基于ORB特征匹配的全局运动估计

为提高全局运动估计的准确性,提出一种基于定向旋转不变性(oriented FAST and rotated BRIEF,ORB)特征匹配的全局运动估计算法.首先对差分图像进行分块,通过设定阈值来筛选出有效的背景运动模块,然后经ORB特征匹配后,代入六参数运动模型,通过最小二乘法求解出估计参数,最后对当前帧做补偿,比较补偿前后的差分图像中的目标轮廓的清晰度.实验结果表明:该算法能有效去除局部运动的影响,在保证全局运动估计准确性的同时,也确保该算法的有效性.

Global Motion Estimation Based on ORB Matching

In order to improve the accuracy of global motion estimation, this paper proposes a global motion estimation method based on oriented FAST and rotated BRIEF (ORB) features. Firstly, the difference image is divided into blocks, and the effective background motion module is selected by setting the threshold. Then, the selected background modules are matched by the ORB feature, and substituted into the six-parameter motion model. Finally, the estimation parameters are solved by the least squares method, which are used to compensate the current frame. Compare the sharpness of the target contour of difference image before and after compensation. The experimental results demonstrate that the proposed algorithm can effectively remove the influence of the local motion and ensure the accuracy of the global motion estimation, while ensuring the effectiveness of the algorithm.