文档介绍：第12期 组合机床与自动化加工技术 No. 12
2021年12月 s. Then,
K-means ++ clustering algorithm is used to realize the clustering of image feature points, so as to reduce the
calculation of violent matching. On this basis, the sparse optical flow method is introduced into ORB feature
matching algorithm to complete the calculation of the motion vector of the feature points. According to the
estimated two-dimensional coordinates of the feature points in the image to be matched, the feature points
far away from the cluster center are eliminated, and the final feature matching result is optimized by random
sampling consistency algorithm. Finally, the experimental results show the feasibility and effectiveness of
the improved ORB feature matching algorithm.
Key words: ORB algorithm ； sparse optical flow method ； airborne visual navigation system ； K-means ++ ；
UAV
o引言 图像匹配算法的复杂性、实时性以及鲁棒性等方面提
出了更高要求⑵。
视觉同时定位与地图构建(Simultaneous Localiza­
2011年Rublee E等⑶提出了一种定向二进制简
tion And Mapping,SLAM)是实现无人机自主定位与导
单描述