Non-rigid point set registration: Coherent Point Drift

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Optimization (2019, methodology): “…[14], ii) image registration with Scale-Invariant Feature Transform (SIFT) [17] in combination with Fast Approximate Nearest Neighbors [25] for feature matching, and iii) treating each map as a set of occupancy points and employing the Coherent Point Drift (CPD) [16] for Point Set Registration.”
GMS: Grid-Based Motion Statistics for Fast, Ultra-Robust Feature Correspondence (2017, background): “More generally, our work is related to optical flow [13, 23, 4, 43, 33, 21, 1, 46], point based coherence techniques [48, 18, 29], patch-match based matchers [12] which directly use smoothness to help match estimation.”
Scanning 3D Full Human Bodies Using Kinects (2012, methodology): “Particularly, we use [33] to find the feature correspondences between Mn and M1.”
As-Projective-As-Possible Image Stitching with Moving DLT (2013, methodology): “The basis of their idea is the pointset registration method based on motion coherence [11].”
Point Set Registration: Coherent Point Drift (2009, methodology): “Finally, in our previous work, we presented the Coherent Point Drift (CPD) algorithm [26] for nonrigid point set registration.”
3D shape scanning with a time-of-flight camera (2010, methodology): “Our algorithm is inspired by the non-rigid registration approach for pairs of scans described in [20].”