双视三维重建的高精度运动参数估计方法

从两幅透视图像恢复被摄目标的三维结构是计算机视觉最基本的任务之一，其中，运动估计算法的性能决定了最终的三维重建精度。首先讨论了双视成像的基本数学模型，并介绍了几种现有运动参数估计方法的基本原理和不足。随后，基于投影误差最小判决函数，提出了用于双像运动估计的改进非线性迭代优化方法。数值仿真结果表明，在大平移小旋转角及小平移大旋转角2种运动条件下，采用文中提出的方法，运动估计精度均有所提高。此外，根据运动参数的估计值对真实目标进行三维重建实验，结果表明尺度重建误差小于2%且角度误差在3°以内。

High Accuracy Motion Estimation Method Used for Three DimensionalReconstructing from Two Views

Recovering the 3D geometric structure of an observed object from its two perspective views is one of the most important tasks in the computer vision research. It’s well known that the accuracy of 3D reconstruction is mainly decided by the performance of motion estimation method. In the paper, the fundamental model of two-view imaging system is introduced and the principles and disadvantages of some motion estimation methods are analyzed. To improve the estimation accuracy, a modified non-linear iterative optimization method is proposed based on the projective error minimization. The numerical simulations prove that the estimation accuracy is improved either under large translation and small rotation or under small translation and large rotation. Furthermore, the proposed method is verified by reconstruction from two view images of simulated object and real object. The result shows that the metric error is below 2% and the angle error below 3°.