AI RESEARCH
A Robust 3D Registration Method via Simultaneous Inlier Identification and Model Estimation
arXiv CS.CV
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ArXi:2008.01574v3 Announce Type: replace Robust 3D registration is a fundamental problem in computer vision and robotics, where the goal is to estimate the geometric transformation between two sets of measurements in the presence of noise, mismatches, and extreme outlier contamination. Existing robust registration methods are mainly built on either maximum consensus (MC) estimators, which first identify inliers and then estimate the transformation, or M-estimators, which directly optimize a robust objective.