基于竞争规则和挡板辅助的基础矩阵估计算法

基础矩阵估计是计算机立体视觉的关键环节,对它的估计精度将直接影响对应点的匹配和特征点坐标的重构计算.笔者通过研究现有基础矩阵估计方法,分析它们的性能和优缺点的基础上,提出了改进TorrM estimators基础矩阵估计方法,并通过竞争规则选择初始值和利用印有标准图案的挡板辅助计算,有效地消除了出格点的影响,提高了基础矩阵估计精度,精确恢复了外极几何关系.

A Fundamental Matrix Estimation Method Based on Competition Rules and Auxiliary Mask

Fundamental matrix estimation is a key problem of computer stereo vision, and its estimated accuracy will have a direct influence on corresponding points match and the reconfiguration calculation of feature point's coordinate. In this paper, studies on the present fundamental matrix estimation methods are carried out,and their performance, merits and demerits are analyzed. Based on these work, an improved Torr M-estimators is put forward. By selecting first value(F_0)based on competition and using the mask printed with standard pattern to assistant computation, outliers are wiped off effectively, the accuracy of fundamental matrix estimation is improved, and the epipolar geometric relation is resumed precisely.