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Deep Hough Voting for Robust Global Registration
[article]
2021
arXiv
pre-print
Point cloud registration is the task of estimating the rigid transformation that aligns a pair of point cloud fragments. We present an efficient and robust framework for pairwise registration of real-world 3D scans, leveraging Hough voting in the 6D transformation parameter space. First, deep geometric features are extracted from a point cloud pair to compute putative correspondences. We then construct a set of triplets of correspondences to cast votes on the 6D Hough space, representing the
arXiv:2109.04310v1
fatcat:s45vb7if5vgsno3fbcmxeyteha