A Robust Fundamental Matrix Estimation Method Based on Epipolar Geometric Error Criterion

• Main Authors: Kun Yan, Rujin Zhao, Enhai Liu, Yuebo Ma
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Computer vision; fundamental matrix; epipolar geometry; robustness
• Online Access: https://ieeexplore.ieee.org/document/8863980/

In this paper, a robust fundamental matrix estimation method based on epipolar geometric error criterion is proposed. First, the method removes outliers into the computation of the fundamental matrix instead of taking it as an independent processing step. The potential error corresponding points are eliminated by iteration to achieve the stable estimation of the fundamental matrix. Then, the epipolar geometry error criterion is used to identify outliers and the estimation results of the fundamental matrix are obtained during each iteration. The iterative process can converge quickly. Even if a large number of matched outliers are present, the calculated values will soon become stable. Experiments have been carried out for synthetic and real image pairs, which show that the proposed method performs very well in terms of robustness to noises and outliers. Additionally it has a low computational cost and is convenient for use in practical applications.