运动估计算法是影响立体视觉定位精度的重要因素，传统的 3D-3D运动估计算法受噪声影响很大，计算精度不高。本文提出了一种基于 2D-3D双目运动估计的立体视觉定位算法。算法不使用运动后的特征点 3D坐标，而直接利用其 2D图像投影坐标。首先，利用 EPnP运动估计算法确定匹配内点和初始运动参数。接着，利用双目相机之间的 2D投影几何约束，提出了基于 Levenberg-Marquardt算法的 2×2D-3D运动参数优化算法，利用确定的匹配内点和初始运动参数，使特征点在立体相机左右图像上的再投影误差最小，从而达到最优的立体相机 2D-3D运动估计。仿真实验和户外真实实验表明: 本文算法获得了很高的计算精度、鲁棒性，大大优于传统的基于 3D-3D运动估计的立体视觉定位算法。

Motion estimation algorithm of stereo vision is one of the important factors which affect the accuracy of stereo visual localization. The traditional 3D-3D motion estimation is greatly affected by noise, so the accuracy of algorithm is not high. We propose a new stereo visual localization algorithm based on 2D-3D binocular motion estimation. In our method, 2D image projection coordinates is directly used instead of 3D coordinates of feature after motion. Firstly, EPnP motion estimation is applied to determine matching inliers and initial motion parameters. We propose 2×2D-3D motion parameters optimization method based on Levenberg-Marquardt algorithm and geometric constraints between the 2D projection of binocular cameras. Optimal 2D-3D motion estimation is achieved by minimizing the error between the observed 2×2D image points and the re-projected 2×2D image points of stereo cameras from the reconstructed 3D features. Simulated experiment and outdoor real experiment show that our method performs well in accuracy and robustness, and are better than traditional 3D-3D methods.