Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A stability analysis of the fundamental matrix
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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Solving the fundamental matrix is an improtant research topic in computer vision. The relationship between the epipole and the parameters of fundamental matrix can be found from the fundamental matrix of rank 2. A new model is equivalent to the fundamental matrix of rank 2. The model of the fundamental matrix, whose rank equals 2. The can be provided. According to the relationship between the parameters, the epipole and the fundamental matrix model, a linear method which aviods the objective function of unconstraint programming solving a nonlinear equation with the element 4 and the power 8 is provided. It realized stable estimation of the fundamental matrix. In the same scene, our algotithm compared with the 8-Points algorithm and the RANSAC algorithm, indicates that our algorithm has smaller errors under certain case. The comparison of results indicates our method algorithm is feasible and has stronger practicability by experiment.