基于异常匹配点去除的基本矩阵优化估计

提出了一种基于异常匹配点去除的基本矩阵优化估计算法。第一，去除异常匹配点，并得到基本矩阵的初值；第二，根据对极距离最小准则非线性优化求解基本矩阵。实验结果从平均余差和平均对极距离两方面表明，该算法消除了异常匹配点对基本矩阵的影响，精度较高，具有一定的优势。

An Exceptional Points Removing Based Optimal Algorithm for Estimating Fundamental Matrix

This paper proposes an exceptional points removing based optimal algorithm for estimating the fundamental matrix. Firstly, the exceptional points are eliminated, and the initial value of the fundamental matrix is obtained. Secondly, a criterion of minimizing the epipoalr distance is used to nonlinearly optimize the initial fundamental matrix. It can be seen from the experiment results that this algorithm eliminates the bad effect of exceptional points on the fundamental matrix, thus it is more precise and has an advantage over other conventional algorithms in terms of both average residual error and average epipolar distance.