Different Aspects of the Registration Problem

In this talk, we discuss several variants of the rigid registration problem, i.e  aligning objects via rigid transformation. In the simplest scenario of point-set registration where the correspondence between points are known, we investigate the robustness of registration to outliers. We also study a convex programming formulation of point-set registration with exact recovery, in the situation where both the correspondence and alignment are unknowns.This talk is based on joint works with Ankur Kapoor, Cindy Orozco, and Lexing Ying. 

Yuehaw Khoo is an assistant professor in the statistics department of University of Chicago. Prior to this, he was a post-doc in Stanford and graduate student in Princeton. He is interested in scientific computing problems in protein structure determination and quantum many-body physics. In these problems, he focuses on non-convex, discrete or large scale optimization and representing high-dimensional functions using neural-network and tensor network.