Linear algorithm with high accuracy for estimating fundamental matrix

A cost function relative to residual errors is introduced, and a linear algorithm by exploiting the strategy of weighted translation transformation is presented. Firstly, the original input data is weighted and the centroid coordinates are calculated, and the origins of coordinates are translated to their centroids. Then, the matching points are normalized. Finally, the eight parameters of fundamental matrix (F-matrix) can be solved and the procedure of estimating the fundamental matrix with high accuracy can be achieved. Experimental results show that this algorithm performs very well in terms of robustness to outliers and noises. The algorithm is superior to other algorithms in residual errors and average epipolar distance and improves the accuracy of F-matrix.