundamental matrix plays important roles in machine vision. A new linear approach to estimating the fundamental matrix is presented. The approach is based on the orthogonal least squares technique for estimating the fundamental matrix. Using the two eigenvectors corresponding to the least two eigenvalues achieved by the technique mentioned above, it constructs a 3×3 generalized eigenvalue problem. The solutions to the problem give not only the fundamental matrix but also the corresponding epipoles. The performance of the new approach is compared with several existing linear methods. It is shown that the new approach achieves the higher accuracy.