A strategy to remove the mismatching feature points in multi-fisheye SLAM system is proposed to solve the problem of decreased positioning accuracy caused by significant distortion and apparent viewing angle differences in fisheye images.This strategy uses a coarse-to-fine feature point removal process,using the initial set of points in the coarse matching algorithm with a threshold of 0.6.In the fine removal phase,a pre-calibrated multi-camera model was used to convert the matched feature points into the same coordinate system and projected onto the unit sphere as a carrying vector,removing the mismatch using the outer pole constraints on the sphere.After removing mismatched feature points,a reprojection error function was established to optimize the initial pose and mapping points.This strategy was tested on 24 000 fisheye images.The results showed that the elimination strategy significantly reduced the mismatch rate,improved the initialization and localization accuracy,and effectively improved the positioning accuracy and performance efficiency of the system.
关键词
视觉SLAM/多目鱼眼相机/误匹配剔除/对极约束
Key words
visual SLAM/multi-fisheye camera/elimination of mismatched/epipolar constraint
维普
万方数据