关键词: 基本矩阵, 最小平方中值法, M估计法

Abstract: By analyzing the shortcoming of existing robust algorithms based on random sampling employed in estimating the fundamental matrix, combining the advantages of LMedS and M-estimators, a new L-M algorithm is proposed with high accuracy for estimating fundamental matrix. The algorithm uses the idea of LMedS method to construct an inliers set of matching points, in general, the inliers set does not contain false matches, but also exists bad locations. It uses Torr-M-estimators to compute fundamental matrix. M-estimators can get a accurate fundamental matrix when the inliers set only contains bad locations. Experimental results on a mass of synthetic data and real images show that the proposed algorithm has higher robustness and estimating accuracy in the case of Gaussian noise and mismatching.

Key words: fundamental matrix, Least Median of Squares（LMedS）, M-estimators