摘要
针对单目视觉里程计的精确定位问题,提出一种专门应用于单目视觉里程计的特征点匹配方法。对FAST算法提取的特征点进行DELAUNAY三角剖分,获得特征点的位置关系。采用LK算法获得匹配点,结合位置关系判断误匹配候选点。对候选点计算SIFT描述子,根据相似程度剔除误匹配点。对获得的匹配对估计基础矩阵,结合尺度信息求取位姿。实验结果表明:该算法可提升匹配点的正确率,提高单目视觉里程计的精度。
Aiming at the problem of precise positioning of monocular vision odometer,a method of feature point matching specifically applied to monocular vision odometer is proposed. Firstly,DELAUNAY triangulation is performed on the feature points extracted by the FAST algorithm to obtain the position relationship of the feature points. Afterwards,the matching points are obtained by using LK algorithm,and mis-matching candidate points are judged according to the position relation. Then,the SIFT descriptor is calculated for the candidate points and the mis-matching points are eliminated according to similarities. Finally,estimate basic matrixes for obtained matching pair,obtain the pose based on the scale information. Experimental results show that the algorithm can improve the accuracy of matching points and improve the precision of monocular vision odometer.
引文
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