Surface Spline Approximation on SO(3)
This work provides a new theoretical framework and practical kernels for approximating functions on the rotation group, which is relevant for applications in robotics, computer graphics, and molecular modeling.
This paper introduces a new class of conditionally positive definite kernels on SO(3) for approximation and interpolation, derived from Green's functions of differential operators. It provides L_p error estimates showing that the approximation order matches the L_p smoothness of the target function.
The purpose of this article is to introduce a new class of kernels on SO(3) for approximation and interpolation, and to estimate the approximation power of the associated spaces. The kernels we consider arise as linear combinations of Green's functions of certain differential operators on the rotation group. They are conditionally positive definite and have a simple closed-form expression, lending themselves to direct implementation via, e.g., interpolation, or least-squares approximation. To gauge the approximation power of the underlying spaces, we introduce an approximation scheme providing precise L_p error estimates for linear schemes, namely with L_p approximation order conforming to the L_p smoothness of the target function.