Rongjie Lai, Rensselaer Polytechnic Institute (RPI)


Non-Rigid Point Cloud Registration Using Robust Sliced-Wasserstein Distance via Laplace-Beltrami Eigenmap


In this talk, I will discuss our recent development on computational models and algorithms for point clouds registration based on the optimal transport theory via Laplace Beltrami eigenmap. Our methods use robust sliced-Wasserstein distance, which is as the average of projected Wasserstein distance along different directions, and incorporate a rigid transformation to handle ambiguities introduced by the Laplace-Beltrami eigenmap. This method provides both generality and flexibility to handle general point clouds setting. By going from smaller n, which provides a quick and robust registration (based on coarse scale features) as well as a good initial guess for finer scale registration, to a larger n, our method also introduces an efficient, robust and accurate approach for multi-scale non-rigid point cloud registration.


Hongkai Zhao

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