论文标题
可分离的四分基本矩阵
Separable Four Points Fundamental Matrix
论文作者
论文摘要
我们提出了一种基于Epolar同构象分解的基本矩阵计算的新方法。我们分析了基于分解的表示的几何含义，并表明它直接诱导了两种独立的一组对应关系的连续采样策略。我们表明，在图像线上有四个对应关系的情况下，我们的方法可确保相对于当前最小方法的评估假设数量最少。我们在现实世界图像对上验证方法，提供快速准确的结果。
We present a novel approach for RANSAC-based computation of the fundamental matrix based on epipolar homography decomposition. We analyze the geometrical meaning of the decomposition-based representation and show that it directly induces a consecutive sampling strategy of two independent sets of correspondences. We show that our method guarantees a minimal number of evaluated hypotheses with respect to current minimal approaches, on the condition that there are four correspondences on an image line. We validate our approach on real-world image pairs, providing fast and accurate results.
