论文标题
立体声视觉的纠正同谱：分析解决方案的最小失真解决方案
Rectifying homographies for stereo vision: analytical solution for minimal distortion
论文作者
论文摘要
立体调整是确定两个图像变换（或同型）的确定，它们在两个图像上映射了相应的点，即3D空间中同一个点的投影，并在变换的图像中的同一水平线上。纠正用于简化后续的立体声对应问题并加快匹配过程。通常，纠正转换对所获得的图像引入透视扭曲，应将其最小化以提高以下算法的准确性，以处理立体声通讯问题。通常根据数值优化进行最佳转换的搜索。这项工作提出了一种封闭式解决方案，用于将镜头构造最小化的构图。实验比较证实了其解决以前公式的收敛问题的能力。提供了Python实施。
Stereo rectification is the determination of two image transformations (or homographies) that map corresponding points on the two images, projections of the same point in the 3D space, onto the same horizontal line in the transformed images. Rectification is used to simplify the subsequent stereo correspondence problem and speeding up the matching process. Rectifying transformations, in general, introduce perspective distortion on the obtained images, which shall be minimised to improve the accuracy of the following algorithm dealing with the stereo correspondence problem. The search for the optimal transformations is usually carried out relying on numerical optimisation. This work proposes a closed-form solution for the rectifying homographies that minimise perspective distortion. The experimental comparison confirms its capability to solve the convergence issues of the previous formulation. Its Python implementation is provided.
