Yuehaw Khoo

Global Registration of Multiple Point Clouds Using Semidefinite Programming

Consider

Large-scale sensor network localization via rigid subnetwork registration

N

Non-iterative rigid 2D/3D point-set registration using semidefinite programming.

points in

Open Problem: Tightness of maximum likelihood semidefinite relaxations

\mathbb{R}^d

Towards non-iterative closest point: Exact recovery of pose for rigid 2D/3D registration using semidefinite programming.

and

SYSTEM AND METHOD FOR REAL-TIME ULTRASOUND GUIDED PROSTATE NEEDLE BIOPSIES USING A COMPLIANT ROBOTIC ARM

M

Integrating NOE and RDC using semidefinite programming for protein structure determination

local coordinate systems that are related through unknown rigid transforms. For each point we are given (possibly noisy) measurements of its local coordinates in some of the coordinate systems. Alternatively, for each coordinate system, we observe the coordinates of a subset of the points. The problem of estimating the global coordinates of the

Bias Correction in Saupe Tensor Estimation.

N

Residual Dipolar Coupling, Protein Backbone Conformation and Semidefinite Programming.

points (up to a rigid transform) from such measurements comes up in distributed approaches to molecular conformation and sensor network localization, and also in computer vision and graphics. The least-squares formulation of this problem, though non-convex, has a well known closed-form solution when

Integrated protein structure determination using NOEs and Residual Dipolar Coupling, using Semidefinite Programming

M=2