基于视差空间运动估计的高精度立体视觉定位

Stereo Visual Localization Based on Motion Estimation in Disparity Space

立体视觉定位算法的运动估计通常在3D欧式空间中进行,但由于特征点3D坐标的噪声各向异性且分布不均匀,3D重建在深度方向上比另两个方向上的准确性差,从而导致3D欧式空间运动估计精确不高。本文提出了一种新的基于视差空间运动估计的高精度立体视觉定位算法。算法首先采用视差空间4点闭环线性解法和RANSAC算法得到初始鲁棒运动估计和匹配内点。接着,利用新的视差空间再投影误差函数提出了基于LM算法的视差空间运动参数非线性优化方法,对初始运动参数进一步优化。视差空间噪声分布均匀且各向同性,本文的初始运动参数线性估计和非线性优化都在视差空间中进行且能达到全局最小。仿真实验和真实实验结果表明,本文算法能得到高精度的立体视觉定位结果,优于传统的3D欧式空间运动估计方法。

The motion estimation in stereo visual localization is usually carried out in 3D Euclidean space.3D points are corrupted with heteroscedastic and anisotropic noise,and the depth direction of 3D reconstruction is less accurate than the two other direction.And therefore,the accuracy of motion estimation in 3D Euclidean space is low.We propose a new high-precision stereo visual localization algorithm based on motion estimation in disparity space.Initial robust motion parameters and matching inliers are obtained by four points closed-form linear motion estimation in disparity space combined with RANSAC algorithm.Then,we propose nonlinear motion optimization method based on L-M algorithm in the new disparity space re-projection error function.The mothod is appied to optimise the initial motion parameters.The noise in disparity space is homogeneous and isotropic,and our initial linear motion estimation and nonlinear optimization method all are carried out in disparity space and can achive globally minimum.Simulated and real experimental result show that our method can achive higher localization accuracy than traditional motion estimation method in 3D Euclidean space.