Logos: Local Geometric Support For High-Outlier Spatial Verification
2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)(2018)
摘要
This paper presents LOGOS, a method of spatial verification for visual localization that is robust in the presence of a high proportion of outliers. LOGOS uses scale and orientation information from local neighbourhoods of features to determine which points are likely to be inliers. The inlier points can be used for secondary localization verification and pose estimation. LOGOS is demonstrated on a number of benchmark localization datasets and outperforms RANSAC as a method of outlier removal and localization verification in scenarios that require robustness to many outliers.
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关键词
outlier removal,LOGOS,local geometric support,high-outlier spatial verification,visual localization,orientation information,inlier points,secondary localization verification,benchmark localization datasets,local neighbourhoods,pose estimation
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