General fusion frame of circles and points in vision pose estimation

Abstract

A general fusion frame of circles and points in vision pose estimation is addressed. We present a very simple formula to solve camera pose with a single circle, and then develop a general fusion method to integrate solved poses of circles and points. Two steps including initial guess and non-linear optimization are used for vision pose estimation. Different situations such as one circle one point, circles with same rotation center axis and circles with different rotation center axis are discussed for initial guess. After that, a novel unified reprojection error for circles and points is defined to determine the optimal pose solution. Experiments with real images are carried out to validate the proposed method, and results show that the method is valid and high-accuracy available.