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Match 3D points with 99% outliers quickly with VOCRA

Match 3D points with 99% outliers quickly with VOCRA


Practical, Fast and Robust Point Cloud Registration for 3D Scene Stitching and Object Localization



3D point cloud registration ranks among the most fundamental problems in remote sensing, photogrammetry, robotics and geometric computer vision.


... existing robust solvers may encounter high computational cost or restricted robustness, ... propose ... VOCRA (VOting with Cost function and Rotating Averaging), for the point cloud registration problem with extreme outlier rates.


... first ... employ the Tukey's Biweight robust cost ... effective in distinguishing true inliers from outliers even with extreme (99%) outlier rates.


... second ... designing a time-efficient consensus maximization paradigm based on robust rotation averaging, serving to seek inlier candidates among the correspondences.


Finally, ... apply Graduated Non-Convexity with Tukey's Biweight (GNC-TB) to estimate the correct transformation


... show that our solver VOCRA is robust against over 99% outliers and more time-efficient than the state-of-the-art competitors.



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