基于线对应的单应矩阵估计及其在视觉测量中的应用

单应矩阵估计在视觉测量、摄像机标定、三维重建等领域有重要的应用价值, 但是在具体应用中如何鲁棒、精确地估计单应矩阵仍是一个没有很好解决的问题. 在研究和实际应用中我们发现,直接线性方法在基于线对应的单应矩阵估计中会出现在某些特殊的摄像机姿态下误差较大的情况. 针对这一情况, 我们提出了一种基于线对应的归一化单应矩阵估计方法并将其应用到视觉测量中,即通过简单的归一化操作使测量矩阵元素的大小分布尽量均匀, 从而降低了测量矩阵的条件数, 提高了算法的鲁棒性, 同时又保持了直接线性方法简单、快速、易实现等优点. 模拟实验和真实图像实验均验证了该方法的有效性.

Line-Based Homography Estimation and Its Application in Visual Metrology

Homography plays an important role in visual metrology,camera calibration and 3D reconstruction.However, how to robustly and accurately estimate a homography from images is still a difficult problem in practice.In this work,we found that in the line-correspondence based homography estimation by a DLT(Direct linear transformation)-like method, some gross estimation errors could arise under some camera configurations,especially when there exists image line(s) passing through(or close to)the origin of the image coordinate system.The underlying reason is that under such configurations,the magnitude of the elements in the measurement matrix could vary significantly,which in turn results in a large condition number of the measurement matrix,and non-robustness of estimation.To alleviate this problem,a new normalized estimation method is proposed in this work,which consists of a new data pre-normalizing step,followed by a standard DLT estimation,and in which the robustness and accuracy of the estimated homography are substantially enhanced.Our new method retains the traditional DLT's conceptual simplicity and computational emciency.Extensive experiments with both simulated data and real images validated our method.